PLC PID Control Explained Simply

A PID controller is the brain behind many automated processes. It helps a system automatically maintain a specific target, or “setpoint,” with great accuracy.

Unlike a simple ON/OFF switch, which can cause large swings, a PID uses a clever formula to make smooth, precise adjustments.

 In industrial settings, PID control is often run by a Programmable Logic Controller (PLC).

The PLC executes the PID algorithm and translates its calculations into commands that control machinery. 

This article will explain the core concepts of PLC PID control. It will break down how the “Proportional,” “Integral,” and “Derivative” terms work together to create a feedback loop that achieves and maintains a setpoint. 

We will explore the common challenge of “tuning” and provide practical examples of how PLC PID control is used in the real world. 

PLC PID Control Explained Simply

The Problem with Simple Control

Let’s begin with a relatable example: controlling the temperature in an oven. In the simplest system, this works like a light switch:

  • The oven’s setpoint is the desired temperature.
  • A sensor measures the current, actual temperature.
  • If the temperature is too low, the controller turns the heater ON.
  • If the temperature is too high, the controller turns the heater OFF.

This strategy is known as ON/OFF control. It is simple, but it has a big problem. It causes constant swings above and below the setpoint. The heater overshoots, then shuts off, then undershoots, and the cycle repeats.

This leads to inefficiency. The equipment experiences more stress and wears out faster.

For processes where high precision matters, like chemical reactions or semiconductor manufacturing, this is unacceptable.

That is why industries use PID control. It takes a smarter approach, one that reduces oscillations and provides smoother, more accurate control.

The Foundation: The Feedback Loop

At the heart of PID control lies a feedback loop. This is the continuous cycle where the system checks itself, compares values, and makes corrections.

There are four key parts to understand:

Setpoint (SP)

The target value. For example, keeping an oven at exactly 100 °C.

Process Variable (PV)

The actual measured value. This comes from a sensor, like a thermometer.

Error (E)

The difference between the setpoint and the process variable. Formula: E = SP – PV.

Control Variable (CV)

The output signal calculated by the PID algorithm and sent by the PLC to the equipment. For an oven, this could be the amount of power delivered to the heater.

The goal of the PID controller is simple in theory: make the error as close to zero as possible.

But in practice, achieving that balance requires the three components: P, I, and D — to work together. Each has a unique role in shaping how the system reacts.

The P, I, and D Explained

Proportional Term (P) – Reacting to the Present

The Proportional term is the most direct part of the equation. It creates a correction that is proportional to the size of the error.

  • If the error is big, the correction is big.
  • If the error is small, the correction is small.
  • As you approach the setpoint, the adjustment becomes gentler.

You can compare it to pressing the gas pedal in a car. If you are far from your target speed, you press harder. As you get close, you ease off.

But proportional control has a weakness. It often leaves a small, constant error known as offset.

This happens because the controller always needs some error to generate an output. The system gets close to the setpoint, but not exactly there.

Integral Term (I) – Learning from the Past

The Integral term solves the offset problem. It looks at the error not just in the present, but over time.

  • It adds up the error history, essentially remembering how long and how large the error has been.
  • If a small error keeps occurring, the integral term grows until it pushes the system to eliminate it completely.
  • Over time, this ensures the process reaches the exact setpoint.

But there is a catch. If the integral is set too strong, the system can overshoot. This means it goes past the setpoint and swings back, sometimes several times.

A related issue is integral windup, where the integral keeps building even when the actuator is already at maximum output.

Derivative Term (D) – Predicting the Future

The Derivative term acts like a predictor. It looks at how quickly the error is changing and estimates where it is headed.

  • If the error is rising fast, the derivative provides a damping force to slow it down.
  • This prevents overshoot and improves stability.
  • It is especially useful in fast-moving processes, like speed control in motors.

However, derivative control is sensitive to noise. If the sensor signal is noisy, the derivative will amplify it, causing jerky outputs. For this reason, many industries use just PI control instead of full PID.

The Role of the PLC

In the past, engineers had to build dedicated hardware for PID control. Today, modern PLCs make it much easier. They come with built-in PID function blocks.

Integration

A PLC connects the sensor inputs (PV) and the actuators that carry out the control variable (CV).

Programming

In the PLC software, you simply insert a PID block, connect the PV and SP signals, and link the output to the device.

Tuning

The PLC stores the gain values for P, I, and D. You can adjust them directly through the interface.

This makes PID implementation more accessible. Even technicians who are not control theory experts can use PLC software to set up and tune loops.

Tuning Your PID Loop

Tuning is the art of adjusting the P, I, and D parameters until the system behaves well. The perfect settings depend on the process.

Start with P

Begin with only proportional control. Increase the gain until the system starts to oscillate, then reduce it to about half.

Add I

Introduce a small integral value. This removes steady-state error. Increase it slowly until the error disappears without causing big swings.

Add D (if necessary)

If your process reacts quickly or tends to overshoot, add a little derivative action for damping.

Auto-tune

Many modern PLCs have an auto-tune feature. The system runs a test, observes behavior, and automatically suggests PID values.

Good tuning balances speed, accuracy, and stability. Poor tuning causes overshoot, oscillations, or sluggish response.

Real-World Examples

Let’s look at where PID control in PLCs is actually used:

Temperature Control

In an industrial oven, the PLC reads temperature from a thermocouple (PV). It compares it to the setpoint (SP). The PID output adjusts gas or electric heaters. The result is precise, stable heating.

Flow Control

In pipelines, a PLC measures flow rate with a flow meter. The PID loop adjusts a motorized valve. This keeps the liquid flowing at the correct rate.

Pressure Control

In compressed air systems, a PID loop keeps tank pressure constant. It does this by controlling a compressor or a pressure valve.

