Direct fuzzy adaptive control based on sliding surface for a class of SISO non-linear systems

In this work we are interested in direct fuzzy adaptive control. The continuous SISO non-linear system is presented by the Takgi-Sugeno type fuzzy state model. The strategy of reference model direct adaptive control theory is presented then the adaptive fuzzy adjustment algorithm is presented. The control law includes two terms. The first is responsible to stabilise the plant is computed based on PDC method. The second constitutes the feed forward gain. All the parameters of the controller are adjusted online. The adjustment algorithm of the controller parameters exploits the sliding surface to profit of robustness of sliding mode control. The stability analysis of the closed-loop system has been proven using the Lyapunov approach. The single synchronous generator coupled to the infinite-bus power system is used to check the performances of the proposed control scheme.

[1]  M. Chtourou,et al.  Indirect Adaptive Fuzzy Control Scheme Based on Lyapunov Approach for a Class of SISO Nonlinear Systems , 2006 .

[2]  Hua Meng,et al.  Application of the fuzzy neural network with inverse identification structure on neutralisation process , 2010, Int. J. Model. Identif. Control..

[3]  Khaled A. El-Metwally.  A variable structure adaptive fuzzy logic stabiliser for a two-area load frequency control problem , 2010, Int. J. Model. Identif. Control..

[4]  Yansheng Yang.  Direct robust adaptive fuzzy control (DRAFC) for uncertain nonlinear systems using small gain theorem , 2005, Fuzzy Sets Syst..

[5]  Mohamed Chtourou,et al.  An indirect adaptive fuzzy sliding mode controller for a class of SISO non-linear systems , 2008, Int. J. Model. Identif. Control..

[6]  Igor Skrjanc,et al.  Globally stable direct fuzzy model reference adaptive control , 2003, Fuzzy Sets Syst..

[7]  Ahmad B. Rad,et al.  Indirect adaptive fuzzy sliding mode control: Part I: fuzzy switching , 2001, Fuzzy Sets Syst..

[8]  Young-Wan Cho,et al.  A Direct Adaptive Fuzzy Control of Nonlinear Systems with Application to Robot Manipulator Tracking Control , 2007 .

[9]  H. Chekireb,et al.  DIRECT ADAPTIVE FUZZY CONTROL OF NONLINEAR SYSTEM CLASS WITH APPLICATIONS , 2003 .

[10]  James J. Buckley,et al.  Universal fuzzy controllers , 1992, Autom..

[11]  Mohamed Chtourou,et al.  An indirect model reference robust fuzzy adaptive control for a class of SISO nonlinear systems , 2009 .

[12]  Kazuo Tanaka,et al.  An approach to fuzzy control of nonlinear systems: stability and design issues , 1996, IEEE Trans. Fuzzy Syst..

[13]  David J. Hill,et al.  Transient stability enhancement and voltage regulation of power systems , 1993 .

[14]  Ning Li,et al.  Type-II T-S fuzzy modelling for SCR flue gas denitration , 2010, Int. J. Model. Identif. Control..

[15]  J. Buckley.  Sugeno type controllers are universal controllers , 1993 .

[16]  Ahmad B. Rad,et al.  Indirect adaptive fuzzy sliding mode control: Part II: parameter projection and supervisory control , 2001, Fuzzy Sets Syst..

[17]  Shaocheng Tong,et al.  Fuzzy adaptive sliding-mode control for MIMO nonlinear systems , 2003, IEEE Trans. Fuzzy Syst..

[18]  Mignon Park,et al.  An indirect model reference adaptive fuzzy control for SISO Takagi-Sugeno model , 2001, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[19]  Tsung-Chih Lin,et al.  Observer-based indirect adaptive fuzzy-neural tracking control for nonlinear SISO systems using VSS and H[infin] approaches , 2004, Fuzzy Sets Syst..

[20]  Juan Luis Castro,et al.  Fuzzy logic controllers are universal approximators , 1995, IEEE Trans. Syst. Man Cybern..

[21]  P. Kundur,et al.  Power system stability and control , 1994 .

[22]  Igor Skrjanc,et al.  Model-Reference Fuzzy Adaptive Control as a Framework for Nonlinear System Control , 2003, J. Intell. Robotic Syst..