Weighted-Sum Extended Bat Algorithm Based PD Controller Design for Wheeled Mobile Robot

PID controller of WMR needs to be tuned as precise as possible in order to develop a good performance of WMR that is able to move from initial position to a desired position with the fast time response and minimum steady state error. Weighted-sum Extended Bat Algorithm (WS-EBA) is a multi-objective optimization method based on Extended Bat Algorithm. The weighted optimization approach is used to search the optimum value of Proportional-Integral-Derivative (PID) gains controller of Wheeled Mobile Robot (WMR) by referring to x and y position. Several experiments are conducted to test the effect of variables or parameters control to the value of PID gains and performance of WMR. Those parameters are the type of PID controller, number of agents in WS-EBA and the optimization functions used in the system to search the optimum value of PID gains. Results obtained from this research study indicates that PD controller, 30 number of searching agents and ITAE as the objective function gives the most suitable controller for WMR with result for X position is 11.00, 20.08 s and 0.00% for rise time, settling time and overshoot respectively. Additionally, for Y position, the results are 12.11, 22.08 s and 0.00% of rise time, settling time and overshoot respectively. The comparison of WS-EBA with Weighted-sum Particle Swarm Optimization (WS-PSO) and Weighted-sum Bat Algorithm (WS-BA) is also experimented in this research. WS-EBA outperformed the rest with the best result performance of WMR, consistency of solution, fastest convergence rate and the most balance of exploration and exploitation phase.