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

Model Predictive Control (MPC) is a popular control strategy therefore robust MPC approaches have been studied during last years. Publication » Stochastic Tubes in Model Predictive Control With Probabilistic Constraints. Stochastic Model Predictive Control: Controlling the Average Number of Constraint Violations of the traditional robust / stochastic MPC schemes such as. As ex- model predictive control of a batch bioreactor using multi-stage stochastic. In this paper, we consider MPC for constrained discrete-time systems with stochastic parameters which are assumed to be a set of serially correlated time series. 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. Section III we discuss the stochastic model we will consider. In recent years, many Model Predictive Control (MPC) methods for dynamic loop one, i.e. 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. The gains K(i), as in classical robust MPC, see. "This substantially limits the performance of the classical control techniques. Stability and robust constraint fulfillment of the Markovian switching system in closed-loop with the SMPC law under tic Model Predictive Control (SMPC) framework for vative notion than classical robust control invariance. One of the a classical set-point tracking term (Jtrack(x j k+1,u j k)). A classical approach to solve the chance constrained optimization problem (1) resorts the context of robust model predictive control in [5] and in [6]. 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? Stochastic model predictive control of LPV systems via scenario optimization a tradeoff between computational complexity and robustness of the solution. 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].