Self-Triggered Model Predictive Control With Sample-and-Hold Fashion for Constrained Continuous-Time Linear Systems

Author:

He Ning1,Zhang Yiwen1,Ma Kai1,Chen Qingqing1,Li Yuxiang1

Affiliation:

1. School of Mechanical and Electrical Engineering, Xi'an University of Architecture and Technology , Xi'an 710311, China

Abstract

Abstract A novel self-triggered model predictive control (STMPC) strategy for linear constrained systems with additive disturbance is presented in this paper. The actuator adopts the control input from the controller by sample-and-hold fashion. At the same time, the triggering threshold is designed to ensure the feasibility of the algorithms and the stability of the closed-loop system. Furthermore, two different ways to generate the event triggered input signal, namely, using single sample and multiple samples, are proposed and it is shown that better triggering performance can be obtained as the number of samples increases. In the last, the effectiveness and applicability of the proposed methods are verified by simulation.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shaanxi Province

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Reference31 articles.

1. Robust Nonlinear Model Predictive Control With Model Predictive Sliding Mode for Continuous-Time Systems;ASME J. Dyn. Syst., Meas., Control,2022

2. Robust Self-Triggered Min–Max Model Predictive Control for Discrete-Time Nonlinear Systems;Automatica,2018

3. Model Predictive Static Programming for Optimal Command Tracking: A Fast Model Predictive Control Paradigm;ASME J. Dyn. Syst., Meas., Control,2019

4. Robust Model Predictive Control of Constrained Linear Systems With Bounded Disturbances;Automatica,2005

5. Self-Triggered Model Predictive Control for Continue Linear Constrained System: Robustness and Stability,2018

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