Genetic Simulated Annealing Algorithm Used for PID Parameters Optimization

Abstract

A type of genetic simulated annealing algorithms (GSAAs) is presented, which is used to optimize the parameters of proportional-integral-derivative (PID) controllers. This approach combines the merits of genetic algorithms (GAs) and simulated annealing algorithms (SAAs). By integrating the global search ability of GA with the local search ability of SAA, the search ability of GSAA is much stronger than GA's and SAA's search ability. So, GSAA could find the global optimal solution of the given problem. Furthermore, the adaptive probability for crossover operator and nonuniform mutation operator is used in the GSAA, which can eliminate the phenomena of premature converge. Computer simulation on the speed control system of a kind of mobile robots is relized by Matlab. The results of computer simulation demonstrate that, comparing with the GA and SAA, the response speed of the PID controller can be improved due to the parameters produced from GSAA.