Level Control

In tanks, the PLC monitors liquid level with a sensor. The PID loop controls pumps or valves to maintain the level.

Speed Control

Conveyor belts often require consistent speeds. A PID loop uses feedback from an encoder and adjusts the motor drive to hold steady speed.

Key Takeaways: PLC PID Control Explained Simply

PLC PID control is one of the most important tools in industrial automation. It is flexible, powerful, and surprisingly simple once you understand the basics.

Instead of crude ON/OFF control, a PID controller gives you three smart strategies — Proportional, Integral, and Derivative.

Together, they make the system respond not only to the present error, but also to past trends and future predictions.

A well-tuned PID loop can handle small drifts, sudden disturbances, and long-term stability.

Thanks to modern PLCs, implementing PID is easier than ever. Built-in blocks and auto-tuning make advanced control accessible even for non-specialists.

The payoff is huge: stable processes, better quality products, reduced wear on equipment, and more efficient energy use.

With a strong grasp of PID basics, you can start unlocking the full power of your automated systems.

FAQ: PLC PID Control Explained Simply

What does “PID” stand for in a PID controller?

PID stands for Proportional, Integral, and Derivative. These are the three control actions or terms that combine to determine the controller’s output based on how far, how long, and how fast the system error is changing.

What is a PID controller’s basic purpose?

A PID controller continuously compares a process variable (PV) with a desired setpoint (SP).

It then calculates an error (SP − PV), and uses the P, I, and D terms to adjust the output in order to reduce that error. The goal is to bring the process variable to the setpoint and keep it stable.

What does each term (P, I, D) do?

Proportional (P): Reacts to the current error. Larger error → larger correction. Helps reduce rise time but can leave a steady-state error.

Integral (I): Accumulates error over time. It addresses steady error or offset that P alone cannot eliminate.

Derivative (D): Looks at the rate at which error is changing. It acts to dampen or slow the controller’s response to prevent overshoot or oscillations. It’s like anticipating what might happen next.

Why is PID tuning important, and what are some common tuning methods?

Tuning means selecting or adjusting the gains (or time constants) of P, I, and D so the controlled process responds nicely (fast, stable, minimal overshoot, minimal steady error).

Without good tuning, the system might oscillate, respond too slowly, or constantly overshoot. 

Common tuning methods include: Manual tuning, by observing system behavior (e.g. increase P until borderline oscillation, then adjust I and D).

Auto-tuning, where the controller itself runs experiments to estimate good gains; Empirical rules like Ziegler-Nichols method.

What is “integral windup”, and how can it be prevented?

Integral windup occurs when the integral term builds up too much error — for example while the output is saturated (at its maximum or minimum limit) and cannot respond further.

When the constraint is removed, this “built up” integral can lead to overshoot or long settling times.

Prevention strategies include: Limiting or bounding the integral term; Using anti-windup logic (e.g. disabling integration when output is saturated or using back-calculation).

Can a PID controller have a simple ON/OFF output?

Yes, though that depends on application. The core PID algorithm usually produces an analog or continuously varying output.

But in some systems, that analog output is converted (via things like PWM or duty cycling) into ON/OFF switching to control physical devices (like heaters) that can’t respond continuously. 

What are the limitations of PID control?

Some limitations include: Sensitivity to noise, especially in the derivative term. Difficulties with non-linear systems or processes whose behavior changes with operating conditions.

Challenges in responding to large or sudden disturbances or changes in setpoint. If the system has long delays (dead time), PID can struggle; Potential overshoot or oscillations if tuning is not done properly. 

What is a “control loop” and what types are there?

A control loop refers to the cycle where the system measures a variable (PV), compares it with the desired value (SP), computes the error, uses a controller to adjust an actuator (CV), and affects the process, which feeds back into PV. This happens continuously.

Types include: Open loop, where no feedback is used — the controller doesn’t see the output; Closed loop, which is what PID control is — feedback is used to adjust continuously. 

How does the derivative term affect stability?

The derivative term adds damping. It helps reduce overshoot and smooth out fast changes.

That improves stability when things are changing rapidly. However, if derivative gain is too large, or if the sensor signal is noisy, it can cause erratic controller output or instability. 

What is “dead time” and how does it impact PID control?

Dead time (or delay) is the time lag between when the controller output changes and when its effect is first observed in the process variable. Long dead times make control harder because the system reacts slowly.

They can degrade performance, cause overshoot or oscillation, or make tuning more difficult. 

When might you use PI control instead of full PID?

PI (Proportional + Integral) control is often enough when the process is slower, or derivative action is not helpful (for example because of sensor noise, or small benefit versus complexity).

Many industrial applications omit the derivative term to simplify control and avoid amplifying noise. 

Dedicated PID devices vs. using a PLC for PID loops — which is better?

It depends on scale and complexity: Dedicated devices (stand-alone PID controllers) are good for simple, localized control (one loop, local HMI), fast deployment, less programming overhead.

PLCs are better when you need multiple loops, integration with other automation logic, data logging, supervising, HMI, alarms, etc.

They offer flexibility, communication, easier maintenance when multiple loops or complexity are involved.

15 Common PLC Programming Mistakes to Avoid

Programmable Logic Controllers (PLCs) sit at the heart of modern industry. They control machines, production lines, and entire plants.

A well-written PLC program can make a factory run smoothly while a poorly written one can cause downtime, safety issues, and costly repairs.

Programming a PLC is not just about making it “work.” It’s about making it reliable, safe, readable, and easy to maintain.

Many beginners, and even experienced programmers, fall into common traps. The good news? Most of these mistakes can be avoided with awareness and good habits.

This article explores the most common PLC programming mistakes. We’ll explain why they happen, what problems they cause, and how to avoid them.

