The optimal projection/maximum entropy approach to designing low-order, robust controllers for flexible structures

The Optimal Projection/Maximum Entropy approach to designing low-order controllers for high-order systems with parameter uncertainties is reviewed. The philosophy of representing uncertain parameters by means of Stratonovich multiplicative white noise is motivated by means of the Maximum Entropy Principle of Jaynes and statistical analysis of modal systems. The main result, the optimal projection equations for fixed-order dynamic compensation in the presence of state-, control- and measurement-dependent noise, represents a fundamental generalization of classical LQG theory.