Initial-Excitation-Based Robust Adaptive Observer for MIMO LTI Systems

This article addresses the problem of adaptive observer design for multi-input multioutput linear time-invariant plants, under the effects of bounded disturbances in the system dynamics and the output, without requiring the persistence of excitation (PE) condition for parameter convergence. A switched robust adaptive observer is proposed, based on initial excitation, a milder condition as compared to PE in terms of excitation requirement and online verifiability. The unknown initial condition of the state is strategically included as an additional unknown parameter in the estimation framework, which, as far as the authors are aware, is a first of its kind technique in the context of adaptive observer design. The extended estimation error dynamics ensures the global uniformly ultimately bounded stability of the estimation error dynamics. Furthermore, estimation errors in a disturbance-free case result in uniform global exponential stability in a delayed sense. Simulation results are presented, and the estimation performance of the proposed adaptive observer is compared with that of the existing algorithms to illustrate the effectiveness.

[1]  Anuradha M. Annaswamy,et al.  Fast Adaptive Observers for Battery Management Systems , 2020, IEEE Transactions on Control Systems Technology.

[2]  Anuradha M. Annaswamy,et al.  An Adaptive Observer Design for Real-Time Parameter Estimation in Lithium-Ion Batteries , 2020, IEEE Transactions on Control Systems Technology.

[3]  Anuradha M. Annaswamy,et al.  Fast Parameter Convergence in Adaptive Flight Control , 2020 .

[4]  Sayan Basu Roy,et al.  Initial Excitation Based Adaptive Observer With Multiple Switching , 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

[5]  Sumit Kumar Jha,et al.  Initial Excitation-Based Iterative Algorithm for Approximate Optimal Control of Completely Unknown LTI Systems , 2019, IEEE Transactions on Automatic Control.

[6]  Sayan Basu Roy,et al.  A Switched Adaptive Observer Design Without Persistence Of Excitation , 2019, 2019 Fifth Indian Control Conference (ICC).

[7]  Sumit Kumar Jha,et al.  Memory-Efficient Filter-Based Approximate Optimal Regulation of Unknown LTI Systems Using Initial Excitation , 2018, 2018 IEEE Conference on Decision and Control (CDC).

[8]  Indra Narayan Kar,et al.  Composite Adaptive Control of Uncertain Euler‐Lagrange Systems with Parameter Convergence without PE Condition , 2018, Asian Journal of Control.

[9]  Shubhendu Bhasin,et al.  Switched MRAC with improved performance using Semi-Initial Excitation , 2018, 2018 Annual American Control Conference (ACC).

[10]  Antonios Tsourdos,et al.  Composite Model Reference Adaptive Control with Parameter Convergence Under Finite Excitation , 2018, IEEE Transactions on Automatic Control.

[11]  Anuradha M. Annaswamy,et al.  Health monitoring with matrix regressor based adaptive observers , 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

[12]  Indra Narayan Kar,et al.  A UGES Switched MRAC Architecture Using Initial Excitation , 2017 .

[13]  R. Kamalapurkar,et al.  Simultaneous state and parameter estimation for second-order nonlinear systems , 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

[14]  Indra Narayan Kar,et al.  Parameter convergence via a novel PI-like composite adaptive controller for uncertain Euler-Lagrange systems , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

[15]  Anuradha M. Annaswamy,et al.  Matrix regressor adaptive observers for battery management systems , 2015, 2015 IEEE International Symposium on Intelligent Control (ISIC).

[16]  Girish Chowdhary,et al.  Concurrent Learning for Parameter Estimation Using Dynamic State-Derivative Estimators , 2015, IEEE Transactions on Automatic Control.

[17]  Girish Chowdhary,et al.  Exponential parameter and tracking error convergence guarantees for adaptive controllers without persistency of excitation , 2014, Int. J. Control.

[18]  Girish Chowdhary,et al.  Concurrent learning adaptive control of linear systems with exponentially convergent bounds , 2013 .

[19]  Travis E. Gibson,et al.  Projection Operator in Adaptive Systems , 2011, ArXiv.

[20]  Hongye Su,et al.  An adaptive observer for joint estimation of states and parameters in both state and output equations , 2011 .

[21]  M. Guay,et al.  Excitation Signal Design for Parameter Convergence in Adaptive Control of Linearizable Systems , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[22]  Daniel Liberzon,et al.  Switching in Systems and Control , 2003, Systems & Control: Foundations & Applications.

[23]  Qinghua Zhang,et al.  Adaptive observer for multiple-input-multiple-output (MIMO) linear time-varying systems , 2002, IEEE Trans. Autom. Control..

[24]  Antonio Loría,et al.  Relaxed persistency of excitation for uniform asymptotic stability , 2001, IEEE Trans. Autom. Control..

[25]  B. Delyon,et al.  A new approach to adaptive observer design for MIMO systems , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[26]  R. Marino,et al.  Adaptive observers with arbitrary exponential rate of convergence for nonlinear systems , 1995, IEEE Trans. Autom. Control..

[27]  Chen-Chung Liu,et al.  Adaptively controlling nonlinear continuous-time systems using multilayer neural networks , 1994, IEEE Trans. Autom. Control..

[28]  Frank L. Lewis,et al.  Neural net robot controller with guaranteed tracking performance , 1993, Proceedings of 8th IEEE International Symposium on Intelligent Control.

[29]  M. Gevers,et al.  Stable adaptive observers for nonlinear time-varying systems , 1987 .

[30]  Petar V. Kokotovic,et al.  Instability analysis and improvement of robustness of adaptive control , 1984, Autom..

[31]  Hidekatsu Tokumaru,et al.  Adaptive Observer with Exponential Rate of Convergence for Multi-Input Multi-Output Systems , 1984 .

[32]  Anuradha M. Annaswamy,et al.  Robust Adaptive Control , 1984, 1984 American Control Conference.

[33]  K. Ichikawa Principle of Lüders-Narendra's adaptive observer , 1980 .

[34]  M. Gupta,et al.  Adaptive observer and identifier design for multi-input multi-output systems* , 1977 .

[35]  G. Kreisselmeier Adaptive observers with exponential rate of convergence , 1977 .

[36]  K. Narendra,et al.  Stable adaptive schemes for state estimation and identification of linear systems , 1974 .

[37]  K. Narendra,et al.  A new canonical form for an adaptive observer , 1974 .

[38]  R. Carroll,et al.  An adaptive observer for single-input single-output linear systems , 1973 .

[39]  K. Narendra,et al.  An adaptive observer and identifier for a linear system , 1973 .

[40]  D. Luenberger Observing the State of a Linear System , 1964, IEEE Transactions on Military Electronics.

[41]  Indra Narayan Kar,et al.  Combined MRAC for Unknown MIMO LTI Systems With Parameter Convergence , 2018, IEEE Transactions on Automatic Control.

[42]  Maria Adler,et al.  Stable Adaptive Systems , 2016 .