A New Control Framework K0=V-1U is a nominal stabilizing controller for P0=M-1N. The transfer function from y to u is K=(V-QN)-1(U+QM) for some stable Q which is the parameterization of all stabilizing controller for P0=M-1N. f=0 if the plant model is perfect (=0): Tyr=P0K0(I+P0K0)-1 Q does not affect nominal tracking disturbance rejection and robust stability are guaranteed by Q Tyd=(I+P0K)-1 Tyu=K(I+P0K)-1 When plant is stable, take N=P0, M=I When K0 is minimum phase, take U=I and V-1=K0 .

Fault Tolerant Control our approach Conventional method: model the failures as model uncertainties and a robust worst case control design is done. Too conservative ! worst case is rare. New method: Design K0=V-1U to satisfy the system performance by assuming no faults (and model uncertainties). Design Q (using any robust techniques, fuzzy control methods, adaptive techniques, etc) to tolerate possible actuators and/or sensors failures (and model uncertainties). Q can be made adaptive or be scheduled for different situations. We believe every fault tolerant controller should be in this form.

Example: A Gyroscope simulation with one sensor fault one input and two outputs system. one sensor fault at 8 sec. LQG controller becomes unstable with the sensor fault H controller is robust but slow. Our new controller performs exactly the same as the nominal LQG controller when there is no fault and maintains stability when there is a fault.

Experimental Study experiments with/without sensor fault Our new controller (GIMC) performs closely to the LQG controller (K0). The difference is caused by the model uncertainties. H controller fails to perform because of dead zone. Without Sensor Fault at 2.2 sec. System with LQG controller becomes unstable. Our new controller performs well and maintains stability