Extended parameter robust control by Bayesian identification synthesis

The Parameter Robust Control by Bayesian Identification (PRCBI) synthesis, whose robustness measure depends on the quality of Bayesian parameter estimates, is extended to linear time-invariant systems where all state-space matrices are sensitive to an uncertain parameter vector. For a conceptual comprehension of the mathematical treatment employed, the new approach is first applied to a simple fictitious second order system and then applied to a more realistic problem representing a power system model whose state and output matrices vary with the uncertain parameter. The results clearly show the validity of the new formulation.