Intelligent control of time-varying dynamical systems using CMAC artificial neural network

In this paper, some successful case studies are presented on the intelligent control of time-varying linear/nonlinear dynamical systems using the Cerebellar Model Arithmetic Computer (CMAC) artificial neural network, and a recently developed unified linear system theory and a novel control technique...

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Bibliographic Details
Published inMathematical and computer modelling Vol. 21; no. 1; pp. 89 - 107
Main Authors Zhu, J.J., Xiao, W.-P.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 1995
Subjects
Self-tuning control
Simulation
System modeling
Trajectory tracking
System modeling
Trajectory tracking
Simulation
Self-tuning control
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ISSN0895-7177
1872-9479
DOI10.1016/0895-7177(94)00197-V

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Summary:In this paper, some successful case studies are presented on the intelligent control of time-varying linear/nonlinear dynamical systems using the Cerebellar Model Arithmetic Computer (CMAC) artificial neural network, and a recently developed unified linear system theory and a novel control technique called Extended-Mean Assignment Control (EMAC). Thanks to CMAC's simple and effective training algorithm and fast learning convergence, satisfactory and encouraging simulation results of angle-of-attack control of an aerobreak re-entry spacecraft and attitude control of an earth orbiting space vehicle subject to gravity gradient torque are obtained and presented in this paper. Suggestions for further investigations on the control of time-varying dynamical systems using CMAC and EMAC are proposed.
ISSN:0895-7177
1872-9479
DOI:10.1016/0895-7177(94)00197-V