Performance Enhancement of Parameter Estimators via Dynamic Regressor Extension and Mixing*

A new procedure to design parameter estimators with enhanced performance is proposed in the technical note. For classical linear regression forms, it yields a new parameter estimator whose convergence is established without the usual requirement of regressor persistency of excitation. The technique is also applied to nonlinear regressions with “partially” monotonic parameter dependence—giving rise again to estimators with enhanced performance. Simulation results illustrate the advantages of the proposed procedure in both scenarios.

[1]  Alexander L. Fradkov,et al.  Design of impulsive adaptive observers for improvement of persistency of excitation , 2015 .

[2]  Ivan Tyukin,et al.  Adaptation and Parameter Estimation in Systems With Unstable Target Dynamics and Nonlinear Parametrization , 2005, IEEE Transactions on Automatic Control.

[3]  Girish Chowdhary,et al.  Concurrent learning for convergence in adaptive control without persistency of excitation , 2010, 49th IEEE Conference on Decision and Control (CDC).

[4]  Yih-Fang Huang,et al.  Asymptotically convergent modified recursive least-squares with data-dependent updating and forgetting factor , 1985, 1985 24th IEEE Conference on Decision and Control.

[5]  Haoyong Yu,et al.  Composite learning control with application to inverted pendulums , 2015, 2015 Chinese Automation Congress (CAC).

[6]  Sergey A. Kolyubin,et al.  Fast Compensation of Unknown Multiharmonic Disturbance for Nonlinear Plant with Input Delay , 2013, ALCOSP.

[7]  S. Sastry,et al.  Adaptive Control: Stability, Convergence and Robustness , 1989 .

[8]  Alessandro Astolfi,et al.  Nonlinear and adaptive control with applications , 2008 .

[9]  R. L. Mishkov,et al.  Exact parameter estimation without persistent excitation in nonlinear adaptive control systems , 2013 .

[10]  Romeo Ortega,et al.  On adaptive control of nonlinearly parameterized nonlinear systems: Towards a constructive procedure , 2011, Syst. Control. Lett..

[11]  Romeo Ortega,et al.  A robust nonlinear position observer for synchronous motors with relaxed excitation conditions , 2017, Int. J. Control.

[12]  Nathan van de Wouw,et al.  Convergent dynamics, a tribute to Boris Pavlovich Demidovich , 2004, Syst. Control. Lett..

[13]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[14]  Yu Tang,et al.  Adaptive control of robots with an improved transient performance , 2002, IEEE Trans. Autom. Control..

[15]  Romeo Ortega,et al.  Immersion and invariance adaptive control of nonlinearly parameterized nonlinear systems , 2009, 2009 American Control Conference.

[16]  Romeo Ortega,et al.  Flux and Position Observer of Permanent Magnet Synchronous Motors with Relaxed Persistency of Excitation Conditions , 2015 .

[17]  P. Lancaster,et al.  The theory of matrices : with applications , 1985 .

[18]  G. Goodwin,et al.  Adaptive computed torque control for rigid link manipulators , 1986, 1986 25th IEEE Conference on Decision and Control.