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Sufficient Conditions for Global Integral Action via Incremental Forwarding for Input-Affine Nonlinear Systems

Mattia Giaccagli, Daniele Astolfi, Vincent Andrieu, Lorenzo Marconi

2021IEEE Transactions on Automatic Control33 citationsDOIOpen Access PDF

Abstract

In this article, we study the problem of constant output regulation for a class of input-affine multi-input multi-output nonlinear systems, which do not necessarily admit a normal form. We allow the references and the disturbances to be arbitrarily large and the initial conditions of the system to range in the full-state space. We cast the problem in the contraction framework, and we rely on the common approach of extending the system with an integral action processing the regulation error. We then present sufficient conditions for the design of a state-feedback control law able to make the resulting closed-loop system incrementally stable, uniformly with respect to the references and the disturbances. Such a property ensures uniqueness and attractiveness of an equilibrium on which output regulation is obtained. To this end, we develop an incremental version of the forwarding (mod <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\lbrace L_gV\rbrace$</tex-math></inline-formula> ) approach. Finally, we provide a set of sufficient conditions for the design of a pure (small-gain) integral-feedback control. The proposed approach is also specialized for two classes of systems that are linear systems having a Lipschitz nonlinearity and a class of minimum-phase systems whose zero dynamics are incrementally stable.

Topics & Concepts

Lipschitz continuityAffine transformationUniquenessNonlinear systemControl theory (sociology)MathematicsClass (philosophy)Applied mathematicsComputer sciencePure mathematicsControl (management)Mathematical analysisPhysicsQuantum mechanicsArtificial intelligenceControl and Stability of Dynamical SystemsAdaptive Control of Nonlinear SystemsAdvanced Control Systems Optimization