标题：Event-Based Prediction-Correction State Estimator * * This work was supported in part by a Grant from the French Ministry of Higher Education and Research.
摘要：AbstractThis paper deals with the problem of state estimation for linear continuous-time systems based on the prediction-correction (PC) set-membership approach. Although the abundant literature on using the PC estimation approach, the case of event-based measurement sampling is still poorly investigated. In the developed approach, the measurement in the correction step of the PC approach is taken only when a prior defined threshold is crossed. A convergence analysis is proposed for ensuring the boundedness of the estimated state enclosure. The effectiveness of the proposed approach is shown through numerical simulation for an unobservable linear system. This approach is compared to the classical PC approach where the measurement is continuously taken.
关键词：KeywordsSet-membership estimationEvent-triggeredLinear system
