The paper deals with the problem of robust output regulation for minimum-phase nonlinear systems in a semiglobal setting. We present a different perspective to the problem of adaptive regulation in which prediction error identification methods, which are routinely used in other control contexts, can be adopted to design robust nonlinear regulators. The proposed control structure combines continuous-time dynamics and 'hybrid identifiers', the latter specifically designed to estimate the actual steady-state control law. The proposed framework encompasses existing frameworks proposed so far in the nonlinear continuous-time literature.

Forte, F., Marconi, L., Teel, A.R. (2017). Robust Nonlinear Regulation: Continuous-Time Internal Models and Hybrid Identifiers. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 62(7), 3136-3151 [10.1109/TAC.2016.2626143].

Robust Nonlinear Regulation: Continuous-Time Internal Models and Hybrid Identifiers

Marconi, Lorenzo;
2017

Abstract

The paper deals with the problem of robust output regulation for minimum-phase nonlinear systems in a semiglobal setting. We present a different perspective to the problem of adaptive regulation in which prediction error identification methods, which are routinely used in other control contexts, can be adopted to design robust nonlinear regulators. The proposed control structure combines continuous-time dynamics and 'hybrid identifiers', the latter specifically designed to estimate the actual steady-state control law. The proposed framework encompasses existing frameworks proposed so far in the nonlinear continuous-time literature.
2017
Forte, F., Marconi, L., Teel, A.R. (2017). Robust Nonlinear Regulation: Continuous-Time Internal Models and Hybrid Identifiers. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 62(7), 3136-3151 [10.1109/TAC.2016.2626143].
Forte, Francesco; Marconi, Lorenzo; Teel, Andrew R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/740949
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