Online Control of Nonlinear Systems using Neuro-Fuzzy Design tuned with Cooperative Particle Sub-Swarms Optimization

نویسندگان

  • Sana Bouzaida
  • Anis Sakly
چکیده

This paper proposes a TSK-type Neuro-Fuzzy system tuned with a novel learning algorithm. The proposed algorithm used an improved version of the standard Particle Swarm Optimization algorithm, it employs several sub-swarms to explore the search space more efficiently. Each particle in a sub-swarm correct her position based on the best other positions, and the useful information is exchanged among the particles during the iteration process. Simulations on Neuro-fuzzy control of two non-linear plants are conduct to verify algorithm performance and indicate that the proposed algorithm outperforms the standard Particle Swarm Optimization algorithm. Keywords— Particle Swarm Optimization; Neuro-Fuzzy design; Cooperative Sub-Swarms; Online Control; Nonlinear Systems

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تاریخ انتشار 2013