Whether you’re a student, technician, or engineer, these lessons can save you time, stress, and money.

Mistake 1: Poor Documentation

One of the most overlooked parts of PLC programming is documentation. We usually rush to write code and forget to label inputs, outputs, or describe logic.

If you re-open the same program in the future, you will see hundreds of rungs, all with cryptic tags like the one shown in the figure below. You have no idea what they control. Troubleshooting becomes a difficult task.

Problem: ItMakes maintenance slow; Leads to confusion for others (or even yourself); Increases risk of errors when modifying code.

Avoidance: Use clear tag names. Instead of “X0, X1, Y0, Y1” use “ReadyToRun.”, add rung comments to explain what each section does and keep a separate document with I/O lists, wiring diagrams, and descriptions. See the figure below:


Takeaway: Good documentation is like leaving a roadmap for the next person and sometimes, that “next person” is you.

Mistake 2: Overcomplicating the Code

“The more complex the code, the smarter it looks”, this is a belief to some programmers. The truth is the opposite. Overcomplicated logic is harder to read, harder to debug, and more prone to failure.

Problem: Increases programming time, makes troubleshooting difficult and confuses technicians who may not be programmers.

Example:
Instead of using three rungs with simple logic, someone nests ten different conditions into one rung. The machine may still work, but no one else understands how.


Avoidance: Keep logic simple, one rung should handle one clear task, break large processes into smaller sections and use function blocks or subroutines for repeated logic.


Takeaway: Clarity beats cleverness in PLC programming.

Mistake 3: Ignoring Safety

PLCs often control equipment that can harm people. Any mistake here isn’t just expensive, it can be deadly.

Common safety mistakes include:

  • Forgetting emergency stop circuits.
  • Relying only on software for safety instead of hardware interlocks.
  • Not handling fault conditions properly.

Problem: Risk of injury or death, legal and financial consequences and loss of trust in the system.


Avoidance: Always design safety circuits in hardware first (e.g., safety relays, contactors), use safety-rated PLCs when needed and program fault detection and safe shutdown sequences.


Takeaway:  Safety should never be an afterthought.

Mistake 4: No Simulation or Testing

Many beginners write the code and immediately load it into the PLC. They skip simulation or offline testing. This is risky.

Problem: Errors appear only during machine operation, can cause equipment damage and/or wastes production time.

Avoidance: Use simulation tools built into programming software, test logic in small parts before full deployment and validate with the team before running on real hardware.

Takeaway:  Testing saves time in the long run.

Mistake 5: Poor Handling of Inputs and Outputs

A common error is assuming that inputs and outputs always behave perfectly. But in the real world, sensors fail, signals bounce, and wiring gets loose.

Examples of mistakes:

  • Ignoring sensor failure scenarios.
  • Driving outputs directly without considering feedback
  • Not debouncing mechanical switches.

Problem: Causes false triggers, leads to unexpected machine behavior and/or can create unsafe conditions.


Avoidance: Add timers or filters for noisy signals, always check for signal validity and add diagnostics for input and output status.


Takeaway:  Think about the “real” environment, not just the code.

Mistake 6: Ignoring Standard Programming Practices

Standards for naming, structuring, and documenting PLC code, is essential to every company or industry. Ignoring them makes your program look like a mess.

Problem: Makes collaboration hard, slows down troubleshooting and/or creates inconsistency across machines.

Avoidance: Follow IEC-61131-3 programming standards, use consistent naming for tags and variables and stick to templates or guidelines provided by your company.

Takeaway:  Standards exist to make everyone’s life easier.

Mistake 7: Not Planning Before Coding

Jumping straight into programming without planning is a classic mistake. A PLC program is like a building. Without a blueprint, it collapses.

Problem: Leads to messy logic, misses important steps in the process and/or wastes time rewriting code.

Avoidance: Write down the sequence of operations first, draw flowcharts or state diagrams and discuss the plan with colleagues before coding.

Results:  Good planning reduces mistakes later.

Mistake 8: Forgetting About Maintenance

A PLC program is rarely “done.” Over time, technicians may need to adjust, expand, or troubleshoot it. If you don’t think about them, you make their job harder.

Problem: Increases downtime during repairs, creates frustration for maintenance staff and/or makes your system unpopular with the team.

Avoidance:  Use clear labels and comments, group related logic together and provide clear diagnostic messages on HMIs.

Takeaway:  A program that’s easy to maintain is a program that lasts.

Mistake 9: Overusing Timers

Timers are useful, but too many programmers use them as a crutch. For example, instead of checking when a motor is actually running, they just “wait 5 seconds” before moving on.

Problem: Makes the system slow, fails if equipment doesn’t behave as expected and/or creates hard-to-troubleshoot delays.


Avoidance: Use sensors and feedback whenever possible, apply timers only when necessary and document why each timer is used.


Takeaway:  Timers should support logic, not replace it.

Mistake 10: Not Considering Power Loss or Restarts

What happens when the PLC loses power? What if the machine restarts after a fault? Many programmers don’t think about these cases.

Problem: Motors may start unexpectedly, equipment may reset to unsafe states and/or production data may be lost.


Avoidance: Define safe startup conditions, save critical data in retentive memory and add logic to handle controlled restarts.


Results:  Always expect the unexpected.

Mistake 11: Lack of Version Control

In many plants, different people modify the same PLC program over time. Without version control, you lose track of changes.

Problem: Hard to know which version is correct, risk of reintroducing old bugs and/or wastes time comparing files manually.

Avoidance: Use version control software (Git, SVN, etc.), keep backup copies with clear version numbers and document changes in a log.

Takeaway:  Version control prevents chaos.

