Adaptive biologically-inspired algorithm-based controller tuning for input tracking control of flexible manipulators

This paper discusses current work on the input tracking control of single-link flexible manipulator systems. Joint-based control (JBC) is tuned using bacterial foraging algorithm (BFA). The objective of the work is to investigate the performance of the BFA with adaptable chemotactic step size in the control of a flexible manipulator in comparison to the original BFA. Lagrange equation discretised by finite difference (FD) approach is used to represent the dynamics of the flexible manipulator, incorporating payload with flexible mode associated damping and hub inertia. The FD method is chosen because it can represent flexible manipulator dynamics adequately well. The impact of two different cost functions is examined and discussed. The controller performance is evaluated based on the hub-angle output in time-domain.