Adaptive tracking control of a class of nonlinear systems using CMAC network
DOI10.1016/0016-0032(96)00055-5zbMath0858.93032OpenAlexW2074410155MaRDI QIDQ2564846
Jer-Guang Hsieh, Teh-Lu Liao, Jui-Hong Horng
Publication date: 25 March 1997
Published in: Journal of the Franklin Institute (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0016-0032(96)00055-5
adaptive controlnonlinear systemsoutput trackingrobotic manipulatorsliding controlLyapunov approachstructured uncertaintycerebellar model articulation controller networkfeedforward compansation
Neural networks for/in biological studies, artificial life and related topics (92B20) Design techniques (robust design, computer-aided design, etc.) (93B51) Adaptive control/observation systems (93C40) Variable structure systems (93B12)
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Cites Work
- Nonlinear control systems: An introduction
- Neural networks for control systems - a survey
- Adaptive control of non-linear continuous-time systems using neural networks—general relative degree and MIMO cases
- Adaptive control of linearizable systems
- Globally stable robust tracking of nonlinear systems using variable structure control and with an application to a robotic manipulator
- A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)
- Direct adaptive output tracking control using multilayered neural networks
- Indirect techniques for adaptive input-output linearization of non-linear systems
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