A two-stage Kalman estimator for motion control using model predictive strategy
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-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 language | English |
|---|---|
| Title of host publication | 2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV) : Kunming, 6 December 2004 - 9 December 2004, 65079 |
| Number of pages | 6 |
| Volume | 3 |
| Publisher | IEEE - Institute of Electrical and Electronics Engineers Inc. |
| Publication date | 2004 |
| Pages | 1699-1704 |
| ISBN (print) | 0780386531 |
| DOIs | |
| Publication status | Published - 2004 |
| Externally published | Yes |
| Event | 8th International Conference on Control, Automation, Robotics and Vision - ICARCV2004 - Kunming, China Duration: 06.12.2004 → 09.12.2004 Conference number: 8 |
- Engineering
- Actuators, Disturbance estimation, Model predictive control, Two-stage Kalman filter