Direct Mnn Control of Continuous Stirred Tank Reactor Based on Input-Output Model

Shiuzhi S. Ge; Jin Zhang; Tongheng H. Lee

doi:10.11499/sicep.2002.0.609.0

SICE Annual Conference 2002

DOI https://doi.org/10.11499/sicep.2002.0.609.0

会議情報

主催: The Society of Instrument and Control Engineers

共催: IEEE/Industiral Electronic Society, IEEE/Robotics and Automation Society, IEEE/Control System Society

Direct Mnn Control of Continuous Stirred Tank Reactor Based on Input-Output Model

Shiuzhi S. Ge, Jin Zhang, Tongheng H. Lee

著者情報

キーワード: non-affine nonlinear system, implicit function theorem, multi-layer neural networks, projection algorithms, CSTR system

会議録・要旨集フリー

p. 609

詳細

抄録

In this paper, a direct multi-layer neural network control scheme is investigated for a class of continuous stirred tank reactors (CSTR). The CSTR plant under study is discretized to an input-output based τ-step ahead discrete-time model. By implicit function theorem, the existence of the implicit desired feedback control (IDFC) is proved. Multi-layer neural networks are used as the emulator of the desired feedback control. Projection algorithms are used to guarantee the boundness of the multi-layer neural network weights. Simulation results show the effectiveness of the proposed controller.

責任著者(Corresponding author)

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