Neural Network Adaptive Control for a Class of SISO Nonlinear Systems

Abstract:

An adaptive neural network control scheme is presented for a class of SISO affine nonlinear systems. Parameters in neural networks are updated using a gradient descent method. No robustifying control term is used in controller. The convergence of adaptive parameters and tracking error and the boundedness of all states in the corresponding closed-loop system are demonstrated by Lyapunov stability theorem. Simulation results demonstrate the effectiveness of the approach.

• Periodical: Advanced Materials Research (Volumes 211-212)
• Pages: 953-957
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.211-212.953
• Online since: February 2011
• Authors: Hui Hu, Peng Guo, Cheng Liu
• Keywords: Affine, Neural Network (NN), Nonlinear, SISO

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