Mistake 12: Ignoring Communication Issues

Modern PLCs often communicate with HMIs, SCADA systems, or other PLCs. Poorly handled communication causes big problems.

Common issues:

  • No error handling when messages fail.
  • Overloading the network with too many updates.
  • Using unclear data mapping.

Problem: Causes slow or unreliable systems, leads to wrong data on screens and/or creates headaches for IT teams.

Avoidance: Test communication under real conditions, use retries and error handling and document data addresses clearly.

Takeaway:  Communication is as important as logic.

Mistake 13: Forgetting Scalability

Many programmers only write code for today’s needs. But machines often evolve. If your code doesn’t scale, future upgrades become painful.

Problem: Hard to expand the program, leads to rewrites and/or costs more in the long term.

Avoidance: Use modular design, plan for extra I/O and functions and think about future needs, not just current ones.

Takeaway:  Scalable code saves time later.

Mistake 14: Relying Too Much on Copy-Paste

Copying and pasting code may seem efficient. But without careful review, it spreads mistakes everywhere.

Problem: Duplicates errors, creates inconsistent logic and/or makes debugging harder.

Avoidance: Reuse logic with structured programming, not blind copy-paste; review every section after copying and use templates where possible.

Takeaway:  Copy-paste is a tool, not a solution.

Mistake 15: Forgetting the Human Factor

At the end of the day, humans use and maintain PLC-controlled machines. Programs that ignore the human factor cause frustration.

Problem: Operators struggle with unclear HMIs; maintenance takes longer and/or training new staff becomes harder.

Avoidance: Design user-friendly HMI screens, show clear alarms and messages and Think from the operator’s perspective.

Takeaway:  A program should serve people, not confuse them.

Conclusion: Common PLC Programming Mistakes to Avoid

This article discussed the most common PLC programming mistakes. It explained why they happen, what problems they cause, and how to avoid them.

After revised these details, we could dare to say that PLC programming is more than writing logic. 

It’s about creating systems that are safe, reliable, and easy to maintain. The mistakes we’ve covered poor documentation, overcomplicated code, ignoring safety, skipping testing, and more, are common but avoidable.

Good programming comes from habits: plan first, keep things simple, document everything, and always think about safety.

Remember that your program will live on long after you write it. Someone else may maintain it, modify it, or rely on it to keep a machine running.

Avoiding these mistakes won’t just make you a better PLC programmer. It will make you a more valuable engineer, a trusted teammate, and someone who builds systems people can rely on.

FAQ: Common PLC Programming Mistakes to Avoid

What are the most frequent PLC programming mistakes?

Naming few: Neglecting documentation; Hard-coding values; Overcomplicating logic; Poor naming and lack of comments; Skipping requirement planning.

How can I improve naming and comments in PLC programs?

Use descriptive tags, Motor_Start; Write comments that explain “why”, not just “what.”;  Adopt a standard naming convention use prefixes (like in_, out_, aux_) and stay consistent.

Why is planning before programming important?

Skipping system requirements invites hidden bugs and unpredictable behavior. Planning ensures you: Capture every operational requirement, including safety and timing; Break down functionality clearly using flow charts or P&IDs; Avoid scope drift and costly revisions.

How do I avoid overcomplicated logic?

Modularize: Break logic into small, reusable function blocks or routines; Eliminate redundancy: Avoid replicating logic across different sections; Follow structured design: Keep branching and nesting shallow for better readability

What are the downsides of hard-coding values?

Every change demands reprogramming, PLC download, and revalidation; Instead, use variables or HMI-alterable parameters so adjustments don’t require touching the core code

What is insufficient error-handling, and why does it matter?

Neglecting fault conditions (like sensor failures or network errors) can allow the PLC to behave unpredictably.

What errors happen due to poor testing? 

Mistakes that slip into live systems often cause: unexpected stoppages or unsafe behavior; Missed edge-case bugs (like sensor delays or unusual system states).

What common mistakes do real-world programmers face? 

From practitioner discussions: Dumb tag names and inconsistency in programming and naming conventions; “Designing for machinery but not HMI—like setting an indicator bit for a fraction of a second, which can cause freeze-ups if communication fails.

The Best PLC Simulation Software in 2025

We use simulation to virtually test and analyze designs, systems, and processes. This helps to improve safety, efficiency, and cost effectiveness and reduce the need for physical prototypes. 

Simulation ensures that product will function as intended in real-world conditions. This digital approach allows for faster iteration, exploration of various design options, and prediction of potential issues before committing to expensive manufacturing. 

Running PLC code on a simulator before loading it into real hardware is one of those things that can save us hours of frustration. That is why important to make a good choice of which software to use

So, this article describes the best simulation tools available, highlight what each one does best, and share some practical advice to help you choose the right fit for your situation.

Criteria for a Good PLC Simulator

Simulation platforms are developed with different objectives. Some are specifically designed for educational environments, others are intended for advanced industrial validation, while several serve as a bridge between the two. The following are key aspects that merit attention, based on:

First, Realistic runtime: The best simulators must behave like an actual PLC. It completes with scan cycles, CPU load, and communication stacks. This realism is crucial when you need to validate logic under near-production conditions.

Second, Integration with IDEs: If the simulator runs directly inside your programming environment such as, TIA Portal, Codesys, or Studio 5000, you won’t waste time copying projects back and forth.

Third, Connectivity options: Real projects rarely run-in isolation. Having virtual Modbus, Profinet, or EtherNet/IP endpoints allows you to test how your logic interacts with HMIs, SCADA, and other devices.

Fourth, Visualization: For training and debugging, being able to “see” sensors, conveyors, and actuators in action makes the whole process far more engaging.

Fifth, Automation support: If you’re running repeated tests (like regression checks), scripting or APIs let you run simulations automatically rather than by hand.

