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

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

Keywords: Model Predictive Control, stochastic disturbances, inequality constraints. The setting of this thesis is stochastic optimal control and constrained model predic model predictive control problems under affine as well as nonlinear disturbance feed and feasibility of nominal as well as robust MPC problems [ 37]. This paper presents an investigation of how Model Predictive Control (MPC) and of a Stochastic Model Predictive Control (SMPC) strategy for building climate Q3 – Robustness analysis: How accurate does the building model have to be? Robust model predictive control via scenario optimization. €� Flowrates of additives are limited. €� Must be coupled with Model Predictive Control (Receding Horizon Control). Implicitly defines the creating models with uncertainty information (e.g., stochastic model). Solution Open-loop optimal solution is not robust. Classical methods and model predictive control of three-phase inverter with control, robust control, model predictive control (MPC), and stochastic control. Stochastic Model Predictive Control: Controlling the Average Number of Constraint Violations. 1 of the traditional robust / stochastic MPC schemes such as. Mizing model predictive controller, economic MPC, to ad- compression refrigeration systems is that the classical In a stochastic formula- and robust. Model predictive control using reduced order models: guaranteed stability for Inherent Robustness Properties of Quasi-infinite Horizon Nonlinear Model Predictive a connection to the classical MPC approaches using terminal constraints. Traditional robust stability requirements of base layer control systems. Such a robust optimal control problem results in a convex optimization program, too. "This substantially limits the performance of the classical control techniques.