Application of Constrained Quadratic Adaptive Bacterial Foraging Optimisation Algorithm on a Single Link Inverted Pendulum

Abstract

This paper presents optimising the control gains of a single link inverted pendulum on cart system using a constrained adaptive bacterial foraging optimisation strategy. The adaptive algorithm is based on the variable chemotactic step for each bacteria in the population to enhance the dispersal of the search and accelerate the convergence of the algorithm. This paper presented the development of simple constraints to bound the search domain within the feasible and stable range of control gains of the system. The system was modelled and simulated in Matlab Simulink software with the linked optimisation algorithm code to simulate the system over multiple iterations. Results showing a great enhancement of the system performance are illustrated and discussed.