Email this article Model predictive Controller for Mobile Robot
Abstract
This paper proposes a Model Predictive Controller (MPC) for control of a P2AT mobile robot. MPC refers to a group of controllers that employ a distinctly identical model of process to predict its future behavior over an extended prediction horizon. The design of a MPC is formulated as an optimal control problem. Then this problem is considered as linear quadratic equation (LQR) and is solved by making use of Ricatti equation. To show the effectiveness of the proposed method this controller is implemented on a real robot. The comparison between a PID controller, adaptive controller, and the MPC illustrates advantage of the designed controller and its ability for exact control of the robot on a specified guide path.
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Guang, Li., Lennox, B., Zhengtao, Ding., 2005, Infinite horizon model predictive control for tracking problems,
Control and Automation,. ICCA '05. International Conference on, pages 516 – 521.
Camacho, E.F., Bordons, C., 1999. Model Predictive Control , Springer-Verlag 2 edition.
Nagy, Z. , Franke, R., Mahn, B., Allg , ower, F., 2005, Real-time implementation of nonlinear model predictive control of inite time processes in an industrial,framework. In International Workshop on Assessment and Future Directions of Nonlinear Model Predictive Control, Germany, pages 483-490.
Likar, B., Kocijan, J., 2007, Predictive control of a gas-liquid separation plant based on a Gaussian process model. Computers & Chemical Engineering, 31(1):142–152.
Hauge, T.A., Slora, R. and Lie, B., Model Predictive Control of a Norske Skog , Preliminary Study, in proceedings of Control Systems,2002, June 3-5, Stockholm, Sweden, pages 75-79.
Garcia, C.E., Prett, D.M, Morari, M., 1989. Model Predictive Control: Theory and Practice, A Survey. Automatica, 25(3):335-348.
Limon, D., Álamo, T., Camacho, E.F., 2005. Enlarging the domain of attraction of MPC controllers, Automatica.
Kouvaritakis, B., Cannon, M., Couchman, P., 2006, MPC as a tool for sustainable development integrated policy assessment. IEEE Transactions on Automatic Control, 51(145–149).
Bellemans, B., Schutter, D., De Moor, B., 2006, Model predictive control for ramp metering of motorway traffic: A case study, Control Engineering Practice, 14(7): 757-767.
van den Boom, T.J.J., De Schutter, B., 2006. MPC of implicit switching max-plus-linear discrete event systems - Timing aspects, Proceedings of the 8th International Workshop on Discrete Event Systems (WODES'06), Ann Arbor, Michigan, pages 457-462.
Azevedo, C., Poignet, P., Espiau, B., 2002. Moving horizon control for biped robots without reference trajectory. In IEEE International Conference on Robotics and Automation, pages 2762–2767.
Shridhar, R., Cooper, J., 1997. A Tuning Strategy for Unconstrained SISO Model Predictive Control. England: Chem..
Mayne, D.Q., Rawlings, J.B, Rao, C.V., Scokaert, P., 2000. Constrained model predictive control: Stability and optimality. Automatica, 36:789-814.
Axehill D., 2004. A Preprocessing Algorithm with Applications to MPC, 43th IEEE Conference on Decision and Control.
Axehila, D., 2004. A Preprocessing Algorithm with Applications to MPC , Fifth Conference on Computer Science and Systems Engineering, Norrköping, Sweden, October 21.
Dougherty D., Cooper, D., 2004. A practical multiple model adaptive strategy for single- loop MPC.
Gilbert, E. G., Tan., 1991. K., Linear system with state and control constraints: The theory and application of maximal output admissible sets. IEEE Transactions on Automatic Control, 36:1008-1020.
D. Gu, H. Hu, M. Brady, F. Li,1997, Navigation System for Autonomous Mobile Robots at Oxford, Proceedings of International Workshop on Recent Advances in Mobile Robots, Leicester, U.K., , 1-2: 24-33.
DOI: http://dx.doi.org/10.22149/teee.v2i2.96
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