CONTROL TECHNOLOGY Why PID control technology continues to thrive

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PID control originally became popular across many industries because of its versatility, simplicity, and effectiveness. It has maintained its popularity and even spread its influence as ongoing advances in both software and hardware steadily improve its capabilities.This article looks at PID technology and how it has advanced.

Proportional–integral–derivative controllers, also known as PID controllers or three-term controllers, have been with us for a long time; their first use was for ship steering control in 1922. From the mid-twentieth century, they became ubiquitous in industrial control applications.

However, continuous hardware and software advances have allowed the controllers to become ever smaller, lower-cost and more functional. This has facilitated their spread into many new applications, some of them perhaps unexpected – they are found in our mobile phones, electric vehicles, and electric ovens, for example.

So just how far have they evolved, and what do they look like now? After a brief recap of basic PID functionality, this article answers these questions by reviewing both the software and the hardware advances that have driven the PID evolution.

Basic PID control

Figure 1 shows a basic PID control loop. The adjustable set point is the target value for a plant variable such as temperature. A sensor on the plant continuously measures the actual temperature value, which is fed back and compared with the set point value. The error signal, which is the difference between these two values, drives the PID controller which uses its internal algorithm to generate the control signal for the plant temperature control system. The controller is working to eliminate the error signal, which happens when the feedback equals the setpoint – or, in other words, when the plant is running at the desired temperature value.

When the controller is in full PID (Proportional, Integral and Differential) mode, it implements a three-term PID algorithm as shown below:

Where

e(t) = SP(t) – PV(t)

SP(t) is the setpoint

PV(t) is the process variable being fed back

The K values are proportional, integral and differential gains. If a gain is set to zero, the whole term becomes zero. This way, the PID mechanism can be turned into a P controller, a PI controller, and other modifications¹.

The proportional term is the difference between the set point (SP) and the measured process variable (PV) – the error value, or e(t) - multiplied by the P gain (K_p).

The proportional gain (K_p) defines the speed of the control system response. If this is too large, the process variable starts to oscillate and can even oscillate out of control.

In certain systems, using only the P term cannot reduce the error value to zero. The remaining difference between the set point and process variable is called the steady-state error. In such cases, we need to add the integral term to the equation.

While the P term only considers the current error value, the integral term is proportional to the time integral of the error value. It means the I component considers the history of the error. The integral gain (K_i) increases the weight of this component in the actuating output.

If there is even a small error, the integral term will increase continuously (or decrease if the error is negative) until the steady state error equals zero.

The derivative term uses the difference between the current and previous error values divided by the time between measurements (dt).

The term is proportional to the rate of change of the process variable. While the P term fixes the current error and the I term considers previous errors, the derivative term works on future error values. The D component compensates for sharp fluctuations in the system, prevents it from strong overshoot, and decreases oscillations. The derivative gain (K_d) changes the weight of this component in the control signal.

The D term is important for systems such as quadcopters that face violent changes. However, it also amplifies measurement noise and external disturbances. It is often excluded when dealing with slow systems.

PID CONTROLLER

PID Controller - Definition and explanations

From steam engine control to your smartphone – how PID hardware has evolved

The earliest modern PID controllers – from the 1920s onwards – were built using mechanical or pneumatic components. Then the appearance of operational amplifiers in the mid Sixties allowed analog electronic PID designs – and these are still in widespread use today.

However, from the late Seventies, PID control could be implemented digitally. Manufacturers started using microcontrollers such as the Intel 8048; an innovation which significantly enhanced process control systems with more precise and reliable automation, more functionality, and compact designs. Online connectivity also becomes possible – an essential feature in today’s IoT environment.

Note that other PID controller implementations are also available. FPAAs (Field-programmable analog arrays)², FPGAs (Field-programmable gate arrays) and ASICs (Application-specific integrated circuits) can all be used, to yield advantages such as ease of programming, and set-up and modification of complex systems using building blocks.

Continuous-discrete conversion

To run a PID algorithm, which represents a continuous process, on a digital device such as a microprocessor, some type of continuous-discrete conversion method must be used. MathWorks offers several discretization and interpolation methods for converting dynamic system models between continuous time and discrete time and for resampling discrete-time models. Their ‘Continuous-Discrete Conversion Methods’ document provides a table of methods, along with advice on how to choose the best type for a given application.³

A practical microcontroller-based PID controller implementation

One readily-accessible approach to implementing a PID algorithm on a microcontroller is available through Arduino - an open-source electronics platform based on easy to use microcontroller hardware and software. Although Arduino was originally introduced as a simple development tool for students lacking an electronics or programming background, it has extended into a package used by professional designers to develop complex scientific instruments and other demanding applications.

The boards can read inputs such as light on a sensor, and generate outputs to control motors, turn on LEDs, and perform many other actions⁴.

Arduino can be coded using a language called Wiring, while the code is managed by the Arduino Software IDE (Integrated Development Environment). The IDE works with a Library Manager, which allows users to install libraries for any application. One example is ArduPID⁵, which supports PID functionality on an Arduino and claims greater accuracy that the legacy Arduino PID library.

The benefits arising from PID digitization

One immediate benefit is that once PID is transferred into a digital – and programmable – environment, functionality possibilities increase dramatically, with more compact and versatile hardware solutions. Integration with related functions is also possible.

For example, the Nano 33 BLE⁶, an Arduino microcontroller product, features a 9-axis inertial measurement unit and the possibility for Bluetooth Low Energy connectivity. With its small size and PID processing capability, it becomes a good solution for mobile phones and other wearable devices.

For automotive applications, STMicroelectronics’ 32-bit SPC5 microcontroller family can run PID and other control algorithms. These can be implemented by using the SPC5Studio IDE, which provides tools and libraries for developing applications on SPC5 microcontrollers. The IDE includes examples and templates to help users get started with their PID control implementation.

This means that the algorithm can run in a complete family of microcontrollers of various capabilities, all with automotive quality and capable of running safety critical applications⁷. They can also be paired with other chips for more functionality - for example with the ST L9963E Battery Management IC and its companion isolated transceiver L9963T to build a complete battery management system. This achieves high accuracy measurements of up to 14 cells in series, on mono or bi-directional daisy-chain configurations, embedding sophisticated cell monitoring and diagnostic features. It also meets the stringent Automotive Safety Integrity Level (ASIL) D⁸ regulations.

Although the PID algorithm remains popular as a fundamental process control tool, its ability to control a process accurately depends on how well it is tuned. Its viability also depends on the level of nonlinearity and other unpredictable factors in the system being controlled.