Title :
OptiFel: A Convergent Heterogeneous Particle Swarm Optimization Algorithm for Takagi–Sugeno Fuzzy Modeling
Author :
Cheung, Ngaam J. ; Xue-Ming Ding ; Hong-Bin Shen
Author_Institution :
Inst. of Image Process. & Pattern Recognition, Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
Data-driven design of accurate and reliable Takagi-Sugeno (T-S) fuzzy systems has attracted a lot of attention, where the model structures and parameters are important and often solved in an optimization framework. The particle swarm optimization (PSO) algorithm is widely applied in the field. However, the classical PSO suffers from premature convergence, and it is trapped easily into local optima, which will significantly affect the model accuracy. To overcome these drawbacks, we have developed a new T-S fuzzy system parameters searching strategy called OptiFel with a heterogeneous multiswarm PSO (MsPSO) to enhance the searching performance. MsPSO groups the whole population into multiple cooperative subswarms, which perform different search behaviors for the potential solutions. We have found that the multiple subswarms strategy proposed in this paper is greatly helpful for finding the optimal parameters suitable for the subspaces of the T-S fuzzy model. Our theoretical proof has also demonstrated that the cooperation among the subswarms can maintain a balance between exploration and exploitation to ensure the particles converge to stable points. Experimental results show that MsPSO performs significantly better than traditional PSO algorithms on six benchmark functions. With the improved MsPSO, OptiFel can generate a good fuzzy system model with high accuracy and strong generalization ability.
Keywords :
control system synthesis; convergence; fuzzy systems; particle swarm optimisation; search problems; stability; MsPSO; OptiFel; PSO algorithm; T-S fuzzy system parameters searching strategy; TS fuzzy system; Takagi-Sugeno fuzzy modeling; convergent heterogeneous particle swarm optimization algorithm; data-driven design; fuzzy system model; generalization ability; heterogeneous multiswarm PSO; local optima; model structure; multiple cooperative subswarms; multiple subswarms strategy; optimal parameters; optimization framework; particle convergence; premature convergence; search behavior; searching performance enhancement; stable points; Computational modeling; Convergence; Fuzzy systems; Mathematical model; Optimization; Particle swarm optimization; Vectors; Convergence analysis; OptiFel; Takagi–Sugeno (T–S) fuzzy system; heterogeneous search; particle swarm optimization (PSO);
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2013.2278972