Application of a general learning algorithm to the control of robotic manipulators
International Journal of Robotics Research
The interpolation capabilities of the binary CMAC
Neural Networks
Design of a single-input fuzzy logic controller and its properties
Fuzzy Sets and Systems
Design and stability analysis of single-input fuzzy logiccontroller
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Learning convergence in the cerebellar model articulation controller
IEEE Transactions on Neural Networks
Adaptive Growing Quantization for 1D CMAC Network
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
A New Cerebellar Model Articulation Controller for Rehabilitation Robots
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
Standalone CMAC control system with online learning ability
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
CMAC neural networks structures
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Intelligent backstepping control for wheeled inverted pendulum
Expert Systems with Applications: An International Journal
ART-type CMAC network classifier
Neurocomputing
Grey adaptive growing CMAC network
Applied Soft Computing
Two-Dimensional adaptive growing CMAC network
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Adaptive dynamic CMAC neural control of nonlinear chaotic systems with L2 tracking performance
Engineering Applications of Artificial Intelligence
Gait Pattern Based on CMAC Neural Network for Robotic Applications
Neural Processing Letters
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This paper attempts to propose a single-input cerebellar model articulation controller (CMAC) control system, which contains only one controller implemented by the CMAC. The single-input CMAC control system adopts two learning stages. An off-line learning stage is to enable the output behavior of the CMAC to approximate the control surface of a fuzzy PD-type controller. An on-line learning stage follows to improve the system stability by the modified learning rule. The linear interpolation scheme is also applied to the recall process at the on-line learning stage to ensure better accuracy of the CMAC output. Simulation results show that the single-input CMAC controller is superior to the fuzzy PD-type controller.