PID controller design based on Prey-Predator Pigeon-Inspired Optimization algorithm

Pigeon-Inspired Optimization (PIO) algorithm is a recently proposed bio-inspired swarm intelligence optimizer. High convergence speed is its most outstanding advantage. However, PIO algorithm can easily trap into a local optimal solution, which is the main defect that limits its further application. To overcome this defect, a Prey-Predator PIO algorithm is proposed in this paper, which combines the standard Pigeon-Inspired Optimization algorithm and the Prey-Predator strategy. This new algorithm can avoid the disadvantage which standard Pigeon-Inspires optimization has. In this paper, comparative experiments on the Proportion-Integral-Derivative (PID) parameter adjustment are conducted by using Particle-Swarm Optimization (PSO), PIO and Prey-Predator PIO, and the comparative results demonstrate our proposed approach is more feasible and effective.