PID Control Loops Explained

Learning Objectives

By completing this learning module, learners will be able to:

• Understand the purpose of closed-loop control systems.

• Define Setpoint (SP), Process Variable (PV), Error, and Controller Output (CO).

• Explain the role of the Proportional, Integral, and Derivative terms in a PID controller.

• Recognise how PID control is applied within Building Management Systems (BMS).

• Identify common symptoms of poorly tuned control loops.

• Understand the basic principles of PID loop tuning.

• Apply PID concepts when commissioning and troubleshooting HVAC equipment.

Category: Controls Engineering
Sub-Category: Control Strategies & HVAC Automation
Estimated Reading Time: 12 Minutes
CPD Value: 0.25 Hours (Approximately)

Introduction

PID (Proportional-Integral-Derivative) control is one of the most widely used control strategies in Building Management Systems (BMS), industrial automation, and process control applications.

Whether controlling:

• Room temperature

• Supply air temperature

• Chilled water flow

• Duct static pressure

• Humidity

• Differential pressure

a PID loop continuously adjusts equipment output to maintain a desired operating condition.

A well-tuned PID loop can provide:

✅ Stable control

✅ Energy efficiency

✅ Reduced equipment wear

✅ Improved occupant comfort

A poorly tuned loop can cause:

❌ Hunting

❌ Oscillations

❌ Slow response

❌ Excessive valve and damper movement

What is a Control Loop?

A control loop is a system that automatically regulates a process by comparing a measured value against a desired target.

Basic Example

A room temperature controller operates as follows:

1. Desired temperature (Setpoint) = 22°C

2. Actual room temperature = 20°C

3. Error = 2°C

4. Controller calculates required correction.

5. Heating valve opens further.

6. Room temperature increases.

7. Temperature is measured again.

8. Process repeats continuously.

This is known as a closed-loop control system because feedback from the process influences future decisions.

Figure 1. Example of a closed-loop PID control sequence used within an Air Handling Unit (AHU).

Key PID Terminology

Setpoint (SP)

The desired target value.

Examples:

Process Variable (PV)

The actual measured condition.

Examples:

• Room sensor = 20°C

• Pressure sensor = 215 Pa

• Humidity sensor = 45% RH

Error

The difference between:

Error = Setpoint − Process Variable

Example:

Setpoint = 22°C

Actual Temperature = 20°C

Error = 2°C

The PID controller's job is to reduce this error to zero.

Controller Output (CO)

The signal generated by the PID controller.

Examples include:

• 0-10V control signal

• Digital valve position

• Fan speed demand

• VSD speed command

A larger error generally results in a larger output correction.

Understanding the Three PID Components

The output of a PID controller is made up of three independent calculations.

P = Proportional Control

The proportional term reacts to the current error.

The larger the error, the larger the corrective action.

Example

Setpoint = 22°C

Measured Temperature = 20°C

Error = 2°C

If the controller has a proportional gain of 20% per °C:

Output = 40%

If temperature drops further:

Error = 3°C

Output = 60%

Advantages

• Fast response

• Simple operation

• Easy to tune

Disadvantages

A proportional-only controller often leaves a small steady-state error.

For example:

• Setpoint = 22°C

• Room stabilises at 21.5°C

The small remaining error may never disappear.

This is known as offset.

I = Integral Control

The integral term addresses accumulated error over time.

It asks:

"How long has the error existed?"

If a small error remains for a prolonged period, the integral action gradually increases the output until the error is eliminated.

Example

Room remains:

• Setpoint = 22°C

• Actual = 21.5°C

Error = 0.5°C

Although the error is small, it persists.

The integral term slowly increases heating demand until the room eventually reaches 22°C.

Advantages

• Eliminates offset

• Improves accuracy

Potential Problems

Excessive integral action can cause:

• Overshoot

• Oscillation

• Hunting

This phenomenon is commonly called Integral Windup.

D = Derivative Control

The derivative term reacts to the rate of change of error.

It essentially asks:

"How quickly is the process changing?"

It predicts where the process is heading and applies corrective action before the error becomes significant.

Example

Room temperature rises rapidly:

• Current temperature = 21.5°C

• Setpoint = 22°C

A proportional controller may continue heating.

A derivative controller recognises the temperature is rising quickly and begins reducing output before overshoot occurs.

Advantages

• Reduces overshoot

• Improves stability

• Dampens oscillations

Potential Problems

Derivative control is sensitive to noisy sensors and unstable measurements.

