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by Dennis van Hessem
Stochastic model predictive control: Insights and . Stochastic inequality constrained closed-loop model predictive control : with application to chemica. Dennis Harald van. Vita.
Stochastic model predictive control: Insights and performance comparisons for linear systems. Stochastic model predictive control hinges on the online solution of a stochastic optimal control problem. This paper presents a computationally efficient solution method for stochastic optimal control for nonlinear systems subject to (time-varying) stochastic disturbances and (time-invariant) probabilistic model uncertainty in initial conditions and parameters.
Mechanical Maritime and Materials Engineering.
van Hessem, D. H. (2004). Stochastic inequality constrained closed-loop model predictive control with application to chemical process operation. thesis, Delft University of Technology. Vitus, M. & Tomlin, C. J. (2011). On feedback design and risk allocation in chance constrained control. In Proceedings of IEEE Conference on Decision and Control (pp. 734–739). Williams, J. Fisher, J. & Willsky, A. S. (2007). Approximate dynamic programming for ained sensor network management. IEEE Transactions on Signal Processing, 55, 4300–4311.
Energy efficient building climate control using Stochastic Model Predictive Control and weather predictions. Closed-loop stochastic dynamic process optimization under input and state constraints. Frauke Oldewurtel, Alessandra Parisio, +6 authors Klaus-Dieter Wirth. Proceedings of the 2010 American Control Conference. van Hessem, O. Bosgra. Proceedings of the 2002 American Control Conference (IEEE Cat.
Dennis Harald van Hessem. PhD thesis, Delft University of Technology, 2004. Jun Yan and Robert R. Bitmead.
D. Van Hessem, Stochastic inequality constrained closed-loop model predictive control–with application to chemical process opera-tion, 2004. L. Blackmore and M. Ono, Convex chance constrained predictive control without sampling, in AIAA Guidance, Navigation, and Control Conference, 2009. M. P. Vitus and C. Tomlin, Closed-loop belief space planning for linear, gaussian systems, in IEEE International Conference on Robotics and Automation.
Constrained model predictive control: Stability and optimality. Stochastic Receding Horizon Control with Output Feedback and Bounded Control Inputs. Automatica, 36:789–814, 2000. Hokayem, E. Cinquemani, D. Chatterjee, J. Lygeros, and F. Ramponi. In IEEE Conference on Decision and Control, pages 6095–6100, 2010. Cannon, B. Kouvaritakis, and Xingjian Wu. Probabilistic Constrained MPC for Multiplicative and Additive Stochastic Uncertainty. Stochastic closed-loop model predictive control of continuous nonlinear chemical processes. Journal of Process Control, 16(3):225–241, 2006. H Deng, M Krstic, and . Williams.
Stochastic Inequality Constrained Closed loop Model Predictive Control With Application To Chemical Process Operation.
Introduction to MPC and constrained control 2. Prediction and optimization 3. Closed loop properties 4. Disturbances and integral action 5. Robust tube MPC. 1-4. Books. 1 B. Kouvaritakis and M. Cannon, Model Predictive Control: Classical, Robust and Stochastic, Springer 2015 Recommended reading: Chapters 1, 2 & 3. 2 . Mayne, Model Predictive Control: Theory and Design. Nob Hill Publishing, 2009. Maciejowski, Predictive control with constraints. Prentice Hall, 2002 Recommended reading: Chapters 1–3, 6 & 8. 1-5. 2004. Dissertation, Delft Uni-versity of Technology. Yan, . and Bitmead, R. R. 2005.