Unconstrained tracking MPC for continuous-time nonlinear systems

Unconstrained tracking MPC for continuous-time nonlinear systems

In this paper, we extend unconstrained model predictive control (MPC) from setpoint stabilization to dynamic reference tracking for continuous-time nonlinear systems. In particular, we focus on the case when the reference cannot be perfectly tracked by the system due to dynamics and/or constraints....

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Bibliographic Details
Main Authors: Long, Yushen, Xie, Lihua
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2022
Subjects:
Engineering::Electrical and electronic engineering
Model Predictive Control
Tracking Control
Online Access:https://hdl.handle.net/10356/159357
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Institution: Nanyang Technological University
Language: English
Description
Summary:In this paper, we extend unconstrained model predictive control (MPC) from setpoint stabilization to dynamic reference tracking for continuous-time nonlinear systems. In particular, we focus on the case when the reference cannot be perfectly tracked by the system due to dynamics and/or constraints. Under the incremental stabilizability assumption and an additional dissipativity assumption, the practical stability of tracking the unknown optimal reachable reference trajectory is proved even though the controller does not know such a reference explicitly.

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