Sampled-data model predictive control using adaptive time-mesh refinement algorithms

• Type: Article in International Conference Proceedings Book
• Date: 2017-09

Authors

Luís Tiago Paiva (Author) FEUP; Fernando A. C. C. Fontes (Author) FEUP

Conference proceedings International

Title: Lecture Notes in Electrical Engineering

Pages: 143-153

12th Portuguese Conference on Automatic Control, CONTROLO 2016

14 September 2017 through 16 September 2017

Indexing

Scopus - 11 Citations

INSPEC

Other information

Authenticus ID: P-00K-X2T

DOI: 10.1007/978-3-319-43671-5_13

Abstract (EN): We address sampled¿data nonlinear Model Predictive Control (MPC) schemes, in particular we address methods to efficiently and accurately solve the underlying continuous-time optimal control problems (OCP). In nonlinear OCPs, the number of discretization points is a major factor affecting the computational time. Also, the location of these points is a major factor affecting the accuracy of the solutions. We propose the use of an algorithm that iteratively finds the adequate time¿mesh to satisfy some pre¿defined error estimate on the obtained trajectories. The proposed adaptive time¿mesh refinement algorithm provides local mesh resolution considering a time¿dependent stopping criterion, enabling an higher accuracy in the initial parts of the receding horizon, which are more relevant to MPC. The results show the advantage of the proposed adaptive mesh strategy, which leads to results obtained approximately as fast as the ones given by a coarse equidistant¿spaced mesh and as accurate as the ones given by a fine equidistant¿spaced mesh. © Springer International Publishing Switzerland 2017.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11