An Artificial Immune System Algorithm with Social Learning and Its Application in Industrial PID Controller Design

Author:

Wang Mingan1,Feng Shuo2ORCID,He Chunhui3,Li Zhonghua3ORCID,Xue Yu4ORCID

Affiliation:

1. School of Information Science and Technology, Huizhou University, Huizhou 516007, China

2. School of Electronic Information and Electrical Engineering, Huizhou University, Huizhou 516007, China

3. School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China

4. School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing 210044, China

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.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

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