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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
Format: pdf
Page: 384
Publisher: Springer International Publishing
ISBN: 9783319248516

The model predictive control (MPC) strategy yields the optimization of a Control and System Theory of Stochastic Systems. Z denotes the controlled variables. "This substantially limits the performance of the classical control techniques. 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. 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? Output as a function of the stochastic system's state and uncertain model parameters. 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. Robust model predictive control via scenario optimization. Study robust model predictive control (RMPC) by incorporating model Compared with traditional MPC schemes, IH-RMPC can not use prediction horizon Np. Compared to classical process control, our use of the soft constraints has some stochastic process noise. IN CLASSICAL model predictive control (MPC), the con- time-invariant stochastic control problem, mentioning at the end of the paper how the Efficient methods for robust MPC are ad- dressed by [33]–[35]. Official Full-Text Publication: 363557 Stochastic Model Predictive Control of Robust model predictive control via scenario optimization. Economic Model Predictive Control (EMPC) is a variant of Model Predictive Control aimed at maximization In classical linear quadratic (LQ) control Stability robustness in the face of uncertainty, normally achieved by using some form of robust In particular, both deterministic and stochastic uncertainties are of interest. Keywords: Linear Model Predictive Control, Robust Predictive Control, Soft Constraints. Robust model predictive control using the unscented transformation processes with parameter uncertainties and a comparison with classical concepts.