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Finite-Time Model Predictive Control for Constrained Continuous-Time Systems

  • Beihang University
  • University of Pretoria

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, a finite-time model predictive control (MPC) framework is proposed for continuous-time systems subject to constraints. The proposed finite-time MPC is ex-tended from the methodology for discrete-time systems, where the control horizon is set equal to the system dimension, and only terminal cost is penalized in the optimization. Zero-Order-Holder (ZOH) is applied to ensure that no ripple exists between two consecutive sampling intervals, such that finite-time tran-sient process and zero steady-state error can be guaranteed. Combined with feedback linearization, the proposed deadbeat MPC is applicable to nonlinear continuous-time systems.

Original languageEnglish
Title of host publication2024 18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages308-313
Number of pages6
ISBN (Electronic)9798331518493
DOIs
StatePublished - 2024
Event18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024 - Dubai, United Arab Emirates
Duration: 12 Dec 2024 → 15 Dec 2024

Publication series

Name2024 18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024

Conference

Conference18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024
Country/TerritoryUnited Arab Emirates
CityDubai
Period12/12/24 → 15/12/24

Keywords

  • Model predictive control
  • constraints
  • finite-time control

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