PID tuning is the process of finding the values of proportional, integral, and derivative gains of a PID controller to achieve desired performance and meet design requirements.
PID controller tuning appears easy, but finding the set of gains that ensures the best performance of your control system is a complex task. Traditionally, PID controllers are tuned either manually or using rule-based methods. Manual tuning methods are iterative and time-consuming, and if used on hardware, they can cause damage. Rule-based methods also have serious limitations: they do not support certain types of plant models, such as unstable plants, high-order plants, or plants with little or no time delay.
You can automatically tune PID controllers using software tools to achieve the optimal system design and to meet design requirements, even for plant models that traditional rule-based methods cannot handle well.
An automated PID tuning workflow involves:
- Identifying plant model from input-output test data
- Modeling PID controllers (for example, in MATLAB using PID objects or in Simulink using PID Controller blocks)
- Automatically tuning PID controller gains and fine-tuning your design interactively
- Tuning multiple controllers in batch mode
- Tuning single-input single-output PID controllers as well as multiloop PID controller architectures