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Abstract
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Article Information:
Adaptive Neural Network Output Feedback Tracking Control for a Class of Complicated Agricultural Mechanical Systems
Hui Hu, Peng Guo, Xilong Qu and Zhongxiao Hao
Corresponding Author: Hui Hu
Submitted: December 10, 2014
Accepted: January 23, 2015
Published: July 05, 2015 |
Abstract:
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The study presents an adaptive neural network output feedback tracking control scheme for a class of complicated agricultural mechanical systems. The scheme includes a dynamic gain observer to estimate the un-measurable states of the system. The main advantages of the authors scheme are that by introducing non-separation principle design neural network controller and the observer gain are simultaneously tuned according to output tracking error, the semi-globally ultimately bounded of output tracking error and all the states in the closed-loop system can be achieved by Lyapunov approach. With the universal approximation property of NN and the simultaneous parametrisation, no Lipschitz assumption and SPR condition are employed which makes the system construct simple. Finally the simulation results are presented to demonstrate the efficiency of the control scheme.
Key words: Agricultural mechanical systems, higher relative degree, neural network, non-separation principle, output feedback, ,
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Cite this Reference:
Hui Hu, Peng Guo, Xilong Qu and Zhongxiao Hao, . Adaptive Neural Network Output Feedback Tracking Control for a Class of Complicated Agricultural Mechanical Systems. Advance Journal of Food Science and Technology, (9): 622-629.
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ISSN (Online): 2042-4876
ISSN (Print): 2042-4868 |
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