Sixth, Licensing and cost: Some tools are open-source and free, while others are tied to expensive vendor ecosystems. Often, your budget (or your customer’s hardware choice) will narrow the field.

The Best Tools in 2025

Our research found that the best tools by 2025 are:

First, Siemens S7-PLCSIM / PLCSIM Advanced: best for Siemens users who want near-perfect virtual controllers.

Second, CODESYS with simulation runtime: best for portability and multi-vendor learning.

Third, Factory I/O + connectors: best for classrooms, training labs, and visual learners.

Fourth, OpenPLC: best free, open-source option for students and hobbyists.

We are going to discuss about them one-by-one.

About Siemens S7-PLCSIM / PLCSIM Advanced

PLCSIM, and PLCSIM Advanced, give you a virtual version of an S7 controller right inside TIA Portal. That means you can load the exact compiled program you’d run on a real S7-1200 or S7-1500, complete with I/O and communication options.

Why Yes: If your plant runs on Siemens’ hardware, this simulator is the most faithful digital stand-in. It’s great for checking logic, testing HMI interactions, and even simulating faults.

Why No: It’s very much tied to Siemens’ ecosystem. If you’re programming for other vendors, it won’t help you much. It’s also a licensed product, so it comes with a price tag.

Best for: Training centers working in Siemens, Integrators or commissioning engineers only environments.

Extra: Make sure your TIA Portal release is being matched by your version of PLCSIM. You can set up virtual Ethernet interfaces to connect to HMIs or OPC servers for realistic network tests.

CODESYS (IDE + Runtime)

CODESYS has become a household name in the automation world because it’s vendor-agnostic.

You can use it to program devices from WAGO, Festo, Beckhoff variants, and countless OEMs.

Built into the IDE is a solid simulation feature, so you can run your project without needing real hardware.

Why Yes: Portability. You can learn IEC 61131-3 programming in one place and later move your project to different hardware with minimal adjustments. It’s also widely used in academic programs.

Why No: While the simulation is good, you may still need hardware-in-the-loop testing to check specific timing or vendor-specific features.

Best for: Engineers working in environments where multiple hardware brands are in play, educators or students.

Extra: Use the built-in “softPLC” runtime for local testing, and try adding visualization objects to simulate HMI integration right in the IDE.

Factory I/O

Factory I/O isn’t a PLC programming environment, instead it’s more like a 3D virtual factory that you can connect your PLC or softPLC to. Think of conveyor belts, sensors, motors, and robots you can control with your ladder logic.

Why Yes: The visual aspect makes learning and debugging far easier. You can literally see the effect of your program on a conveyor or robotic arm, which is great for teaching and training.

Why No: Since it’s not a PLC IDE, you’ll still need another tool (like OpenPLC, PLCSIM, or Codesys) to actually run the logic. Some users also find the licensing a bit expensive for classroom setups.

Best for: Anyone who benefits from a visual, hands-on simulation environment, training labs, or classrooms.

Extra: Pair Factory I/O with OpenPLC for a cost-effective learning setup. Connect the two via Modbus/TCP and start experimenting with ladder logic sequences right away.

OpenPLC

OpenPLC is the open-source alternative to the big-name simulators. It supports ladder logic, structured text, and other IEC 61131-3 languages, and it runs on everything from Windows PCs to Raspberry Pi boards.

Why Yes: It’s free, open, and flexible. For students or small labs, it’s an affordable way to get into PLC programming. Plus, because it’s open-source, you can actually dig into the code if you’re curious.

Why No: It’s not meant to replace certified industrial-grade PLCs in critical systems. You won’t get the same ruggedness, timing guarantees, or official vendor support.

Best for: Proof-of-concept projects where cost is a concern, hobbyists or students.

Extra: Use OpenPLC Editor alongside Factory I/O, or deploy the runtime on a Raspberry Pi to create your own mini testbed.

How to Make Decision 

We have put conditions for selection:

  • WHETHER  you’re tied to a vendor   THEN   stick with their simulator.
  • WHETHER  you want portability  THEN  CODESYS or OpenPLC.
  • WHETHER  you need visualization THEN add Factory I/O to the mix.
  • WHETHER  budget is your main concern THEN OpenPLC + Factory I/O is the cheapest effective combo.
  • WHETHER  you need automated testing  THEN look for tools with APIs or scripting support (PLCSIM Advanced and some vendor tools offer this).

Advancement

  • For students: Start with CODESYS or OpenPLC, and pair with Factory I/O if you want visuals.
  • For OEM developers: Use vendor IDEs or CODESYS, simulate with virtual controllers, and integrate Factory I/O for testing.
  • For commissioning teams: Stick with vendor-grade simulators like PLCSIM Advanced or Rockwell Emulate for the most accurate results.

Conclusion 

IT DOESN’T exist a single best PLC simulator, it really depends on your goals, your hardware, and your budget.

Generally, incorporating a vendor-specific tool (for accuracy) with something visual or open-source (for learning and portability) gives you the best of both worlds.

Simulation isn’t just about saving time; it’s about building confidence in your code before it ever touches a real machine.

Start small, validate early, and let the simulator do the heavy lifting before the plant floor does.

Last but not least, if you ask me personally “ The Best PLC Simulation Software in 2025

” my answer would be CODESYS.

FAQ: Best PLC Simulation Software

What are the top PLC simulation/emulation tools in 2025?

Siemens TIA Portal (PLCSIM/PLCSIM Advanced), CODESYS (with simulation/runtime), Beckhoff TwinCAT (PC-based simulation), Factory I/O, OpenPLC

How Does an Ultrasonic Sensor Work?

The rapidly evolving world of industrial automation, sensors play a critical role in bridging the gap between the physical and digital realms.

