Robust output-feedback controller design via local BMI optimization


Reference:
S. Kanev, C. Scherer, M. Verhaegen, and B. De Schutter, "Robust output-feedback controller design via local BMI optimization," Automatica, vol. 40, no. 7, pp. 1115-1127, July 2004.

Abstract:
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.


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Bibtex entry:

@article{KanSch:03-007,
        author={S. Kanev and C. Scherer and M. Verhaegen and B. {De Schutter}},
        title={Robust output-feedback controller design via local {BMI} optimization},
        journal={Automatica},
        volume={40},
        number={7},
        pages={1115--1127},
        month=jul,
        year={2004},
        doi={10.1016/j.automatica.2004.01.028}
        }



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