Adaptive tracking control of a class of nonlinear systems using CMAC network

Jui Hong Horng, Jer Guang Hsieh, Teh-Lu Liao

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

In this paper, an adaptive control based on a Cerebellar Model Articulation Controller (CMAC) network is derived to solve the output tracking problem for a class of nonlinear systems with unknown structured nonlinearities. Without requiring a priori knowledge of the system parameter values, the proposed adaptive control consists of the conventional sliding control and a feedforward compensation with the CMAC network. The sliding control is used as a classical tracking controller for the nominal system and the CMAC network is used to compensate the parametrization errors. It is shown by the Lyapunov approach that the outputs of the closed-loop system asymptotically track the desired output trajectories. The effectiveness of the proposed control scheme is verified with an application to a two degree-of-freedom (DOF) robotic manipulator.

Original languageEnglish
Pages (from-to)861-878
Number of pages18
JournalJournal of the Franklin Institute
Volume333
Issue number6
DOIs
Publication statusPublished - 1996 Jan 1

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications
  • Applied Mathematics

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