OPTIMALLY SCALED H-INFINITY FULL INFORMATION CONTROL SYNTHESIS WITH REAL UNCERTAINTY

An algorithm to synthesize optimal controllers for the scaled H-infini ty full information problem with real and complex uncertainty is prese nted. The control problem is reduced to a linear matrix inequality, wh ich can be solved via a finite dimensional convex optimization, This t echnique is compared with the optimal scaled H-infinity full informati on with only complex uncertainty and D-K iteration control design to s ynthesize controllers for a missile autopilot. Directly including real parametric uncertainty into the control design results in improved ro bust performance of the missile autopilot. The controller synthesized via D-K iteration achieves results similar to the optimal designs.