Variance-Constrained H∞H_{\infty } finite-horizon filtering for multi-rate time-varying networked systems based on stochastic protocols

summary:In this paper, the variance-constrained $H_\infty$ finite-horizon filtering problem is investigated for a class of time-varying nonlinear system under muti-rate communication network and stochastic protocol (SP). The stochastic protocol is employed to determine which sensor obtains access to the muti-rate communication network in order to relieve communication burden. A novel mapping technology is applied to characterize the randomly switching behavior of the data transmission resulting from the utilization of the SP in muti-rate communication network. By using relaxation method, sufficient conditions are derived for the existence of the finite-horizon filter satisfying both the prescribed $H_\infty$ performance and the covariance requirement of filtering errors, and the solutions of filters satisfying the above indexes are obtained by using linear matrix inequalities. Finally, the validity and effectiveness of the proposed filter scheme are verified by numerical simulation

Fault Detection of Networked Control Systems Based on Sliding Mode Observer

This paper is concerned with the network-based fault detection problem for a class of nonlinear discrete-time networked control systems with multiple communication delays and bounded disturbances. First, a sliding mode based nonlinear discrete observer is proposed. Then the sufficient conditions of sliding motion asymptotical stability are derived by means of the linear matrix inequality (LMI) approach on a designed surface. Then a discrete-time sliding-mode fault observer is designed that is capable of guaranteeing the discrete-time sliding-mode reaching condition of the specified sliding surface. Finally, an illustrative example is provided to show the usefulness and effectiveness of the proposed design method

Fault Detection for Wireless Network Control Systems with Stochastic Uncertainties and Time Delays

The fault detection problem is investigated for a class of wireless network control systems which has stochastic uncertainties in the state-space matrices, combined with time delays and nonlinear disturbance. First, the system error observer is proposed. Then, by constructing proper Lyapunov-Krasovskii functional, we acquire sufficient conditions to guarantee the stability of the fault detection observer for the discrete system, and observer gain is also derived by solving linear matrix inequalities. Finally, a simulation example shows that when a fault happens, the observer residual rises rapidly and fault can be quickly detected, which demonstrates the effectiveness of the proposed method

Dynamic graph learning: A structure-driven approach

The purpose of this paper is to infer a dynamic graph as a global (collective) model of time-varying measurements at a set of network nodes. This model captures both pairwise as well as higher order interactions (i.e., more than two nodes) among the nodes. The motivation of this work lies in the search for a connectome model which properly captures brain functionality across all regions of the brain, and possibly at individual neurons. We formulate it as an optimization problem, a quadratic objective functional and tensor information of observed node signals over short time intervals. The proper regularization constraints reflect the graph smoothness and other dynamics involving the underlying graph’s Laplacian, as well as the time evolution smoothness of the underlying graph. The resulting joint optimization is solved by a continuous relaxation of the weight parameters and an introduced novel gradient-projection scheme. While the work may be applicable to any time-evolving data set (e.g., fMRI), we apply our algorithm to a real-world dataset comprising recorded activities of individual brain cells. The resulting model is shown to be not only viable but also efficiently computable

Fault Detection for Wireless Network Control System Based on Sliding Mode Observer

This paper considers the fault detection problem of wireless network control system with time delay and uncertainties. For a class of model which has bounded disturbance and unknown fault, a sliding mode observer is designed for the situation that all the states of the system can be measured and no missing measurement occurs. We convert the design of fault detection observer to the design of reaching motion and sliding motion, by the use of Lyapunov function, a sufficient condition for sliding motion with time delay independent and uncertainties is acquired through linear matrix inequality, while the nonlinear item in observer is also designed. Finally, the effectiveness of proposed method is demonstrated by simulation results

Fault Detection for Networked Control Systems Based on Wireless Sensor Networks

Focusing on a class of networked control systems built around wireless sensor networks (WSN), the controller and the actuator in systems are assumed to be time-driven and the clocks are fully synchronized. The observer based on discrete switched systems is designed to detect faults which occur in the system. Firstly, by studying the transmission characteristics of data with wireless sensor networks, the augmented fault observer is constructed, and the observer is equivalent to the discrete switched system. Secondly, based on Lyapunov stability theory, the stability condition of observer can be viewed as a linear matrix inequality and the stability of system is proved. When the system is normal, if the given inequality condition is satisfied, the observer system is stable. When a fault occurs, the observer can detect the fault by the rapid change of residue. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method