Title
Stabilizing embedded MPC with computational complexity guarantees
Abstract
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.
Year
Venue
Keywords
2013
Control Conference
closed loop systems,computational complexity,discrete time systems,gradient methods,iterative methods,linear systems,optimal control,predictive control,quadratic programming,stability,closed-loop system,computational complexity guarantees,control variables,discrete-time linear systems,dual fast gradient-projection method,embedded mpc,embedded control applications,exponential stability,finite-horizon optimal control problem,infeasibility level,iterations,model predictive control,sampling time,stabilization,state variables,suboptimality level,optimization,stability analysis,real time systems,vectors
Field
DocType
Citations 
Mathematical optimization,Optimal control,Linear system,Linear-quadratic-Gaussian control,Control theory,Model predictive control,Exponential stability,State variable,Quadratic programming,Mathematics,Computational complexity theory
Conference
1
PageRank 
References 
Authors
0.35
0
3
Name
Order
Citations
PageRank
Rubagotti, M.1412.70
Panagiotis Patrinos226831.71
Alberto Bemporad34353568.62