An Artificial Immune System Algorithm with Social Learning and Its Application in Industrial PID Controller Design. (31st January 2017)

• Record Type: Journal Article
• Authors: Wang, Mingan; Feng, Shuo; He, Chunhui; Li, Zhonghua; Xue, Yu
• Other Names: Lefik Marek Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2017(2017)
• Publication Date: 2017-01-31
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2017/3959474
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : A novel artificial immune system algorithm with social learning mechanisms (AIS-SL) is proposed in this paper. In AIS-SL, candidate antibodies are marked with an elitist swarm (ES) or a common swarm (CS). Correspondingly, these antibodies are named ES antibodies or CS antibodies. In the mutation operator, ES antibodies experience self-learning, while CS antibodies execute two different social learning mechanisms, that is, stochastic social learning (SSL) and heuristic social learning (HSL), to accelerate the convergence process. Moreover, a dynamic searching radius update strategy is designed to improve the solution accuracy. In the numerical simulations, five benchmark functions and a practical industrial application of proportional-integral-differential (PID) controller tuning is selected to evaluate the performance of the proposed AIS-SL. The simulation results indicate that AIS-SL has better solution accuracy and convergence speed than the canonical opt-aiNet, IA-AIS, and AAIS-2S.