A sufficient condition to design unknown input observers for nonlinear systems with arbitrary relative degree
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Universidade Federal de Minas Gerais
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This article addresses the problem of state and unknown inputs (UIs) estimation for nonlinear systems with arbitrary relative degree with respect to the UIs. For this purpose, a novel nonlinear unknown input observer (UIO) is proposed, which is able to decouple the UIs by using the derivatives of the output signal. The error dynamics is attained by an exact handling and a factorization of its gradient to obtain a local polytopic representation suitable for input-affine nonlinear systems. For that representation, a novel design condition based on convex optimization and linear matrix inequalities is proposed to exponentially stabilize the estimation error and to guarantee the validity of the proposed nonlinear UIO. Numerical simulations indicate the effectiveness of the proposed approach for different classes of nonlinear systems, for which the UIs could be totally decoupled from the state estimation.
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The state estimation of nonlinear systems is a basic concern in control theory, which becomes more challenging in the presence of uncertainties. The uncertainties are unavoidable since they are related, for example, to disturbances, inaccurate models, faults and cyber-attacks. This context motivates the design of observers that are able to estimate simultaneously the system states and uncertainties. In this sense, the reconstruction of disturbances plays an important role to support, for example, secure estimation, fault diagnosis, and fault-tolerant control3 strategies. However, while the disturbance estimation problem is well addressed for linear systems under usual conditions, such as unitary relative degree, the literature is still incipient for nonlinear systems with arbitrary relative degree.
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https://onlinelibrary.wiley.com/doi/full/10.1002/rnc.6273