Self-organizing rule-based control of multivariable nonlinear servomechanisms

Fuzzy Sets and Systems

Volumn 91, Issue 3, 1997, Pages 285-304

  Nie, Junhong ^a   Lee, T H ^b  

^a MCMASTER UNIVERSITY   (Canada)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Fuzzy reasoning; Learning; Rule based system; Self organizing; Servo control

Indexed keywords

COMPUTER SIMULATION; FUZZY SETS; INTERPOLATION; KNOWLEDGE BASED SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; NONLINEAR CONTROL SYSTEMS; ONLINE SYSTEMS; SERVOMECHANISMS; TWO TERM CONTROL SYSTEMS;

FEEDFORWARD CONTROL; FUZZY REASONING ALGORITHMS; SELF ORGANIZING COUNTERPROPAGATION NETWORK;

MULTIVARIABLE CONTROL SYSTEMS;

EID: 0031280994     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-0114(96)00149-2     Document Type: Article

References (2)

1. S. Arimoto, Learning control theory for robotic motion, Int. J. Adaptive Control Signal Process. 4 (1990) 543-564.
2. C.G. Atkeson and D.J. Reinkensmeyer, Using associative content-addressable memories to control robots, in: W.T. Miller, R.S. Sutton and P.J. Werbos, Eds., Neural Networks for Control (MIT Press, Cambridge, MA. 1990) 255-286.