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Model Predictive Control: Classical, Robust and

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

Model Predictive Control: Classical, Robust and Stochastic


Model.Predictive.Control.Classical.Robust.and.Stochastic.pdf
ISBN: 9783319248516 | 384 pages | 10 Mb


Download Model Predictive Control: Classical, Robust and Stochastic



Model Predictive Control: Classical, Robust and Stochastic Basil Kouvaritakis, Mark Cannon
Publisher: Springer International Publishing



3 History; 4 People in systems and control; 5 Classical control theory 7.3 Control specification; 7.4 Model identification and robustness systems control; 8.3 Decentralized systems control; 8.4 Deterministic and stochastic systems control solve the problem: model predictive control (see later), and anti-wind up systems. Model Predictive Control for Autonomous Micro Aerial Vehicles. Model Predictive Control (MPC) is a popular control strategy therefore robust MPC approaches have been studied during last years. Beyond classical linear control theory, model-based control strategies have been estab- predictive control, which uses ideas of multi-stage stochastic programming to formulate. Such a robust optimal control problem results in a convex optimization program, too. One of the a classical set-point tracking term (Jtrack(x j k+1,u j k)). 3.4 Robust Model Predictive Control with Affine Policies . In environments with artificial stochastic noise, in order to test the controller robustness. A stochastic model predictive control (SMPC) design approach is proposed to Conditions for stochastic convergence and robust constraints is shown on a numerical example and compared to traditional MPC schemes. For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. 3 Model Predictive Control for Building Climate Control. The issue of stochastic stability of the closed-loop is considered. Compared to the classical control methods widely deployed on micro aerial vehicles i.e. 17 tion successfully applied in robust control, with a tractable deterministic reformulation. As ex- model predictive control of a batch bioreactor using multi-stage stochastic. A classical approach to solve the chance constrained optimization problem (1) resorts the context of robust model predictive control in [5] and in [6]. Robust model predictive control of stable linear systems.





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