Control of a single-link flexible manipulator using improved bacterial foraging algorithm

Abstract

This paper presents an investigation into application of controller tuning using improved bacterial foraging algorithm (BFA) namely exponentially adaptive BFA (EABFA). The objective of the work is to evaluate the performance of EABFA in the controller tuning of a joint-based collocated (JBC) proportional-derivative (PD) control system. A simulation model of a single-link flexible manipulator system that incorporates hub inertia, structural damping and payload at the end-point of flexible arm is used as a test bed. JBC tuned by BFA is used to control the hub angular movement. An adaptable chemotactic step size mechanism that incorporates exponential function of the nutrient value is introduced to improve the original BFA. The developed EABFA has faster convergence with better or comparable optimum results than that of the original BFA. The performance of EABFA is assessed based on its convergence, optimum nutrient value and time-domain hub-angular response of the manipulator system.