Combined linear quadratic Gaussian and H-infinity control of a benchmark problem

A combined linear quadratic Gaussian and Hx design method is applied to a benchmark problem. Robust controllers are derived that minimize an upper bound of a quadratic performance index subject to an Hx norm bound on a disturbance transfer function matrix. Real parameter variations are included in the design through the addition of fictitious weighted disturbances. Three design cases, each with different robustness, performance, and disturbance rejection requirements, are considered for the benchmark problem. Uncertain parameters and noncollocation of the sensor and actuator make the problem nontrivial. Compensators are found that meet the requirements with reasonable control effort, controller complexity, and noise rejection.