Optimal Guaranteed Cost Sliding Mode Control for Constrained-Input Nonlinear Systems With Matched and Unmatched Disturbances

IEEE Transactions on Neural Networks and Learning Systems
Huaguang ZhangYang Cui

Abstract

Based on integral sliding mode and approximate dynamic programming (ADP) theory, a novel optimal guaranteed cost sliding mode control is designed for constrained-input nonlinear systems with matched and unmatched disturbances. When the system moves on the sliding surface, the optimal guaranteed cost control problem of sliding mode dynamics is transformed into the optimal control problem of a reformulated auxiliary system with a modified cost function. The ADP algorithm based on single critic neural network (NN) is applied to obtain the approximate optimal control law for the auxiliary system. Lyapunov techniques are used to demonstrate the convergence of the NN weight errors. In addition, the derived approximate optimal control is verified to guarantee the sliding mode dynamics system to be stable in the sense of uniform ultimate boundedness. Some simulation results are presented to verify the feasibility of the proposed control scheme.

References

Jul 18, 2008·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Huaguang ZhangYanhong Luo
Jul 18, 2008·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Asma Al-TamimiMurad Abu-Khalaf
Jul 5, 2012·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Huaguang ZhangYanhong Luo
May 9, 2014·IEEE Transactions on Neural Networks and Learning Systems·Derong LiuHongliang Li
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Mar 21, 2015·IEEE Transactions on Neural Networks and Learning Systems·Biao LuoHan-Xiong Li
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Sep 5, 2015·IEEE Transactions on Neural Networks and Learning Systems·Qinmin YangYouxian Sun
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