Nonstationary quantized control for discrete-time Markov jump singularly perturbed systems against deception attacks
| Autor: | Dong Yan, Jinde Cao, Jun Cheng, Changfeng Xue, Xia Zhou, Yanfang Tang |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Sequence Computer Networks and Communications Computer science Applied Mathematics Quantization (signal processing) Markov process 02 engineering and technology Exponential function symbols.namesake Bernoulli's principle 020901 industrial engineering & automation Discrete time and continuous time Control and Systems Engineering Control theory Bounded function Signal Processing 0202 electrical engineering electronic engineering information engineering symbols 020201 artificial intelligence & image processing |
| Zdroj: | Journal of the Franklin Institute. 358:2915-2932 |
| ISSN: | 0016-0032 |
| DOI: | 10.1016/j.jfranklin.2021.01.038 |
| Popis: | This paper addresses the nonstationary quantized control problem for the discrete-time Markov jump singularly perturbed systems (MJSPSs) subject to deception attacks (DAs). The control inputs are characterized by randomly occurring DAs and nonstationary quantization simultaneously, where the DAs are depicted by means of a Bernoulli distributed sequence. By applying a multi-layer structure methodology (MLSM), the nonstationary controllers are devised for MJSPSs. Meanwhile, the correlation among system mode, controller mode, and quantizer mode are portrayed via the nonstationary Markov process. Based on a mode-dependent Lyapunov functional, sufficient criteria are established such that the resulting closed-loop system (CLS) is stochastic mean square exponential ultimately bounded (SMSEUB), and the desired controller is designed. Ultimately, two simulation examples are offered to elaborate on the validity and superiority of the proposed theoretical results. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect