Event-based Distributed Filtering Approach to Nonlinear Stochastic Systems over Sensor Networks
- 10 Downloads
In this paper, an event-triggered communication strategy and a distributed filtering scheme are designed for discrete-time nonlinear stochastic systems over wireless sensor networks (WSNs). The underlying system is represented by the Takagi-Sugeno (T-S) fuzzy model, and in addition by the description of the WSN under consideration. The structure of the WSN is established on a deterministic one. Based on an event-triggering condition tailored for each sensor, distributed fuzzy filters are established using the triggered measurements of the smart sensors. As a result, an augmented stochastic system is presented for the distributed filtering design. A robust mean-square asymptotic stability criterion is explored using the Lyapunov stability theory and the Disk stability constraint is applied to improve the performance of the distributed filters. An optimization solution to obtaining the parameters of the distributed filters is developed. Subsequently, a computer-simulated example helps to illustrate the validity of the proposed new filtering design techniques.
KeywordsDistributed filtering event-triggered control fuzzy systems sensor networks
Unable to display preview. Download preview PDF.
- L. Zhao, N. Chen, and Y. Jia, “An improved energy efficient routing protocol for heterogeneous wireless sensor networks,” International Journal of Innovative Computing, Information and Control, vol. 13, no. 5, pp. 1637–1648, 2017.Google Scholar
- Z. Xiujuan and F. Huajing, “Recursive state estimation for discrete-time nonlinear systems with event-triggered data transmission, norm-bounded uncertainties and multiple missing measurements,” International Journal of Robust and Nonlinear Control, vol. 26, no. 17, pp. 3673–3695, Nov. 2016.MathSciNetCrossRefzbMATHGoogle Scholar
- J. Hu, Z. Wang, J. Liang, and H. Dong, “Event-triggered distributed state estimation with randomly occurring uncertainties and nonlinearities over sensor networks: a delayfractioning approach,” Journal of the Franklin Institute, vol. 352, no. 9, pp. 3750–3763, 2015.MathSciNetCrossRefzbMATHGoogle Scholar
- H. Ren, G. Zong, and H. R. Karimi, “Asynchronous finitetime filtering of networked switched systems and its application: an event-driven method,” IEEE Trans. on Circuits and Systems I: Regular Papers, pp. 1–12, 2018.Google Scholar
- J. Song, Y. Niu, J. Lam, and H.-K. Lam, “Fuzzy remote tracking control for randomly varying local nonlinear models under fading and missing measurements,” IEEE Trans. on Fuzzy Systems, pp. 1–1, 2017.Google Scholar
- K. Tanaka and H. O. Wang, =Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach, John Wiley & Sons, New York, 2004.Google Scholar