Resumen de Reference governors for chance-constrained systems
Uros V. Kalabi´c, Nan Li, Christopher Vermillion, Ilya Kolmanovsky
This paper presents a reference governor formulation that is applicable to systems with stochastic disturbances and achieves constraint satisfaction properties that are analogous to those of conventional reference governors. In particular, the reference governor proposed herein is shown to enforce chance constraints, guarantee a form of eventual recursive feasibility, and guarantee almost-sure convergence to constant, constraint-admissible reference inputs. It can also be applied to enforce constraints for closed-loop systems with state observers. This stands in contrast with traditional reference governor techniques, which must be heuristically tuned in order to achieve a balance between constraint satisfaction and the size of achievable steady-state references in the presence of stochastic disturbances. A numerical example is reported which illustrates the operation of the reference governor for chance-constrained systems and is compared to the conventional, robust approach.
