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Neural-based adaptive control design for general nonlinear systems and its application to process control

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3 Author(s)
Ge, S.S. ; Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore ; Hang, C.C. ; Zhang, T.

In this work, a neural-based adaptive controller is presented to solve the tracking control problem for a general class of unknown nonlinear systems. The proposed controller ensures that the output tracking error converges to a small neighborhood of the origin. The weight updating law of neural networks (NNs) is derived using Lyapunov theory and the stability of the closed-loop system is guaranteed. The proposed control scheme has been successfully applied to the composition control in a continuously stirred tank reactor (CSTR) in chemical processes

Published in:

American Control Conference, 1998. Proceedings of the 1998  (Volume:1 )

Date of Conference:

21-26 Jun 1998