A design of CMAC-based fuzzy logic controller with fast learning and accurate approximation

Fuzzy Sets and Systems

Volumn 125, Issue 1, 2002, Pages 93-104

  Kim, D ^a  

^a Pohang University of Science and Technology (POSTECH)   (South Korea)

Author keywords

Backpropagation learning; Cerebellar model articulation controller; Fuzzy logic controller; Truck backer upper control

Indexed keywords

APPROXIMATION THEORY; COMPUTER SIMULATION; FUZZY SETS; LEARNING SYSTEMS; MATHEMATICAL MODELS; NEURAL NETWORKS;

FUZZY LOGIC CONTROLLERS (FLC);

FUZZY CONTROL;

EID: 0036131826     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-0114(00)00102-0     Document Type: Article

References (15)

1. A new approach to manipulator control: The cerebellar model articulation controller (CMAC)
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3. Neural-network-based fuzzy logic control and decision system
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5. CMAC: An associative neural network alternative to backpropagation
6. Fast learning in multi-resolution hierarchies
7. ANFIS: Adaptive-network-based fuzzy inference system
8. A fuzzy cerebellar model articulation controller
9. A fuzzy CMAC model for color reproduction
10. Improving the fuzzy system performance by fuzzy system ensemble
11. A design and analysis of objective function-based unsupervised neural networks for fuzzy clustering
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13. Generating fuzzy rules from numerical data, with applications
14. Generating fuzzy rules by learning from examples
15. Learning convergence in the cerebellar model articulation controller