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Predictive control for delay systems: theory and applications

Abstract : In industrial processes, time delay often occurs in many dynamical systems, such as chemical processes, communication systems, and vehicle systems. Presence of time delay in a process increases the difficulty of controlling such systems. These delays can affect the state, input, and output; they can be constant or time varying, known or unknown, deterministic or stochastic depending on the systems under consideration. In this chapter, we propose a robust model predictive control (MPC) algorithm for a class of uncertain discrete-time systems with both states and input delays. We consider the constant and time-varying delay cases as well as the state feedback case. The uncertainty is assumed polytopic with a known upper bound. By the augmented system description we reduce a robust model predictive control law to a convex optimization involving linear matrix inequalities (LMIs). After defining an optimization problem that minimizes a cost function at each time instant, we compute a state feedback by minimizing the upper bound of the cost function subject to constraints on inputs. We give closed-loop stability conditions on the systematic construction of a Lyapunov–Krasovskii functional and compare its robustness properties with the standard MPC in the presence of parameter uncertainties and delay systems. Finally, we study the constrained control problem for a quarter-vehicle model and nonlinear system using the proposed robust MPC.
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Contributor : Frédéric Davesne <>
Submitted on : Monday, March 15, 2021 - 10:19:26 AM
Last modification on : Wednesday, April 14, 2021 - 3:37:07 AM



Sofiane Bououden, Mohammed Chadli. Predictive control for delay systems: theory and applications. Control Strategy for Time-Delay Systems, Elsevier, pp.143--178, 2021, ⟨10.1016/B978-0-32-385347-7.00011-0⟩. ⟨hal-03169120⟩



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