Robust Event-Triggered Model Predictive Control for Uncertain Linear Parameter-Varying Systems

A novel robust composite event-triggered model predictive control method is proposed for linear parameter-varying systems. The proposed controller integrates the nominal and robust compensation elements for optimal control in terms of the error between the observer state and the nominal. Only when the output of the observer violates the measurement error condition, the controller can be updated during the recalculation process of the optimal problem. The activation strategy effectively reduces the communication and computational burden, and the control design framework combines uncertainties and bounded disturbances into a robust invariant set to guarantee system stability. Finally, the viability of the method is verified through simulation experiments.