Abstract

The PSO (Particle Swarm Optimization) algorithm is applied to non-linear process, and is easy to be run into local optimum. The PSO algorithm is improved by T-S (Takagi-Sugeno)fuzzy model, although it solved the non-linear features of PSO algorithm, the PSO algorithm is still inability once in holding stop pattern. Thus, the membership function of the T-S fuzzy model extend the Gaussian function, the membership function is changed self-adaptively according to the actual situation. In the paper, based on extended T-S fuzzy model of self-adaptive disturbed PSO (ETSD-PSO) Algorithm is presented. The results of the simulation and comparative analysis show that ETSD-PSO algorithm in both performance and precision, or when the PSO algorithm hold stop pattern achieve very good results.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.