Title :
Every Continuous Nonlinear Control System Can be Obtained by Parametric Convex Programming
Author :
Baes, Michel ; Diehl, Moritz ; Necoara, Ion
Author_Institution :
Electr. Eng. Dept., Katholieke Univ. Leuven, Leuven
Abstract :
In this short note, we define parametric convex programming (PCP) in a slightly different manner than it is usually done by extending convexity not only to variables but also to the parameters, and we show that the widely applied model predictive control (MPC) technique is a particular case of PCP. The main result of the note is an answer to the inverse question of PCP: which feedback laws can be generated by PCP? By employing results of convex analysis, we provide a constructive proof-yet not computational-that allows us to conclude that every continuous feedback law can be obtained by PCP.
Keywords :
continuous systems; convex programming; feedback; nonlinear control systems; predictive control; continuous feedback law; continuous nonlinear control system; model predictive control; parametric convex programming; Circuit stability; Feedback; Hypercubes; Iterative methods; Linear matrix inequalities; Linear systems; Nonlinear control systems; Predictive control; Predictive models; Transmission line matrix methods; Continuous feedback laws; model predictive control (MPC); parametric convex programming (PCP);
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2008.928131
