Rubagotti, Matteo and Patrinos, Panagiotis and Bemporad, Alberto Stabilizing embedded MPC with computational complexity guarantees. In: Proceedings of European Control Conference. IEEE, pp. 3065-3070. ISBN 978-3-033-03962-9 (2013)Full text not available from this repository.
This paper describes a model predictive control (MPC) approach for discrete-time linear systems with hard constraints on control and state variables. The finite-horizon optimal control problem is formulated as a quadratic program (QP), and solved using a recently proposed dual fast gradient-projection method. More precisely, in a finite number of iterations of the mentioned optimization algorithm, a solution with bounded levels of infeasibility and suboptimality is determined for an alternative problem. This solution is shown to be a feasible suboptimal solution for the original problem, leading to exponential stability of the closed-loop system. The proposed strategy is particularly useful in embedded control applications, for which real-time constraints and limited computing resources can impose tight bounds on the possible number of iterations that can be performed within the scheduled sampling time.
|Item Type:||Book Section|
|Additional Information:||2013 European Control Conference (ECC) July 17-19, 2013, Zürich, Switzerland.|
|Uncontrolled Keywords:||Closed loop systems, Optimal control, Optimization, Real-time systems, Stability analysis, Standards, Vectors|
|Subjects:||T Technology > TJ Mechanical engineering and machinery|
|Research Area:||Computer Science and Applications|
|Depositing User:||Ms T. Iannizzi|
|Date Deposited:||05 Mar 2014 14:12|
|Last Modified:||05 Mar 2014 14:12|
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