A two-stage Kalman estimator for motion control using model predictive strategy

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

The paper proposes an hybrid Kalman filter integrating a robust and optimal algorithm for the use as an observer in model-varying predictive control (MVPC) of a nonlinear system. Moreover, a position MPC is derived in detail. Even though the proposed approach is quite general, a real case coming from automotive application is studied using computer simulation to demonstrate the effectiveness of the proposed technique. Simulations and results with real data are also discussed. © 2004 IEEE.
Original languageEnglish
Title of host publication2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV) : Kunming, 6 December 2004 - 9 December 2004, 65079
Number of pages6
Volume3
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Publication date2004
Pages1699-1704
ISBN (print)0780386531
DOIs
Publication statusPublished - 2004
Externally publishedYes
Event8th International Conference on Control, Automation, Robotics and Vision - ICARCV2004 - Kunming, China
Duration: 06.12.200409.12.2004
Conference number: 8

    Research areas

  • Engineering
  • Actuators, Disturbance estimation, Model predictive control, Two-stage Kalman filter