Output-Feedback Adaptive Neural Controller for Uncertain Pure-Feedback Nonlinear Systems Using a High-Order Sliding Mode Observer

A novel adaptive neural output-feedback controller for SISO nonaffine pure-feedback nonlinear systems is proposed. The majority of the previously described adaptive neural controllers for pure-feedback nonlinear systems were based on the dynamic surface control (DSC) or backstepping schemes. This makes the control law as well as the stability analysis highly lengthy and complicated. Moreover, there has been very limited research till date on the output-feedback neural controller for this class of the systems. The proposed controller evades adopting adaptive backstepping or DSC scheme through reformulating the original system into the Brunovsky form, which considerably simplifies the control law. Combining a high-order sliding mode observer and single radial-basis function network with universal approximation property, it is shown that the controller guarantees closed-loop system stability in the Lyapunov sense.

[1]  Yuequan Yang,et al.  Adaptive DSC of stochastic non-linear systems with input unmodelled dynamics , 2017 .

[2]  Shuzhi Sam Ge,et al.  Adaptive NN control of uncertain nonlinear pure-feedback systems , 2002, Autom..

[3]  Jang-Hyun Park,et al.  Adaptive Neural Control for Strict-Feedback Nonlinear Systems Without Backstepping , 2009, IEEE Transactions on Neural Networks.

[4]  Shaocheng Tong,et al.  Adaptive Controller Design-Based ABLF for a Class of Nonlinear Time-Varying State Constraint Systems , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[5]  Arie Levant,et al.  Higher-order sliding modes, differentiation and output-feedback control , 2003 .

[6]  Yan Lin,et al.  Adaptive dynamic surface control for pure‐feedback systems , 2012 .

[7]  A. Ferrara,et al.  Control of a Class of Mechanical Systems With Uncertainties Via a Constructive Adaptive/Second Order VSC Approach , 2000 .

[8]  Bing Chen,et al.  Observer-based adaptive neural control for a class of nonlinear pure-feedback systems , 2016, Neurocomputing.

[9]  Xiaocheng Shi,et al.  Adaptive neural tracking control of pure-feedback nonlinear systems , 2012, CCDC 2012.

[10]  Federico Thomas,et al.  Adaptive Neural Control of Nonlinear Systems , 2001, ICANN.

[11]  Anthony J. Calise,et al.  Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks , 2002, IEEE Trans. Neural Networks.

[12]  Chae-Joo Moon,et al.  Adaptive Fuzzy Controller for the Nonlinear System with Unknown Sign of the Input Gain , 2006 .

[13]  Hao Wang,et al.  Robust adaptive neural control of uncertain pure-feedback nonlinear systems , 2012, 2012 Third International Conference on Intelligent Control and Information Processing.

[14]  Dan Wang,et al.  Neural network‐based adaptive dynamic surface control of uncertain nonlinear pure‐feedback systems , 2011 .

[15]  Yang Yi,et al.  Adaptive Neural Dynamic Surface Control of Pure-Feedback Nonlinear Systems With Full State Constraints and Dynamic Uncertainties , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[16]  J. Park,et al.  Direct adaptive output-feedback fuzzy controller for a nonaffine nonlinear system , 2004 .

[17]  Huaguang Zhang,et al.  Adaptive Fault-Tolerant Tracking Control for MIMO Discrete-Time Systems via Reinforcement Learning Algorithm With Less Learning Parameters , 2017, IEEE Transactions on Automation Science and Engineering.

[18]  Jang-Hyun Park,et al.  Direct adaptive controller for nonaffine nonlinear systems using self-structuring neural networks , 2005, IEEE Transactions on Neural Networks.

[19]  Peng Shi,et al.  Novel Neural Control for a Class of Uncertain Pure-Feedback Systems , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[20]  Shuzhi Sam Ge,et al.  Direct adaptive NN control of a class of nonlinear systems , 2002, IEEE Trans. Neural Networks.

[21]  Jang-Hyun Park,et al.  Robust adaptive fuzzy controller for nonlinear system using estimation of bounds for approximation errors , 2003, Fuzzy Sets Syst..

[22]  Shaocheng Tong,et al.  Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints , 2017, IEEE Transactions on Cybernetics.

[23]  Jang-Hyun Park,et al.  Direct adaptive self-structuring fuzzy controller for nonaffine nonlinear system , 2005, Fuzzy Sets Syst..

[24]  Jing Na,et al.  Adaptive Control for Nonlinear Pure-Feedback Systems With High-Order Sliding Mode Observer , 2013, IEEE Transactions on Neural Networks and Learning Systems.

[25]  Shaocheng Tong,et al.  Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems , 2017, Autom..

[26]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[27]  Shuzhi Sam Ge,et al.  Adaptive Neural Control of MIMO Nonlinear Systems With a Block-Triangular Pure-Feedback Control Structure , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[28]  D. Mayne.  Nonlinear and Adaptive Control Design [Book Review] , 1996, IEEE Transactions on Automatic Control.

[29]  Jang-Hyun Park,et al.  Output-feedback control of uncertain nonlinear systems using a self-structuring adaptive fuzzy observer , 2005, Fuzzy Sets Syst..

[30]  Zhouhua Peng,et al.  Adaptive control based on single neural network approximation for non-linear pure-feedback systems , 2012 .

[31]  John D. Hunter,et al.  Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.

[32]  J. Park,et al.  Adaptive fuzzy observer with minimal dynamic order for uncertain nonlinear systems , 2003 .

[33]  Kok Kiong Tan,et al.  Further results on adaptive control for a class of nonlinear systems using neural networks , 2003, IEEE Trans. Neural Networks.

[34]  Gwi-Tae Park,et al.  Robust adaptive fuzzy controller for non‐affine nonlinear systems with dynamic rule activation , 2003 .

[35]  Hassan K. Khalil,et al.  High-gain observers in nonlinear feedback control , 2009, 2009 IEEE International Conference on Control and Automation.

[36]  Shaocheng Tong,et al.  Adaptive Fuzzy Output Feedback Dynamic Surface Control of Interconnected Nonlinear Pure-Feedback Systems , 2015, IEEE Transactions on Cybernetics.

[37]  Young-Hak Chang,et al.  Adaptive Neural Control of Nonlinear Pure-feedback Systems , 2010 .

[38]  Yang Yi,et al.  Adaptive neural dynamic surface control of strict-feedback nonlinear systems with full state constraints and unmodeled dynamics , 2017, Autom..

[39]  Pingjing Yao,et al.  Adaptive neural network control for a class of low-triangular-structured nonlinear systems , 2006, IEEE Transactions on Neural Networks.

[40]  Shaocheng Tong,et al.  Observer-Based Adaptive Fuzzy Backstepping Output Feedback Control of Uncertain MIMO Pure-Feedback Nonlinear Systems , 2012, IEEE Transactions on Fuzzy Systems.