Semi-automatic tuning of NMPC based trajectory control system in agricultural machine

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 44, Issue 1 PART 1, 2011, Pages 2912-2918

  Backman, Juha ^a   Oksanen, Timo ^a   Visala, Arto ^a  

^a AALTO UNIVERSITY   (Finland)

Author keywords

Guidance system; Navigation; Trajectory following; Tuning

Indexed keywords

AGRICULTURAL MACHINERY; AGRICULTURAL ROBOTS; AGRICULTURE; EXTENDED KALMAN FILTERS; MODEL PREDICTIVE CONTROL; NAVIGATION; PREDICTIVE CONTROL SYSTEMS; TRAJECTORIES; TUNING;

AGRICULTURAL MACHINE; CONTROLLED SYSTEM; EXPERIMENTAL CONTROL; GUIDANCE SYSTEM; NONLINEAR MODEL PREDICTIVE CONTROL; TRAJECTORY CONTROL; TRAJECTORY CONTROL SYSTEMS; TRAJECTORY FOLLOWING;

STATE ESTIMATION;

EID: 84866756389     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20110828-6-IT-1002.00601     Document Type: Conference Paper

References (12)

1. Backman, J., Oksanen, T., and Visala, A. (2010). Nonlinear Model Predictive Trajectory Control in Tractor-Trailer System for Parallel Guidance in Agricultural Field Operations. In Agricontrol 2010. Kyoto, Japan.
2. Congwei, H., Chen, W., Chen, Y., and Dajie L. (2003). Adaptive Kalman Filtering for Vehicle Navigation. Journal of Positioning Systems, 2(1), pp. 42-47.
3. Jetto, L., Longhi, S. and Venturini, G. (1999a). Development and Experimental Validation of an Adaptive Extended Kalman Filter for the Localization of Mobile Robots. IEEE Transactions on Robotics and Automation, 15(2), pp. 219-229.
4. Jetto, L., Longhi, S. and Vitali, D. (1999b). Localization of a wheeled mobile robot by sensor data fusion based on a fuzzy logic adapted Kalman filter. Control Engineering Practice, 7(6), pp. 763-771.
5. Kühne, F., Gomes da Silva Jr., J.M., Lages, W.F. (2005). Mobile Robot Trajectory Tracking Using Model Predictive Control. In VII SBAI II LARS. São Luís, Brazil.
6. Lenain, R., Thuilot, B., Cariou, C. and Martinet, P. (2005). Model Predictive Control for Vehicle Guidance in Presence of Sliding: Application to Farm Vehicles Path Tracking. In Proceedings of the 2005 IEEE International Conference on Robotics and Automation, pp. 885-890. ICRA, Barcelona, Spain.
7. Mohamed, A.H., and Schwarz, K.P. (1999). Adaptive Kalman Filtering for INS/GPS. Journal of Geodesy, 73, pp. 193-203.
8. Odelson, B.J., Lutz, A., and Rawlings, J.B. (2006). The Autocovariance Least-Squares Method for Estimating Covariances: Application to Model-Based Control of Chemical Reactors. IEEE Transactions on Control System Technology, 14(3), pp. 532-540.
9. Sasiadek, J.Z., Wang, Q. and Zeremba, M.B. (2000). Fuzzy Adaptive Kalman Filtering for INS/GPS Data Fusion. In Proceedings of the 15th IEEE International Symposium on Intelligent Control, pp. 181-186. ISIC, Rio, Patras, Greece.
10. Vougioukas, S.G. (2007). Reactive Trajectory Tracking for Mobile Robots based on Non Linear Model Predictive Control. In 2007 IEEE International Conference on Robotics and Automation, pp. 3074-3079. ICRA, Roma, Italy.
11. Weidong, D., Wang, J., Rizos, C., and Kinlyside, D. (2007). Improving Adpative Kalman Estimation in GPS/INS Integration. The Journal of Navigation, 60, pp. 517-529.
12. Wojsznis, W., Gudaz, J., Blevins, T., and Mehta, A. (2003). Practical approach to tuning MPC. ISA Transactions, 42(1), pp. 149-162.