A Data-compressed Technique of a Reference Governor in a Piecewise Affine Function

This paper shows how to construct a reference governor for which the size of its implemented data can be adjusted with an integer parameter nu, keeping an assurance of fulfilling a pointwise-in-time constraint. Using a technique called "blocking", a management method is established that changes the external reference every nu T_s period, where T_s denotes a sampling period of a constrained system. The constraint fulfillment for an infinite time is achieved by satisfying a terminal condition using a maximal output admissible set. The reference governor is finally obtained with an explicit solution to the convex quadratic programming problem. Simulation and experimental evaluations demonstrate its effectiveness at constraint fulfillment and data compression.