Genetic-Algorithm-Based Fixed-Structure Robust H∞Loop-Shaping Control of a Pneumatic Servosystem

Abstract

The robust controller designed by conventional H∞optimal control is complicated, high-order, and difficult to implement practically. In industrial applications, structures such as lead-lag compensators and PID are widely used because their structure is simple, tuning parameters are fewer, and they are lower-order. Their disadvantages are that control parameters are difficult to tune for good performance and they lack robustness. To solve these problems, we propose an algorithma genetic-algorithm-based fixed-structure robust H∞loop-shaping controlfor designing the robust controller. Conventional H∞loop shaping is a sensible procedure for designing the robust controller. To obtain parameters in the proposed controller, we proposed a genetic algorithm to optimize specified-structure H∞loop shaping problem. The infinity norm of transfer function from disturbances to states is minimized via searching and evolutionary computation. The resulting optimal parameters stabilize the system and guarantee robust performance. We applied the evolutionary robust controller to a pneumatic servosystem. To compare performance, we studied three types of controller PID with a derivative first-order filter controller, a PI controller, and an H∞loop-shaping controller. Results of experiments demonstrate the advantages of a simple structure and robustness against parameters changing. Simulations verify the effectiveness of the proposed technique.