A Modified CMAC Algorithm Based on Credit Assignment
Neural Processing Letters
Stock Prediction Using FCMAC-BYY
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
An online Bayesian Ying-Yang learning applied to fuzzy CMAC
Neurocomputing
Study of Cooperation Strategy of Robot Based on Parallel Q-Learning Algorithm
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part I
FPGA-based real-time implementation of an adaptive RCMAC control system
WSEAS Transactions on Circuits and Systems
Adaptive CMAC neural control of chaotic systems with a PI-type learning algorithm
Expert Systems with Applications: An International Journal
CMAC-Based PID Control of an XY Parallel Micropositioning Stage
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Self-organizing CMAC control for a class of MIMO uncertain nonlinear systems
IEEE Transactions on Neural Networks
CMAC-based compensator for limiting bound required in supervisory control systems
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
CMAC neural networks structures
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Direct inverse model control based on a new improved CMAC neural network
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Grey adaptive growing CMAC network
Applied Soft Computing
Fuzzy CMAC with online learning ability and its application
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
A balanced learning CMAC neural networks model and its application to identification
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
The improved CMAC model and learning result analysis
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Journal of Intelligent and Robotic Systems
Gait Pattern Based on CMAC Neural Network for Robotic Applications
Neural Processing Letters
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In this paper, a novel learning scheme is proposed to speed up the learning process in cerebellar model articulation controllers (CMAC). In the conventional CMAC learning scheme, the correct numbers of errors are equally distributed into all addressed hypercubes, regardless of the credibility of the hypercubes. The proposed learning approach uses the inverse of learned times of the addressed hypercubes as the credibility (confidence) of the learned values, resulting in learning speed becoming very fast. To further demonstrate online learning capability of the proposed credit assigned CMAC learning scheme, this paper also presents a learning robust controller that can actually learn online. Based on robust controllers presented in the literature, the proposed online learning robust controller uses previous control input, current output acceleration, and current desired output as the state to define the nominal effective moment of the system from the CMAC table. An initial trial mechanism for the early learning stage is also proposed. With our proposed credit-assigned CMAC, the robust learning controller can accurately trace various trajectories online.