Adaptive Neural Network Output Feedback Control for Stochastic Nonlinear Systems With Unknown Dead-Zone and Unmodeled Dynamics
Top Cited Papers
- 4 September 2013
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Cybernetics
- Vol. 44 (6), 910-921
- https://doi.org/10.1109/tcyb.2013.2276043
Abstract
This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.Keywords
Funding Information
- National Natural Science Foundation of China (61074014, 61374113, 61203008)
- Program for Liaoning Innovative Research Team in University
This publication has 43 references indexed in Scilit:
- Adaptive neural dynamic surface control for servo systems with unknown dead-zoneControl Engineering Practice, 2011
- Model Following Controller Design for Large-Scale Systems With Time-Delay Interconnections and Multiple Dead-Zone InputsIEEE Transactions on Automatic Control, 2011
- Decentralized adaptive stabilization of interconnected nonlinear systems with unknown non-symmetric dead-zone inputsAutomatica, 2009
- Adaptive Neural Network Tracking Control of MIMO Nonlinear Systems With Unknown Dead Zones and Control DirectionsIEEE Transactions on Neural Networks, 2009
- Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback formAutomatica, 2008
- Decentralized adaptive control for large-scale time-delay systems with dead-zone inputAutomatica, 2008
- Robust adaptive control of a class of nonlinear systems with unknown dead-zoneAutomatica, 2004
- Model reference adaptive control of continuous-time systems with an unknown input dead-zoneIEE Proceedings - Control Theory and Applications, 2003
- An adaptive dead-zone inverse controller for systems with sandwiched dead-zonesInternational Journal of Control, 2003
- Convergence results for an adaptive dead zone inverseInternational Journal of Adaptive Control and Signal Processing, 1998