Robust event-triggered data-driven control subject to control constraints

被引:0
|
作者
Echreshavi, Zeinab [1 ]
Farbood, Mohsen [1 ]
Shasadeghi, Mokhtar [1 ]
Mobayen, Saleh [2 ,3 ]
机构
[1] Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz
[2] Department of Electrical Engineering, University of Zanjan, Zanjan
[3] Graduate School of Intelligent Data Science, National Yunlin University of Science and Technology, Yunlin, Douliu
关键词
Control input constraint; Control input rate constraint; Data-driven control; Event-triggered control; Noisy data;
D O I
10.1007/s00500-024-10304-1
中图分类号
学科分类号
摘要
This paper concerns with the problem of robust event-triggered data-driven control (DDC) considering control input and rate control constraints, simultaneously for discrete-time multi-input multi-output (MIMO) linear systems such that only the noisy data are measurable. Firstly, the data-dependent representation of the closed-loop system controlled by an event-triggered-based feedback control law is obtained. More precisely, to reduce the unnecessary communication resources, the control input updates and consequently, improve the system performance, event-triggered mechanism is utilized to design a stabilizing controller. Under a decreasing triggering threshold and a quadratic Lyapunov function, the ultimate boundedness stability (UBS) of the closed-loop system is ensured and the bounded region is expressed. Sufficient conditions for the UBS of the system are derived in terms of data-dependent linear matrix inequalities (LIMs). To meet the practical problems such as inherent limitations of the practical systems and to maximize the life-time of the actuators, the control input and rate control constraints are considered, simultaneously in the design procedure. In this scenario, the sufficient conditions are also obtained based on data-dependent LMIs. Finally, to demonstrate the effectiveness of the proposed control method, the recommended robust constrained event-triggered DDC is implemented to a numerical example and the simulation results demonstrate the validity of the proposed control approach. Moreover, a table is presented to compare the practical metrics such as robustness, necessities of the model plant identification, computational burden and control input constraints to verify the superiorities of the proposed method despite the existing results. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
引用
收藏
页码:13083 / 13096
页数:13
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