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Fixed-Order Controller Design for SISO Systems Using Monte Carlo Technique

Pavel Shcherbakov, Boris Polyak, Yana Petrikevich
A novel randomized approach to fixed-order controller design is proposed for discrete-time SISO plants.
It is based on the Monte Carlo sampling Schur stable polynomials using so-called Fam--Meditch parametrization
and projecting them onto the affine set of closed-loop characteristic polynomials, which is defined by the controller
parameters. If the sampling-projecting procedure fails to find a stabilizing controller, certain candidate controllers
are then locally optimized by means of an iterative method of nonsmooth optimization.
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