Tuning evolvable PID controllers through a clonal selection algorithm

This work discusses the use of an evolvable proportional-integral-derivative (PID) controller that consists of a PID controller hardware whose gains can be set, for example, by evolutionary computation techniques, such as genetic algorithms. Due to PID controllers´ widespread use in industry, tuning procedures for them are always a topic of interest. An evolutionary immune inspired algorithm, named clonal selection algorithm, is used for tuning the controller so that closed-loop step response specifications are satisfied. By using this procedure, designers need only specify the desired closed-loop response. Experiments with different processes indicate that the gains obtained through clonal selection algorithms may provide better responses than those obtained by the classical Ziegler-Nichols method. Moreover, the clonal algorithm is capable of generating adequate gains for systems where classical rules are not applicable.