Hybrid fuzzy proportional-integral plus conventional derivative control of linear and nonlinear systems

This paper presents a new approach toward the optimal design of a hybrid proportional-integral-derivative (PID) controller applicable for controlling linear as well as nonlinear systems using genetic algorithms (GAs). The proposed hybrid PID controller is derived by replacing the conventional PI controller by a two-input normalized linear fuzzy logic controller (FLC) and executing the conventional D controller in an incremental form. The salient features of the proposed controller are as follows: (1) the linearly defined FLC can generate nonlinear output so that high nonlinearities of complex systems can be handled; (2) only one well-defined linear fuzzy control space is required for both linear and nonlinear systems; (3) optimal tuning of the controller gains is carried out by using a GA; and (4) it is simple and easy to implement. Simulation results on a temperature control system (linear system) and a missile model (nonlinear system) demonstrate the effectiveness and robustness of the proposed controller.