From a robotic arm detecting the exact position of an object to conveyor belt ensuring accurate material flow. 

Furthermore, an autonomous vehicle avoiding collisions. All this because the sensors are at the heart of decision-making.

Among the many sensor technologies used for distance measurement and object detection, the ultrasonic sensors have proven to be a versatile and cost-effective solution.

This article explains how ultrasonic sensors work, explores their applications in automation industrial, and provides their advantages and disadvantages.

Furthermore, it compares ultrasonic sensors with other distance-sensing technologies.

What Is an Ultrasonic Sensor?

An ultrasonic sensor is a device that measures the distance to an object by using sound waves.

This task is done at frequencies higher than the audible range of humans, which is above 20 kHz, as it can seen in the figure below.

Infra – Ultrasound wave

Most of industrial ultrasonic sensors operate between 25 kHz and 70 kHz, though some specialized ones can go higher.

How does Ultrasonic Sensor Work?

The principle is based on echo-location, similar to how bats and dolphins navigate:

  • The sensor emits a short ultrasonic pulse called trigger.
  • The sound wave travels through the air until it hits an object.
  • The wave reflects back to the sensor (echo).
  • The sensor calculates the time of flight (ToF) of the sound wave.

From the information of the above, the following basic formula is deduced:

The division by 2 accounts for the round trip (going to the object and returning).

Working Principle in Automation World

In an automation system, ultrasonic sensors typically consist of transducer, control circuit and the outputs:

  • Transducer: Is in charge of converting an electrical signal into ultrasonic sound waves and vice versa.
  • Control Circuit: Generates the pulse signal (trigger) and processes the received echo.
  • Output Stage: Provides an analog or digital output for the automation controller such as PLC, microcontroller, or industrial PC.

Process Flow in Automation

From an automation point of view, the whole process of ultrasonic measurement works as explained below

  • Triggering: The automation controller commands the sensor to emit a pulse.
  • Propagation: The sound wave travels at approximately 343 m/s in air.
  • Echo Detection: The sensor detects the reflected signal.
  • Signal Processing: The time difference between sending and receiving is converted into distance.
  • Decision Making: The automation system uses this distance data for tasks such as object positioning, counting, or safety control.

Applications of Ultrasonic Sensors in Automation

  • Object Detection on Conveyor Belts: Detecting the presence or absence of packages and counting objects regardless of color or transparency.
  • Liquid Level Measurement: Monitoring tank levels in process industries (chemicals, food, water treatment).
  • Robotics and AGVs (Automated Guided Vehicles)
  • Collision avoidance and obstacle detection.
  • Packaging and Bottling Lines
  • Checking the fill level of bottles (especially transparent materials where optical sensors struggle).
  • Ensuring caps or lids are properly placed.
  • Automotive Automation: Parking assistance and blind-spot monitoring.
  • Industrial automotive robots using ultrasonic feedback.
  • People and Object Counting: Entry/exit monitoring in automated systems.
  • Smart building applications (lighting control, HVAC).

Advantages (Pros) of Ultrasonic Sensors

  • Non-Contact Measurement & Simple Integration
  • No physical contact needed, avoiding wear and contamination.
  • Insensitive to Object Color and Transparency
  • Works equally well on shiny, transparent, or dark surfaces, unlike optical sensors.
  • Good Range Versatility: Can detect objects from a few centimeters to several meters away.
  • Cost-Effective: Cheaper than laser rangefinders or 3D vision systems.
  • Ruggedness: Can work in dusty, smoky, or poorly lit environments where cameras or IR sensors fail.
  • Provides analog (voltage/current) or digital (switching) outputs directly compatible with PLCs.

Limitations (Cons) of Ultrasonic Sensors

  • Environmental Sensitivity: Sound speed changes with temperature, humidity, and air pressure, affecting accuracy.
  • Limited Resolution: Accuracy is typically within a few millimeters, not suitable for high-precision tasks.
  • Slow Response Time: Since sound travels slower than light, measurement cycle times are longer compared to laser or IR sensors.
  • Interference and Crosstalk: Multiple ultrasonic sensors operating close together can interfere with each other.
  • Angle Dependence: Works best when objects are perpendicular to the sensor. Slanted or sound-absorbing surfaces reduce detection reliability.

Comparison with Other Distance Sensors

In this chapter we address the comparison of our sensor in stud against other sensors that use the same technology

Ultrasonic vs Infrared (IR) Sensors

IR sensors use reflected infrared light to detect distance, but Ultrasonic works regardless of color or transparency, not affected by ambient light. Unfortunately, Ultrasonic have slower response and lower resolution 

Ultrasonic vs Laser Rangefinders (LIDAR)

Laser rangefinders measure distance using time of flight of light or phase shift, but Ultrasonic are cheaper, more rugged in dusty/dirty conditions. Although Ultrasonic have lower precision, shorter range, slower measurement.

Ultrasonic vs Vision Systems (Cameras + AI)

Vision systems provide rich data (shape, color, dimensions), while Ultrasonic are simple, inexpensive, and unaffected by lighting conditions.

On the other hand, Ultrasonic provides only distance information, no shape or color recognition.

Ultrasonic vs Capacitive/Inductive Proximity Sensors

Capacitive sensors detect changes in dielectric properties; inductive sensors detect metal objects.

On the other hand, Ultrasonic can detect any material (metal, plastic, glass, liquid). Although, Ultrasonic are larger size, slower response.

Future of Ultrasonic Sensors in Automation

With Industry 4.0 and IIoT (Industrial Internet of Things), ultrasonic sensors are evolving. Have started to include smart ultrasonic sensors with built-in temperature compensation to reduce environmental errors.

