Adaptive fuzzy modular backstepping output feedback control of uncertain nonlinear systems in the presence of input saturation

In this paper, we present a new scheme to design adaptive fuzzy output-feedback controller for uncertain nonlinear systems in the presence of input saturation. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a state filter is designed to estimate unmeasured states. Combining the backstepping recursive design with modular design techniques, a new adaptive fuzzy output control scheme is synthesized. Unlike some existing control schemes for systems with input saturation, the developed controller dose not require assumptions on the states available and nonlinear systems satisfying the matching condition. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin. A simulation is included to illustrate the effectiveness of the proposed approach.

[1]  Jacek M. Zurada,et al.  Adaptive neural network control of uncertain nonlinear systems with nonsmooth actuator nonlinearities , 2007, Neurocomputing.

[2]  Yadong Wang,et al.  A new approach to fuzzy rule generation: fuzzy extension matrix , 2001, Fuzzy Sets Syst..

[3]  Shaocheng Tong,et al.  Adaptive Fuzzy Output Tracking Control of MIMO Nonlinear Uncertain Systems , 2007, IEEE Transactions on Fuzzy Systems.

[4]  Abdesselem Boulkroune,et al.  Adaptive fuzzy controller for multivariable nonlinear state time-varying delay systems subject to input nonlinearities , 2011, Fuzzy Sets Syst..

[5]  Shaocheng Tong,et al.  A Novel Robust Adaptive-Fuzzy-Tracking Control for a Class of NonlinearMulti-Input/Multi-Output Systems , 2010, IEEE Transactions on Fuzzy Systems.

[6]  Gang Feng,et al.  Robust control for a class of uncertain nonlinear systems: adaptive fuzzy approach based on backstepping , 2005, Fuzzy Sets Syst..

[7]  Bing Chen,et al.  Direct adaptive fuzzy control for nonlinear systems with time-varying delays , 2010, Inf. Sci..

[8]  Herón Molina-Lozano,et al.  A new fast fuzzy Cocke–Younger–Kasami algorithm for DNA strings analysis , 2011, Int. J. Mach. Learn. Cybern..

[9]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control , 1994 .

[10]  Bor-Sen Chen,et al.  H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach , 1996, IEEE Trans. Fuzzy Syst..

[11]  Jing Wang,et al.  Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems , 2002, IEEE Trans. Neural Networks.

[12]  Mohammed M'Saad,et al.  Asymptotic stabilization of linear plants in presence of input and output saturations , 2001, Autom..

[13]  C.-S. Chiu.  Mixed Feedforward/Feedback Based Adaptive Fuzzy Control for a Class of MIMO Nonlinear Systems , 2006, IEEE Transactions on Fuzzy Systems.

[14]  Frédéric Grognard,et al.  Improving the performance of low-gain designs for bounded control of linear systems , 2002, Autom..

[15]  Jing Zhou,et al.  Robust Adaptive Control of Uncertain Nonlinear Systems in the Presence of Input Saturation and External Disturbance , 2011, IEEE Transactions on Automatic Control.

[16]  Shaocheng Tong,et al.  A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems , 2003, IEEE Trans. Fuzzy Syst..

[17]  Ping Lu,et al.  Tracking control of nonlinear systems with bounded controls and control rates , 1996, Autom..

[18]  Anuradha M. Annaswamy,et al.  Adaptive Control of a Class of Time-delay Systems in the Presence of Saturation , 2001 .

[19]  Hyun Min Do,et al.  An anti-windup design for single input adaptive control systems in strict feedback form , 2004, Proceedings of the 2004 American Control Conference.

[20]  Chen-Sheng Ting,et al.  A Robust Fuzzy Control Approach to Stabilization of Nonlinear Time-delay Systems with Saturating Inputs , 2008 .

[21]  Shaocheng Tong,et al.  Observer-based fuzzy adaptive control for strict-feedback nonlinear systems , 2009, Fuzzy Sets Syst..

[22]  Xizhao Wang,et al.  Training T-S norm neural networks to refine weights for fuzzy if-then rules , 2007, Neurocomputing.

[23]  Korris Fu-Lai Chung,et al.  Positive and negative fuzzy rule system, extreme learning machine and image classification , 2011, Int. J. Mach. Learn. Cybern..

[24]  Hartmut Logemann,et al.  Low-gain integral control of continuous-time linear systems subject to input and output nonlinearities , 2003, Autom..

[25]  Chun-Fei Hsu,et al.  Fuzzy-identification-based adaptive backstepping control using a self-organizing fuzzy system , 2009, Soft Comput..

[26]  Alexander Leonessa,et al.  Adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints , 2009 .

[27]  S. P. Kárason,et al.  Adaptive Control in the Presence of Input Constraints , 1993, American Control Conference.

[28]  Li-Juan Wang,et al.  An improved multiple fuzzy NNC system based on mutual information and fuzzy integral , 2011, Int. J. Mach. Learn. Cybern..

[29]  Prodromos Daoutidis,et al.  An Anti-Windup Design for Linear Systems with Input Saturation , 1998, Autom..

[30]  Shuzhi Sam Ge,et al.  Robust Adaptive Neural Network Control for a Class of Uncertain MIMO Nonlinear Systems With Input Nonlinearities , 2010, IEEE Transactions on Neural Networks.

[31]  Peter Hippe,et al.  Systematic closed-loop design in the presence of input saturations , 1999, Autom..

[32]  Tieshan Li,et al.  Decentralized adaptive neural control of nonlinear interconnected large-scale systems with unknown time delays and input saturation , 2011, Neurocomputing.

[33]  Changjiu Zhou,et al.  Adaptive fuzzy H/sub /spl infin// stabilization for strict-feedback canonical nonlinear systems via backstepping and small-gain approach , 2005, IEEE Transactions on Fuzzy Systems.

[34]  Miroslav Krstic,et al.  Nonlinear and adaptive control de-sign , 1995 .