Robust output-feedback controller design via local BMI optimization

doi:10.1016/j.automatica.2004.01.028

2004-07-01

159

PRE

DOI：10.1016/j.automatica.2004.01.028

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摘要

En 中文

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. (C) 2004 Elsevier Ltd. All rights reserved.

Keyword:

multiobjective control

robust control design

structured uncertainty

dynamic output-feedback

LMIs

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期刊

Automatica

IF:

5.9

论文数:

1.2W

被引数:

5.2W

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