Stability Enhancement of Plant Model by using Artificial Intelligence.

      Аннотация: This Book demonstrates the detail how to employ the modern methods to search efficiently the optimal PID controller parameters of a plant transfer function. In this project the values of kp, ki and kd are manipulated to maintain the stability of the system. PSO, BFO and ACO works on the basis of exploration and exploitation. Exploration covers large area where as exploitation covers the small area. Use of PSO, BFO and ACO methods tuned the PID parameter to make them more general and to achieve the steady state error lime, also to improve the dynamic behavior of the system. It is observed from MATLAB simulation result that ACO algorithm provides better performance and stability as compared to PSO and BFO. The proposed approach had superior features including easy implementation and good computation efficiency.

Ключевые слова: PSO, Particle, Swarm Optimization, ACO, Ant Colony, Optimization, BFO, bacterial foraging optimization