Self-scheduled control of a gyroscope
A classical mixed sensitivity minimization approach and a model matching formulation are compared with the goal to design a linear parameter-varying augmented state feedback control law for a laboratory-scale control moment gyroscope. Dynamic weighting filters are used to impose integral action and roll-off on the controller. Consequently, measurement noise is effectively suppressed and steady state accuracy is guaranteed even in the presence of input disturbances. Both designs are validated in real-time experiments and compared to a previous design that uses static weights. With the new designs, control effort is reduced while transient performance is maintained and tracking accuracy, as well as disturbance attenuation, is improved.
Linear parameter-varying systems
Mixed sensitivity problem
Multivariable control systems
Robust control applications
Robust controller synthesis