Finite-Horizon Near-Optimal Output Feedback Neural Network Control of Quantized Nonlinear Discrete-Time Systems With Input Constraint

IEEE Transactions on Neural Networks and Learning Systems
Hao XuSarangapani Jagannathan

Abstract

The output feedback-based near-optimal regulation of uncertain and quantized nonlinear discrete-time systems in affine form with control constraint over finite horizon is addressed in this paper. First, the effect of input constraint is handled using a nonquadratic cost functional. Next, a neural network (NN)-based Luenberger observer is proposed to reconstruct both the system states and the control coefficient matrix so that a separate identifier is not needed. Then, approximate dynamic programming-based actor-critic framework is utilized to approximate the time-varying solution of the Hamilton-Jacobi-Bellman using NNs with constant weights and time-dependent activation functions. A new error term is defined and incorporated in the NN update law so that the terminal constraint error is also minimized over time. Finally, a novel dynamic quantizer for the control inputs with adaptive step size is designed to eliminate the quantization error overtime, thus overcoming the drawback of the traditional uniform quantizer. The proposed scheme functions in a forward-in-time manner without offline training phase. Lyapunov analysis is used to investigate the stability. Simulation results are given to show the effectiveness and feasibility...Continue Reading

References

Dec 13, 2006·Network : Computation in Neural Systems·Peter Dayan, Angela J Yu
Dec 13, 2006·Network : Computation in Neural Systems·Simon M Stringer, Edmund T Rolls
Feb 14, 2008·IEEE Transactions on Neural Networks·Zheng Chen, Sarangapani Jagannathan
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Oct 17, 2012·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Derong Liu, Qinglai Wei
Jul 1, 2012·IEEE Transactions on Neural Networks and Learning Systems·Travis Dierks, Sarangapani Jagannathan
May 9, 2014·IEEE Transactions on Neural Networks and Learning Systems·Derong Liu, Qinglai Wei
Jan 1, 2013·IEEE Transactions on Neural Networks and Learning Systems·Ali Heydari, Sivasubramanya N Balakrishnan
Mar 1, 2013·IEEE Transactions on Neural Networks and Learning Systems·Hao Xu, Sarangapani Jagannathan
Sep 30, 2014·IEEE Transactions on Cybernetics·Qinglai WeiXiong Yang

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Citations

Mar 2, 2016·IEEE Transactions on Cybernetics· Xiangnan Zhong, Haibo He
Mar 14, 2017·IEEE Transactions on Neural Networks and Learning Systems·Behzad TalaeiJohn Singler

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