Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Quantized control of Markov jump nonlinear systems based on fuzzy hidden Markov model|
|Citation:||IEEE Transactions on Cybernetics, 2018; 49(7):2420-2430|
|Shanling Dong, Zheng-Guang Wu, Peng Shi, Hongye Su, and Tingwen Huang|
|Abstract:||This paper considers the problem of asynchronous guaranteed cost control (GCC) for nonlinear Markov jump systems with stochastic quantization. Hidden Markov model is used to describe the nonsynchronous controller and the random quantization phenomenon. Based on Takagi–Sugeno fuzzy technique and Lyapunov function approach, a sufficient condition is obtained, which can not only ensure the asymptotic stability of the closed-loop system and existence of the desired controller, but also can yield the minimal upper bound of GCC performance. Finally, two examples are provided to demonstrate the correctness and reliability of our developed approaches.|
|Keywords:||Asynchronous controller; hidden Markov model (HMM); random quantization; Takagi–Sugeno (T–S) fuzzy technique|
|Rights:||© 2018 IEEE|
|Appears in Collections:||Electrical and Electronic Engineering publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.