1. Nonlinear MPC for Tracking for a Class of Nonconvex Admissible Output Sets
- Author
-
Emanuele Garone, Daniel R. Ramirez, Andres Cotorruelo, and Daniel Limon
- Subjects
0209 industrial biotechnology ,Mathematical optimization ,Optimization problem ,Linear programming ,Computer science ,MathematicsofComputing_NUMERICALANALYSIS ,Convex set ,02 engineering and technology ,Extension (predicate logic) ,Homeomorphism ,Computer Science Applications ,Nonlinear system ,Model predictive control ,020901 industrial engineering & automation ,Control and Systems Engineering ,TheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITY ,Convergence (routing) ,Electrical and Electronic Engineering - Abstract
This article presents an extension to the nonlinear model predictive control (MPC) for tracking scheme able to guarantee convergence even in cases of nonconvex output admissible sets. This is achieved by incorporating a convexifying homeomorphism in the optimization problem, allowing it to be solved in the convex space. A novel class of nonconvex sets is also defined for which a systematic procedure to construct a convexifying homeomorphism is provided. This homeomorphism is then embedded in the MPC optimization problem in such a way that the homeomorphism is no longer required in closed form. Finally, the effectiveness of the proposed method is showcased through an illustrative example.
- Published
- 2021