Genetic algorithm and simulated annealing for optimal robot arm PID control

This paper describes the use of genetic algorithm (GA) and simulated annealing (SA) for optimizing the parameters of PID controllers for a 6-DOF robot arm. A GA and a SA are designed to optimal-tune the parameters of the PID controller of each joint for a single step response and for the tracking of other specified trajectories. The GA and the SA are required to optimize evaluation functions related to the combinations of different performance indices. Simulations are carried out on a PUMA 560 arm model being controlled by PID controllers with their parameters optimized using the proposed GA and SA. Based on the simulation results, the performances of genetic algorithm and simulated annealing are compared and discussed