Optimization of PI and Fuzzy-PI Controllers on Simulation Model of Szabad(ka)-II Walking Robot

Abstract

The Szabad(ka)-II 18 DOF walking robot and its simulation model is suitable for research into hexapod walking algorithm and motion control. The complete dynamic model has already been built, and is used as a black box for walking optimization in this research. First, optimal straight line walking was chosen as our objective, since the robot mainly moves in this mode. This case can be tested and validated as well on the current version of our robot. An ellipse-based leg trajectory has been generated for this low-cost straight line walking. Currently a simple new Fuzzy-PI controller with three input variables is being constructed and compared with an previously used PI controller. The purpose of defining the rules and its optimization are to obtain a controller that provides walking with higher quality. Both the compared controllers have been optimized together with the parameters of the leg trajectory. The particle swarm optimization (PSO) method was chosen from several methods with our benchmark-based selection research and the help of specific test functions; moreover the previous research (the comparison of genetic algorithm (GA) and PSO) also led to this conclusion.