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Robust sampled-data controller design for uncertain nonlinear systems via Euler discretization
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DOI：10.1002/rnc.5234.png)
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Abstract
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Robust stabilization of a class of uncertain nonlinear systems through a sampled-data control law is considered in this work. Based on the forward discrete-time Euler approximation, conditions in the form of linear matrix inequalities are provided to synthesize a discrete controller that guarantees the states to be asymptotically driven to the origin, regardless of the presence of bounded parametric uncertainties. In contrast with other approaches, the system is not required to be Lure-type nor the conditions to have predefined gains to be tested. Examples are given to illustrate the effectiveness of the proposal.
Keywords:
convex optimization
discretization
nonlinear systems
robust control
sampled-data control
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