Network connectivity (EtherCAT, IO-Link, Modbus) for seamless integration in smart factories.

Process of miniaturization allowing their use in compact robotic systems. Also, hybrid sensing where ultrasonic sensors are combined with cameras or laser scanners for robust multi-sensor systems.

Conclusion

This article addressed about Ultrasonic sensors that use sound wave (echo-location) to obtain their measurement.

It also showed the applications of the later sensor together with the advantages and disadvantages. 

Furthermore, the comparison with other types of sensors was demonstrated as well as future of Ultrasound was discussed.

After the above discussion, we can agree that Ultrasound sensors are one of the most versatile and cost-effective distance sensing solutions in industrial automation. 

Their ability to detect objects regardless of color, transparency, or lighting conditions makes them indispensable in many applications, from conveyor belt monitoring to robotic navigation and liquid level measurement.

However, like any technology, they come with limitations: slower response, lower accuracy compared to optical systems, and environmental dependencies. The choice of sensor ultimately depends on the specific automation requirement. 

In many cases, ultrasonic sensors serve as the perfect balance between cost, reliability, and performance, particularly when paired with other sensor technologies.

 FAQ: How Does an Ultrasonic Sensor Work?

What is an ultrasonic sensor?

Ultrasound sensor is a device that is used to measure the distance. This sensor uses sound wave to detect how far the object is, just like bats and dolphins.

How does it operate?

It operates just like dolphin or bats, the send the wave and wait for it to reflect– back (echoing). Then they measure this delay time that is how they know how far is the object.

What’s the distance calculation formula?

Assume ToF is the that measure since the device send the wave until it echoed back, then
 

4. What components are involved?

It includes transducer, the component in charge of converting sound wave to electrical signal. A controller that processes the signal an send it to output.

What are the advantages?

Non-contact measurement, low coast, reliability, simple integration among others.

How to Measure a 4-20 mA loop Signal With a Multimeter

Process industries require monitoring of pressure, temperature, pH level, etc. for smooth operation.

These transmitters send information to PLCs or controllers on a 4 mA to 20mA loop.

Often engineers troubleshoot these transmitters by checking the 4 mA to 20 mA loop signal.

How the 4-20 mA loop works

The loop’s operation is straightforward: a sensor’s output voltage is first converted to a proportional current, with 4 mA normally representing the sensor’s zero-level output and 20 mA representing the sensor’s full-scale output. A reading of 20 mA means that a direct-acting valve, for example, is 100% open, and a reading of 4 mA means that it is closed. (The opposite is true for a reverse-acting valve). Readings between the maximum and minimum values indicate that the circuit is controlling the valve.

Verifying a 4-20 mA loop is a crucial step in both troubleshooting and calibrating process systems.

Full verification includes testing the output of the transmitter, the wiring, input to the control system and control system input card, and the return wiring back to the transmitter.

How to Measure a 4-20 mA loop Signal With a Multimeter

Here, I am going to show you two different methods on how to measure a 4-20 mA loop signal using a multimeter.

Method #1: Measure the 4-20 mA loop signal with the help of a multimeter

Identify the Loop Wiring

Find the two wires carrying the 4–20 mA signal from the transmitter or sensor to the controller/PLC.

Tip: Consult the device manual or wiring diagram.

Break the Circuit (Series Measurement)

Unlike measuring voltage (parallel), current measurement requires the multimeter to be inserted in series with the loop.

Choose a point where the loop can be safely opened (often at a terminal block or test point).

Power must remain ON in the loop for accurate measurement.

Configure the Multimeter

  • Turn the dial to DC mA (usually a 20 mA or 50 mA range is best).
  • Plug the red lead into the mA input jack (NOT the voltage or A high-current jack).
  • Plug the black lead into the COM jack.

Connect the Multimeter in Series

  • Disconnect one wire at the test point.
  • Connect the red lead to the wire coming from the transmitter.
  • Connect the black lead to the terminal going to the PLC/controller.
  • This way, the loop current flows through the meter.

Read the Measurement

A normal signal should read between 4.00 mA and 20.00 mA.

If you see:

  • <4 mA → Possible wiring issue, sensor fault, or calibration error.
  • >20 mA → Overrange condition or device malfunction.

Remove the Multimeter

Power down or hold the loop signal as needed.

Reconnect the wire directly to restore normal operation.

Method #2: Measure the 4-20 mA loop signal with the help of a process clamp meter

The functions of an advanced loop calibrator allow technicians to troubleshoot on the spot without disconnecting wires or “breaking the loop.”

Multifunction process calibrators can also be used to test 4-20 mA loops as well as digital controls.

Step 1: Access the wire connected to the ‘+’ terminal of the transmitter (no need to remove the wire).

Step 2: Put the process clamp meter in ‘Measure’ mode.

Step 3: Clamp the wire connected to the positive terminal of the transmitter and measure the mA signal as shown below.

You can use Fluke’s 771 or 772 or 773 process clamp meters to measure mA without breaking the loop.

Advantage of this method

You need not break the loop to measure the mA signal. This is the biggest advantage.

Disadvantage of this method

Process clamp meters are expensive.

Safety Tips when using a multimeter to measure 4-20 mA loop

Check Multimeter Rating

Ensure the multimeter’s current rating is suitable for the expected measurement.

Proper Probe Insertion

Confirm that the multimeter probes are correctly inserted into the appropriate ports (usually labeled COM and mA/µA).

Avoid Overloading

Do not exceed the multimeter’s current measurement limit to prevent damage to the multimeter and ensure personal safety.

Conclusion

Measuring a 4-20 mA signal with a multimeter involves setting the multimeter to the appropriate mode, connecting it in series with the current loop, and interpreting the readings.

This process helps ensure that sensors and transmitters in industrial control systems are operating correctly.

