Quantized Output Feedback Tracking Control for Discrete-Time Periodic Markov Jump Systems With Packet Loss Compensation

被引:0
|
作者
Zhang, Fan [1 ]
Hua, Mingang [1 ]
Deng, Feiqi [2 ]
Fei, Juntao [1 ]
Chen, Hua [3 ]
机构
[1] Hohai Univ, Coll Artificial Intelligence & Automat, Changzhou 213200, Peoples R China
[2] South China Univ Technol, Coll Automat Sci & Engn, Guangzhou 510640, Peoples R China
[3] Hohai Univ, Coll Sci, Nanjing 210098, Peoples R China
基金
中国国家自然科学基金;
关键词
Packet loss; Output feedback; Quantization (signal); Smoothing methods; Bandwidth; Automation; Weight measurement; Symmetric matrices; Random variables; Trajectory; Discrete-time; tracking controller; periodic Markov jump systems; single exponential smoothing approach; packet loss compensation; quantization; MODEL;
D O I
10.1109/TASE.2024.3486067
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The H-infinity static output feedback tracking control issue for discrete-time periodic Markov jump systems with quantization and packet loss is explored. The packet loss follows Bernoulli random distribution, which assumes that the packet is discarded in a probabilistic manner before being transmitted to the controller. On this basis, considering the restricted network bandwidth, a novel quantization-based packet loss compensation scheme using single exponential smoothing approach is firstly given to help offset the influence of network congestion and missing packets. Then, an output feedback tracking controller is firstly designed to minimize the tracking error between the system output and the given reference model output. Aiming at the loss of mode information, the tracking controller designed is partially mode-dependent. Furthermore, by giving a mode-dependent Lyapunov function with periodicity, the sufficient condition for the existence of this controller is derived to ensure the stability of the tracking error system with H-infinity performance. Ultimately, the effectiveness and practicality of the developed technique are demonstrated through an example of a single-link robotic arm model.
引用
收藏
页数:12
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