Parametric modelling approach using bacterial foraging algorithms for modelling of flexible manipulator systems

This paper presents current work on biologically-inspired optimisation techniques based on bacterial foraging algorithms (BFAs) and their application to modelling of a single-link flexible manipulator. The objective of this work is to develop a single-link flexible manipulator model based on modified BFAs. First, three adaptation mechanisms of the chemotactic step size mechanism of BFA are proposed. New approaches of adaptable chemotactic step size are based on linear, quadratic and exponential functions of cost function value. Then, these three adaptive BFAs are used to develop three single-input single-output models to characterise a flexible manipulator from torque input to hub-angle, hub velocity and end-point acceleration responses. The performances of the adaptive BFAs are compared to that of standard BFA based on convergence to optimum value, the optimum value achieved and time-domain and frequency domain responses of the developed models.