Always prioritize safety by powering down the circuit before making connections and ensuring the multimeter is properly rated for the measurements being taken.

How to Select the Right Gas Detection Solution

Selecting the right gas detection solution is critical to maintaining safety and compliance across various environments.

The process requires evaluating potential hazards, understanding site-specific conditions, and ensuring compliance with regional standards. Here’s a comprehensive guide to making an informed choice.

Why do you need a gas detection system?

Depending on the industry, many gases can be produced as a by-product or part of the process.

Gases such as benzene can cause cancer, and flammable gases such as propane and methane need to be monitored, and you need a system that will let people in those areas evacuate in case of any danger. 

What are gas detectors?

Gas detectors can detect explosive, flammable, and toxic gases and oxygen depletion.

This device is used widely in industry and can be found in locations such as oil rigs to monitor manufacturing processes and emerging technologies such as photovoltaics.

How to select the right gas detection solution for your plant

Many gas detection products on the market might appear to be the same. Still, a closer inspection of specifications, functionality, and features reveals major differences in what products can do and their potential value.

Similarly, individual applications’ designs, needs, and processes are unique.

Understand Site-Specific Risks and Hazards

Before selecting a gas detector, conduct a thorough risk assessment of the site:

Identify Potential Risks

Knowing which gases are present is essential. As you mentioned, a reliable approach is to use a gas analyzer or consult a third party for a detailed site evaluation. This will provide clarity on detectable gases and help mitigate risks effectively.

Consider Industry-Specific Requirements

Each industry faces unique risks. For instance, environments that involve chemical processing may require benzene detection.

In confined spaces, monitoring for gases like oxygen, hydrogen sulfide, carbon monoxide, and volatile organic compounds (VOCs) is essential.

To select the right gas detection system, it’s essential to understand the risks on-site. Using a gas analyzer or a third-party service can quickly reveal the gases you need to monitor.

For example, confined spaces often need detectors for oxygen, hydrogen sulfide, carbon monoxide, and VOCs.”

Choose the Right Type of Gas Detector

Different environments and applications may require either fixed or portable gas detectors:

Fixed vs. Portable Detectors

Fixed gas detection systems are ideal for continuous monitoring in high-risk or permanent areas, such as warehouses or industrial plants. Portable detectors, on the other hand, offer flexibility and are suited for dynamic settings.

Single vs. Multi-Gas Detectors

Multi-gas detectors are efficient and cost-effective for industries where several gases are a concern. Single-gas detectors, meanwhile, are ideal for settings where one primary gas is the main risk.

In my experience, portable gas detectors are ideal for confined spaces and are versatile in various environments.

For stationary areas, however, fixed solutions provide continuous coverage, which can be essential in high-risk zones.

Consider Environmental Conditions

Environmental factors significantly influence gas detector performance. For example:

Adapt to Temperature and Climate

In high- or low-temperature environments, standard gas detectors may underperform. Select a detector with appropriate specifications for extreme conditions—like mining or offshore rigs—where durability is essential.

Specialized Detectors for Specific Conditions

Some environments, such as humid or dusty locations, may require detectors with moisture-proofing or particulate filters.

Each environment requires specific detectors; extreme cold or high heat can impact performance. In mining, for instance, rugged, temperature-resistant models are necessary.”

Check for Necessary Certifications

Compliance with regional standards is vital for safety and legal reasons:

Regional Certification Standards

Different countries have distinct certification requirements. For instance, Brazil uses the InMetro certification, while the U.S., Canada, and Mexico rely on UL or CSA certifications. Europe adheres to ATEX or IECEx standards.

Importance of Compliance

Meeting local standards is essential to avoid potential penalties and to ensure that the equipment is reliable. Uncertified equipment may not perform optimally, especially under challenging conditions.

In my experience, certifications vary widely. For example, projects in the U.S. need UL or CSA certification, while European projects often require ATEX or IECEx compliance.”

Evaluate Integration Capabilities

Integration is crucial, particularly if the detector will connect to a broader safety system:

Compatibility with Existing Systems

For fixed systems, check if the detector is compatible with protocols like Modbus, HART, or BACnet, especially if connecting to building automation systems. This makes monitoring seamless and efficient.

Software and Data Management for Portable Detectors

Many portable detectors come with software for data collection and analysis. Look for models that offer free software, which can reduce costs and simplify monitoring.

Integration options can make a huge difference. If you’re adding a fixed system to a building automation network, compatibility with protocols like Modbus or BACnet is key. Portable detectors also benefit from having free software for easier data access.”

Assess the Support and Maintenance Requirements

Regular maintenance ensures that gas detectors remain accurate and reliable over time:

Routine Calibration and Testing

Regular calibration is necessary to maintain detector accuracy. Ensure that the manufacturer provides calibration support or has local service options.

Ease of Use and Training Needs

Some gas detection systems may require specialized training. Choose equipment that matches your team’s skills, and provide additional training if necessary to ensure proper operation.

Additional Considerations for Choosing a Gas Detection Solution

Finally, a few extra factors can help maximize value and usability:

Budget vs. Long-Term Value

While cost is always a factor, investing in high-quality detectors often saves money over time by reducing maintenance needs and increasing reliability.

Availability of Spare Parts and Replacement Options

Ensure that you can easily obtain replacement parts or additional units if needed. Quick access to parts minimizes downtime and keeps safety measures in place.

Key Takeaways: How to Select the Right Gas Detection Solution

Selecting the right gas detection solution requires a blend of industry-specific insight, regional compliance knowledge, and practical considerations based on site requirements.

With careful attention to these factors, you’ll be well-prepared to choose a system that enhances safety, supports regulatory compliance, and meets the unique demands of your environment.