Optimization of the control parameters of a pneumatic servo cylinder drive using genetic algorithms

Abstract

Genetic algorithms are applied here to optimize the control gains of a three-loop controller for a pneumatic servo cylinder drive. The three-loop controller has position, velocity, and acceleration feedback gain, all of which have formerly been manually tuned. A general procedure for optimizing the control parameters of fluid power systems by using genetic algorithms is presented. It is shown that, by using minimum information specific to the system, near-optimal values of the control gains can be obtained within 10 generations. It is also shown that the numerical values of both the optimal velocity and the acceleration gain tend to increase as either the load mass or reference position increases, when the optimal position gain is fixed at a constant value. The optimized gains are confirmed by a plot of the fitness distribution defined in this study, which represents the control performance of the system in a given gain space. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.