Low-cost optimal state feedback fuzzy control of nonlinear second-order servo systems

This paper discusses low-cost optimal Takagi-Sugeno state feedback fuzzy controllers for the position control of servo systems where the process is modeled by second-order linear dynamics with an integral component, and saturation and dead zone input static nonlinearity. The state feedback gain matrices in the rule consequents of the fuzzy controllers are obtained by the combination of the parallel distributed compensation and linear-quadratic regulator applied to each rule. An example concerning the position control of a DC servo system laboratory equipment is offered and experimental results are included.