For this reason, many HVAC applications use:

• PI Control

• P-only Control

rather than full PID control.

Visualising PID Behaviour

Imagine driving a car towards a speed limit of 60 mph:

Proportional

You press harder on the accelerator when far below 60 mph.

Integral

If you're stuck at 58 mph for a long time, you gradually press harder until you reach 60 mph.

Derivative

If you're approaching 60 mph rapidly, you ease off early to avoid exceeding the speed limit.

Together these actions produce stable and accurate speed control.

PID Control in Building Management Systems

PID loops are found throughout modern BMS installations.

Temperature Control

Used to control:

• Heating valves

• Cooling valves

• Fan coil units

• Air handling units

Example

Room Temperature → PID Controller → Heating Valve

The valve position continuously adjusts to maintain room comfort.

Static Pressure Control

Used for:

• Variable Air Volume (VAV) systems

• Supply fan speed control

Example

Pressure Sensor → PID Controller → Variable Speed Drive

The fan speed continuously adjusts to maintain design pressure.

Humidity Control

Used in:

• Clean rooms

• Healthcare facilities

• Laboratories

Maintains precise humidity conditions through humidifiers or dehumidification systems.

Chilled Water Systems

PID loops control:

• Valve positioning

• Pump speeds

• Chiller sequencing

to maintain efficient operation.

Common Control Loop Problems

Hunting

The process repeatedly swings around the setpoint.

Example:

22°C → 23°C → 21°C → 23°C → 21°C

Typical Causes

• Excessive gain

• Excessive integral action

• Slow sensors

Slow Response

The controller takes too long to reach the setpoint.

Causes

• Gain too low

• Excessive deadband

• Incorrect tuning

Overshoot

The process exceeds the target value before stabilising.

Example:

Setpoint = 22°C

Temperature rises to 24°C before settling.

Causes

• Gain too high

• Excessive integral action

Short Cycling

Equipment repeatedly starts and stops.

Causes

• Poor tuning

• Sensor placement issues

• Incorrect control strategy

Basic PID Tuning Concepts

PID tuning determines how aggressively the controller responds.

Increasing Proportional Gain

Results in:

• Faster response

• More aggressive control

Too much gain can create instability.

Increasing Integral Action

Results in:

• Reduced offset

• Greater accuracy

Too much integral action can cause oscillation.

Increasing Derivative Action

Results in:

• Better damping

• Reduced overshoot

Too much derivative action can amplify sensor noise.

Typical HVAC Strategy

Most HVAC control loops use:

PI Control

Proportional + Integral

This provides:

• Good accuracy

• Stable operation

• Simplified tuning

Without the complexity of derivative action.

Practical Commissioning Tips

When commissioning a PID loop:

Check Sensor Accuracy

An incorrectly calibrated sensor will make tuning impossible.

Verify Actuator Operation

Ensure:

• Valves stroke correctly

• Dampers move freely

• VSDs respond properly

Start Conservatively

Use lower gain values initially and increase gradually.

Trend Everything

Review trends for:

• Setpoint

• Process variable

• Controller output

Trend analysis is often the fastest method of diagnosing loop issues.

Understand Process Dynamics

A room temperature loop behaves differently from:

• Duct pressure

• Water temperature

• Humidity control

Each process requires different tuning characteristics.

Summary

PID control is the foundation of modern automated control systems and is essential knowledge for any BMS engineer, commissioning engineer, or controls technician.

A PID controller continuously compares a measured value against a desired setpoint and calculates a corrective output using three components:

• Proportional (P) responds to current error.

• Integral (I) responds to accumulated error.

• Derivative (D) responds to rate of change.

When correctly tuned, PID loops deliver accurate, stable, and energy-efficient control of HVAC and building systems. Understanding how these three elements work together enables engineers to diagnose control issues, improve system performance, and deliver optimum building comfort and efficiency.

Knowledge Check

1. What is the difference between a Setpoint and a Process Variable?

2. What causes control loop hunting?

3. Which PID component removes steady-state offset?

4. Why is derivative action often avoided in HVAC applications?

5. What information should be trended when diagnosing a PID loop?

6. What is the most common control strategy used in HVAC systems: P, PI, or PID?

Answers: 1) Desired value vs measured value, 2) Poor tuning/excessive gain or integral action, 3) Integral, 4) Sensitivity to measurement noise, 5) Setpoint, Process Variable and Output, 6) PI Control.



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