Auto-Tuning of Optimum PID Controller Parameters Based on Quantum-Behaved Particle Swarm Optimization

PID controllers have been widely used for speed and position control of various applications.Quantum-behaved particle swarm optimization(QPSO) is proposed to search for the optimum parameters of PID controller.The model of a DC motor is used as a plan in this research.The conventional gain tuning of PID controller such as Ziegler-Nichols method usually produces a big overshoot,which is not preferable performance.Particle swarm optimization is a heuristic global optimization method,arising from the research of bird and fish flock movement behavior.Comparison between controllers tuned by QPSO and Z-N methods is carried out. Results demonstrate that designed PID controller using QPSO has less overshoot and smaller settling time.Furthermore,the QPSO-based PID controllers for different performance index have similar performances,except that is optimized by ITSE where long settling time is seen.