Improved quantum bacterial foraging algorithm for tuning parameters of fractional-order PID controller

Abstract

The quantum bacterial foraging optimization (QBFO) algorithm has the characteristics of strong robustness and global searching ability. In the classical QBFO algorithm, the rotation angle updated by the rotation gate is discrete and constant, which cannot affect the situation of the solution space and limit the diversity of bacterial population. In this paper, an improved QBFO (IQBFO) algorithm is proposed, which can adaptively make the quantum rotation angle continuously updated and enhance the global search ability. In the initialization process, the modified probability of the optimal rotation angle is introduced to avoid the existence of invariant solutions. The modified operator of probability amplitude is adopted to further increase the population diversity. The tests based on benchmark functions verify the effectiveness of the proposed algorithm. Moreover, compared with the integer-order PID controller, the fractional-order proportion integration differentiation (PID) controller increases the complexity of the system with better flexibility and robustness. Thus the fractional-order PID controller is applied to the servo system. The tuning results of PID parameters of the fractional-order servo system show that the proposed algorithm has a good performance in tuning the PID parameters of the fractional-order servo system.