A genetically trained adaptive neuro-fuzzy inference system network utilized as a proportional-integral-derivative-like feedback controller for non-linear systems

Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering

Volumn 223, Issue 3, 2009, Pages 309-321

  Lutfy, O F ^a   Mohd Noor, S B ^a   Marhaban, M H ^a   Abbas, K A ^a  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

Author keywords

ANFIS; Classical PID controller; Genetic algorithms; Neuro fuzzy systems

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ANFIS; CLASSICAL PID CONTROLLER; CONTINUOUS STIRRED TANK REACTOR; FEEDBACK CONTROLLER; GA (GENETIC ALGORITHM); HYBRID LEARNING METHODS; INPUT AND OUTPUTS; LEARNING METHODS; NEURO-FUZZY SYSTEMS; NON-LINEAR; OUTPUT DISTURBANCE; PID CONTROLLERS; PROPORTIONAL INTEGRAL DERIVATIVES; REAL-CODING; SCALING FACTORS;

CONTROLLERS; EDUCATION; ELECTRIC CONTROL EQUIPMENT; ENGINEERING EXHIBITIONS; FEEDBACK; FEEDBACK CONTROL; FUZZY INFERENCE; FUZZY SYSTEMS; GENETIC ALGORITHMS; LEARNING ALGORITHMS; LINEAR SYSTEMS; MEMBERSHIP FUNCTIONS; NONLINEAR CONTROL SYSTEMS; PROPORTIONAL CONTROL SYSTEMS; THREE TERM CONTROL SYSTEMS; TWO TERM CONTROL SYSTEMS;

ADAPTIVE CONTROL SYSTEMS;

EID: 66549095449     PISSN: 09596518     EISSN: None     Source Type: Journal    
DOI: 10.1243/09596518JSCE683     Document Type: Article

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