An improved BFO algorithm for optimising the PID parameters of servo system

In view of the disadvantages of slow convergence speed and low convergence precision in bacterial foraging optimization (BFO) algorithm, an improved bacterial foraging optimization (IBFO) algorithm is presented in this paper. The application of a nonlinear and adaptive step size balances the global searching capability and the local searching ability. To better reflect the ability of bacteria to foraging, the reproduction operation is completed by using the fitness value of the current bacterial location, and the variation operation is introduced to increase the diversity of the population. A piecewise elimination-dispersal probability is adopted to improve the precision and accuracy. Several classical test functions verify the significance of the IBFO algorithm. After that, the IBFO algorithm is applied to optimize PID parameters of a typical servo system. Simulation results show that, comparing with other techniques, the proposed IBFO algorithm can more effectively improve the convergence property and stability of the servo system.