Abstract
This paper proposes a reference management technique for closed-loop systems with state and control constraints. The management rule is represented in the form of a piecewise state affine function obtained from an explicit solution to a multi-parametric quadratic programming problem, which explicitly considers not only a constraint fulfillment but also a tracking performance. Therefore, it can be realized that successive and optimal management of a given constant reference is online. However, as our approach theoretically has no robustness for modeling errors and noises, we performe its experimental validation using a real position servomechanism and show results of the effectiveness and practicability. Additionally, from the aspect of its implementation we also illustrate the experimental responses in the case that each sampling time of the local closed loop system and our reference governor is different, and state an issue about a reference governor in the future.
