基于神经网络的非线性学习控制研究
Learning Control of Nonlinear Systems Based on Neural Networks
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Abstract: A back-propagation neural network is applied to learning control of nonlinear control systems. By training the neural networks using back-propagation algorithm, optimal state feedback control of nonlinear systems can be realized. This paper presents a novel learning control mechanism for a class of nonlinear systems, which does not depend the model of nonlinear control system. Simulation results show that the new scheme is efficient for large unknown nonlinearity.
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Key words:
- Neural network /
- back-propagation /
- nonlinear control /
- learning control
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