attaoveisi / Extended_State_Observer

a disturbance rejection-based solution to the problem of robust output regulation of linear systems. The difference between the underlying plant and its nominal mathematical model is represented by two classes of disturbances. The first class is generated by an autonomous linear system while the other class has no specific dynamical structure. Robustness against the first disturbance class is achieved by the internal model principle. Next, in the framework of disturbance rejection control, an extended state observer (ESO) is designed to estimate and compensate for the second class of disturbances. As a result, the proposed output regulation method can deal with a vast range of uncertainties. The stability of the closed loop system is investigated and results on practical regulation are drawn. Keywords—Output regulation, extended state observer, disturbance rejection, linear system, robustness

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Extended_State_Observer

a disturbance rejection-based solution to the problem of robust output regulation of linear systems. The difference between the underlying plant and its nominal mathematical model is represented by two classes of disturbances. The first class is generated by an autonomous linear system while the other class has no specific dynamical structure. Robustness against the first disturbance class is achieved by the internal model principle. Next, in the framework of disturbance rejection control, an extended state observer (ESO) is designed to estimate and compensate for the second class of disturbances. As a result, the proposed output regulation method can deal with a vast range of uncertainties. The stability of the closed loop system is investigated and results on practical regulation are drawn.

Keywords—Output regulation, extended state observer, disturbance rejection, linear system, robustness

refer to https://scholar.google.com/citations?user=-HRHoYoAAAAJ&hl=de

[1] B. A. Francis and W. M. Wonham, “The internal model principle of control theory,” Automatica, vol. 12, no. 5, pp. 457–465, 1976.

[2] B. Francis, O. A. Sebakhy, and W. M. Wonham, “Synthesis of multivariable regulators: The internal model principle,” Appl Math Optim, vol. 1, no. 1, pp. 64–86, 1974.

[3] A. Isidori, L. Marconi, and A. Serrani, “Fundamentals of Internal-Model-Based Control Theory,” in Advances in Industrial Control, Robust Autonomous Guidance: An Internal Model Approach, A. Isidori, L. Marconi, and A. Serrani, Eds., London: Springer London, 2003, pp. 1–58.

[4] J. Huang and Z. Chen, “A General Framework for Tackling the Output Regulation Problem,” IEEE Trans. Automat. Contr., vol. 49, no. 12, pp. 2203–2218, 2004.

[5] E. J. Davison and A. Goldenberg, “Robust control of a general servomechanism problem: The servo compensator,” Automatica, vol. 11, no. 5, pp. 461–471, 1975.

[6] Z. Gao, “On the centrality of disturbance rejection in automatic control,” (ENG), ISA transactions, vol. 53, no. 4, pp. 850–857, 2014.

[7] J. Huang, “Linear Output Regulation,” in Advances in design and control, Nonlinear output regulation: Theory and applications, J. Huang, Ed., Philadelphia,, Great Britain: SIAM, 2004, pp. 1–34.

[8] Z. Chen and J. Huang, “Robust Output Regulation: A Framework,” in Advanced Textbooks in Control and Signal Processing, Stabilization and Regulation of Nonlinear Systems, Z. Chen and J. Huang, Eds., Cham: Springer International Publishing, 2015, pp. 197–237.

[9] A. A. Prasov and H. K. Khalil, “A Nonlinear High-Gain Observer for Systems With Measurement Noise in a Feedback Control Framework,” IEEE Trans. Automat. Contr., vol. 58, no. 3, pp. 569–580, 2013.

[10] S. Sastry, Nonlinear systems: Analysis, stability and control. New York: Springer, 1999.

[11] S. Boyd, L. E. Ghaoui, E. Feron, and V. Balakrishnan, Linear matrix inequalities in system and control theory. Philadelphia, Pa.: Society for Industrial and Applied Mathematics, 1994.

[12] M. Grant and S. Boyd, “Graph implementations for nonsmooth convex programs,” in Lecture Notes in Control and Information Sciences, Recent Advances in Learning and Control, V. Blondel, S. Boyd, and H. Kimura, Eds.: Springer-Verlag Limited, 2008, pp. 95–110.

[13] M. Grant and S. Boyd, CVX: Matlab Software for Disciplined Convex Programming, version 2.1. Available: http://cvxr.com/cvx.

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a disturbance rejection-based solution to the problem of robust output regulation of linear systems. The difference between the underlying plant and its nominal mathematical model is represented by two classes of disturbances. The first class is generated by an autonomous linear system while the other class has no specific dynamical structure. Robustness against the first disturbance class is achieved by the internal model principle. Next, in the framework of disturbance rejection control, an extended state observer (ESO) is designed to estimate and compensate for the second class of disturbances. As a result, the proposed output regulation method can deal with a vast range of uncertainties. The stability of the closed loop system is investigated and results on practical regulation are drawn. Keywords—Output regulation, extended state observer, disturbance rejection, linear system, robustness

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