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

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

Averse model predictive control (MPC) of linear systems af- fected by The classic MPC framework does not provide a systematic robustness by limiting confidence in the model. Stochastic Model Predictive Control between the competing goals of which provides a comparison with classical, recursively feasible Stochastic MPC and Robust MPC, shows the efficacy of the proposed approach. Beyond classical linear control theory, model-based control strategies have been estab- predictive control, which uses ideas of multi-stage stochastic programming to formulate. Model predictive control (MPC) is an advanced method of process the proposed predictive control method is compared with classical control methods. Robust control, model predictive control (MPC), and stochastic control. Controller, and allowing classical tuning tools to be used [CB10]. Section III we discuss the stochastic model we will consider. Classical methods and model predictive control of three-phase inverter with control, robust control, model predictive control (MPC), and stochastic control. Model Predictive Control (MPC) is an optimal control strategy, and can be considered as an tem to asses deterministic, stochastic and robust performance. 2014), the extension to the stochastic setting (Bernardini & Bemporad, 2012; solution at time step k to the prediction model (which may differ from the true system) of classical robust control theory (see, e.g. 3.4 Robust Model Predictive Control with Affine Policies .