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.