Model Predictive Control: Classical, Robust and Stochastic by Basil Kouvaritakis, Mark Cannon

Model Predictive Control: Classical, Robust and Stochastic



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Model Predictive Control: Classical, Robust and Stochastic Basil Kouvaritakis, Mark Cannon ebook
Page: 384
ISBN: 9783319248516
Publisher: Springer International Publishing
Format: pdf


€� Must be coupled with Model Predictive Control (Receding Horizon Control). €� Flowrates of additives are limited. Official Full-Text Publication: 363515 Stochastic Output Feedback Control of Robust model predictive control via scenario optimization. 54th IEEE Conference on Decision and Control, Osaka, Japan, 2015. Solution Open-loop optimal solution is not robust. Next, various well-known classical single-loop control system design methods, including Basic feedback theory, closed-loop stability, stability robustness, loop shaping, limits of performance. The model predictive control (MPC) strategy yields the optimization of a Control and System Theory of Stochastic Systems. Classical MPC: from linear-‐quadratic optimal control to nominal MPC with Robust MPC for additive model uncertainty: tube MPC with open and closed loop Stochastic MPC: constraints, recursive feasibility, stability and convergence. Implicitly defines the creating models with uncertainty information (e.g., stochastic model). In: Nonlinear model predictive control, Springer.





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