NDLI: Predictive control based on feedforward neural network for strong nonlinear system

Content Provider	IEEE Xplore Digital Library
Author	Min Han Wei Guo Jincheng Wang
Copyright Year	2005
Description	Author affiliation: Sch. of Electron. & Inf. Eng., Dalian Univ. of Technol., China (Min Han; Wei Guo; Jincheng Wang)
Abstract	The paper presents a generalized predictive control (GFC) algorithm based on feedforward neural network to control nonlinear system. In recent years, approximate linearization theory via feedback is used to control nonlinear system, but robustness can not be guaranteed. Considering neural network can accomplish nonlinear mapping from input to output, feedforward neural network is chosen as a nonlinear model of process. Based on such model, GPC is applied to control a second-order nonlinear system. To test the performance of system utilized such control algorithm, different experiments are made. Simulation results demonstrate that the performance of the system controlled by the proposed algorithm is good, and that system essentially responds in the desired manner. It is also demonstrated that the GPC based on neural network is provided with good adaptation and robustness.
Starting Page	2266
Ending Page	2271
File Size	1044541
Page Count	6
File Format	PDF
ISBN	0780390482
DOI	10.1109/IJCNN.2005.1556254
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-07-31
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive control Neural networks Feedforward neural networks Nonlinear systems Nonlinear control systems Control systems Prediction algorithms Linear approximation Neurofeedback Linear feedback control systems
Content Type	Text
Resource Type	Article

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