In this work, we propose a design strategy for adaptive control of a class of nonlinear systems with input and state constraints. The systems of interest are required to have relative degree 1 and a convergent zero-dynamics: these properties cover a significant number of applications, after suitable changes of coordinates and with a proper selection of the regulated output. Through a design based on Barrier Lyapunov Functions, inspired by Explicit Reference Governors, we propose a feasible closed-form right-inverse unit that can be effectively interconnected with a nominal adaptive stabilizer, this way enforcing constraint satisfaction, while rejecting the effects of parametric uncertainties at the same time. The stabil- ity and feasibility properties of the control scheme are formally proven, and verified in a detailed numerical simulation.

Bosso, A. (2019). Constrained-Inversion MRAC: An Approach Combining Hard Constraints and Adaptation in Uncertain Nonlinear Systems” [10.1109/CDC40024.2019.9030145].

Constrained-Inversion MRAC: An Approach Combining Hard Constraints and Adaptation in Uncertain Nonlinear Systems”

Bosso Alessandro
;
Christian Conficoni;Andrea Tilli
2019

Abstract

In this work, we propose a design strategy for adaptive control of a class of nonlinear systems with input and state constraints. The systems of interest are required to have relative degree 1 and a convergent zero-dynamics: these properties cover a significant number of applications, after suitable changes of coordinates and with a proper selection of the regulated output. Through a design based on Barrier Lyapunov Functions, inspired by Explicit Reference Governors, we propose a feasible closed-form right-inverse unit that can be effectively interconnected with a nominal adaptive stabilizer, this way enforcing constraint satisfaction, while rejecting the effects of parametric uncertainties at the same time. The stabil- ity and feasibility properties of the control scheme are formally proven, and verified in a detailed numerical simulation.
2019
Proceedings of the 58th IEEE Conference on Decision and Control
2039
2045
Bosso, A. (2019). Constrained-Inversion MRAC: An Approach Combining Hard Constraints and Adaptation in Uncertain Nonlinear Systems” [10.1109/CDC40024.2019.9030145].
Bosso, Alessandro, Andrea Serrani, Christian Conficoni, Andrea Tilli
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/741301
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