Event-Triggered Interpolation Predictive Control of Linear Parameter-Varying Systems
In this paper,an event-triggered interpolation model predictive control method is proposed for constrained linear parameter varying(LPV)systems with uncertain bounded disturbances.By the interpolation method,optimization problem solution will show the current moment system default parameterized form of feedback control law,to reduce the number of optimization problem solving variables and reduce the burden of the system.Superimposing the multiplicative perturbations of system scheduling parameters and the additive perturbations of each time point,a finite step compact constraint set is constructed to realize the robust constraints.And the deviation of the nominal system and the actual system that exceeds the tight constraint set is used as the trigger condition.Trigger thresholds associated with interpolation coefficients and robust constraint sets are calculated online.We show that the proposed algorithm is recursively feasible and the closed-loop system is input-to-state stable in the attraction region.Finally,an example is given to verify the proposed method.
Model predictive controllinear parameter-varying systemevent-trigger controlinterpolation based control
NETL
NSTL
万方数据
