Quantitative Feedback Theory control design using particle swarm optimization method

• Published in: Transactions of the Institute of Measurement and Control Vol. 34; no. 4; pp. 463 - 476
• Main Authors: Ali, Hazem I, Noor, Samsul Bahari B Mohd, Bashi, SM, Marhaban, Mohammad Hamiruce
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.06.2012; Sage Publications Ltd
• Subjects: Actuators; Algorithms; Design engineering; Feedback control systems; Optimization; Optimization algorithms; Optimization techniques; Pneumatics; Quantitative feedback theory; Robust control; Robustness; pneumatic actuator; robust control; PSO; Loop shaping; QFT
• ISSN: 0142-3312; 1477-0369
• DOI: 10.1177/0142331210397084

In this paper, a particle swarm optimization (PSO) method is proposed to design Quantitative Feedback Theory (QFT) control. This method minimizes a proposed cost function subject to appropriate robust stability and performance QFT constraints. The PSO algorithm is simple and easy to implement, and can be used to automate the loop shaping procedures of the standard QFT. The proposed method is applied to the high uncertainty pneumatic servo actuator system as an example to illustrate the design procedure of the proposed algorithm. The proposed method is compared with the standard QFT control. The results show that the superiority of the proposed method in that it can achieve the same robustness requirements of standard QFT control with simple structure and low order controller.