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Relaxing the conditions for parameter estimation-based observers of nonlinear systems via signal injection

Abstract : Parameter estimation-based observers are a new kind of state reconstruction methods where the state observation task is translated into an on-line parameter estimation problem. A key step for its application is the transformation of the system dynamics into a particular cascade form, which involves the solution of a partial differential equation that, moreover, should satisfy some injective requirement. In this note we use a recently proposed technique of signal injection to generate new outputs and simplify these tasks. In this way, we make this observer applicable to a wider class of nonlinear systems—even with indistinguishable states. The application of the proposed approach is illustrated with the design of a novel sensorless controller for magnetic levitation systems.
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Bowen Yi, Roméo Ortega, Weidong Zhang. Relaxing the conditions for parameter estimation-based observers of nonlinear systems via signal injection. Systems and Control Letters, Elsevier, 2018, 111, pp.18-26. ⟨10.1016/j.sysconle.2017.10.011⟩. ⟨hal-01816429⟩

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