Some Applications of Soft Computing Methods in System Modeling and Control | Zendy

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Some Applications of Soft Computing Methods in System Modeling and Control

Author(s) -

Béla Lantos

Publication year - 1998

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.1998.p0082

Subject(s) - computer science , scara , soft computing , artificial neural network , pid controller , fuzzy control system , control engineering , neuro fuzzy , nonlinear system , fuzzy logic , control theory (sociology) , mimo , control system , intelligent control , genetic algorithm , control (management) , robot , artificial intelligence , machine learning , engineering , temperature control , computer network , channel (broadcasting) , physics , electrical engineering , quantum mechanics

The paper deals with the application of fuzzy systems, artificial neural networks (neural systems), and genetic algorithms to solve modeling and control problems in system engineering. Part 1 the paper covers the design of classical PID and fuzzy PID controllers for nonlinear systems with an (approximately) known dynamic model. Optimal controllers are designed based on genetic algorithms. Part 2 considers neural control of a SCARA robot. Part 3 deals with the fuzzy control of a special class of MIMO nonlinear systems and generalizes the method of Wang for such systems.

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