Tuning the Parameters of TSK Neuro-Fuzzy System by Particle Swarm Optimization

Abdulaziz, Sally; Nabil, Essam; Zaki, Gomaa; Atlam, Galal

doi:10.21608/mjeer.2019.62781

Tuning the Parameters of TSK Neuro-Fuzzy System by Particle Swarm Optimization

Document Type : Original Article

Authors

Dept. of Industrial Elect. and Control Eng., Faculty of Elect., Eng., Menoufia University, Egypt.

10.21608/mjeer.2019.62781

Abstract

Particle Swarm Optimization (PSO) algorithm is applied to improve the efficiency of Takagi-Sugeno-Kang (TSK) neuro-fuzzy network in identification of nonlinear system. First, a TSK type neuro-fuzzy system is adopted for improving identification and prediction, and then PSO technique is adopted to optimize the execution of neuro-fuzzy network. The simulation results indicate that the applied PSO accomplishes good performance and tracks the plant output with minimal error.

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