A multiple-model MRAC scheme for multivariable systems with matching uncertainties

This paper develops a multivariable multiple-model adaptive control scheme for adaptive state feedback state tracking control of systems whose plant-model matching conditions are uncertain and parameters are unknown. To deal with the uncertainty of plant-model matching conditions needed for adaptive control, multiple reference model systems are employed to generate multiple parameter estimation and feedback control signals from which a most suitable control input is selected by a control switching mechanism designed using multiple estimation errors. Such a new multiple-model control design is based on an expanded control system parametrization which has the capacity to cover system structural uncertainties. Stability analysis and simulation results ensure and verify the desired adaptive control system stability and tracking performance.

[1]  Nhan T. Nguyen,et al.  Multiple-Model Adaptive Fault-Tolerant Control of a Planetary Lander , 2009 .

[2]  Tianyou Chai,et al.  A Nonlinear Control Method Based on ANFIS and Multiple Models for a Class of SISO Nonlinear Systems and Its Application , 2011, IEEE Transactions on Neural Networks.

[3]  Shaoyuan Li,et al.  Multiple model predictive control for large envelope flight of hypersonic vehicle systems , 2016, Inf. Sci..

[4]  Michael G. Safonov,et al.  Safe Adaptive Switching Control: Stability and Convergence , 2008, IEEE Transactions on Automatic Control.

[5]  Seungwoo Kim,et al.  Takagi-Sugeno fuzzy model based indirect adaptive fuzzy observer and controller design , 2010, Inf. Sci..

[6]  Austin M. Murch.  A Flight Control System Architecture for the NASA AirSTAR Flight Test Infrastructure , 2008 .

[7]  Kumpati S. Narendra,et al.  Adaptive control using multiple models , 1997, IEEE Trans. Autom. Control..

[8]  Giorgio Battistelli,et al.  Multi-model unfalsified adaptive switching supervisory control , 2010, Autom..

[9]  Kumpati S. Narendra,et al.  New Concepts in Adaptive Control Using Multiple Models , 2012, IEEE Transactions on Automatic Control.

[10]  Wei Wang,et al.  Adaptive backstepping control of uncertain systems with unknown input time-delay , 2009, Autom..

[11]  Ruiyun Qi,et al.  An adaptive control scheme using multiple reference models , 2014 .

[12]  Yan Shi,et al.  Adaptive output-feedback neural tracking control for a class of nonstrict-feedback nonlinear systems , 2016, Inf. Sci..

[13]  Brian D. O. Anderson,et al.  A Combined Multiple Model Adaptive Control Scheme and Its Application to Nonlinear Systems With Nonlinear Parameterization , 2012, IEEE Transactions on Automatic Control.

[14]  Delphine Bresch-Pietri,et al.  Adaptive trajectory tracking despite unknown input delay and plant parameters , 2009, Autom..

[15]  Anuradha M. Annaswamy,et al.  Composite adaptive posicast control for a class of LTI plants with known delay , 2013, Autom..

[16]  Thomas S. Brinsmead,et al.  Multiple model adaptive control. Part 2: switching , 2001 .

[17]  Peter Xiaoping Liu,et al.  Robust adaptive fuzzy fault-tolerant control for a class of non-lower-triangular nonlinear systems with actuator failures , 2016, Inf. Sci..

[18]  Shuzhi Sam Ge,et al.  Adaptive output-feedback control for a class of uncertain stochastic non-linear systems with time delays , 2008, Int. J. Control.

[19]  Anuradha M. Annaswamy,et al.  Parameter convergence in nonlinearly parameterized systems , 2003, IEEE Trans. Autom. Control..

[20]  Gang Tao,et al.  Adaptive Control Design and Analysis , 2003 .

[21]  Wei Wang,et al.  Adaptive actuator failure compensation control of uncertain nonlinear systems with guaranteed transient performance , 2010, Autom..

[22]  Alireza Fatehi,et al.  Improved switching for multiple model adaptive controller in noisy environment , 2012 .

[23]  Zhengtao Ding,et al.  Sampled-data adaptive control of a class of nonlinear systems , 2011 .