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Robust output-feedback controller design via local BMI optimization. (English) Zbl 1051.93042

Summary: The problem of designing a globally optimal full-order output-feedback controller for polytopic uncertain systems is known to be a non-convex NP-hard optimization problem that can be represented as a bilinear matrix inequality optimization problem for most design objectives. In this paper a new approach is proposed to the design of locally optimal controllers. It is iterative by nature, and starting from any initial feasible controller it performs local optimization over a suitably defined non-convex function at each iteration. The approach features the properties of computational efficiency, guaranteed convergence to a local optimum, and applicability to a very wide range of problems. Furthermore, a fast (but conservative) LMI-based procedure for computing an initially feasible controller is also presented. The complete approach is demonstrated on a model of one joint of a real-life space robotic manipulator.

MSC:

93B52 Feedback control
93B40 Computational methods in systems theory (MSC2010)
93B51 Design techniques (robust design, computer-aided design, etc.)
15A39 Linear inequalities of matrices
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