This paper is concerned with the state estimation problem for a class of nonlinear cyber-physical systems (CPSs) where the nonlinear dynamical physical process is approximated by a Takagi-Sugeno fuzzy model. The physical plant is measured by a set of wireless sensors and the sensors communicate with the remote estimator via a communication channel. In the considered CPS, the randomly occurring sensor saturation, signal quantization, packet dropouts as well as the medium access constraint are studied in a unified framework. We develop a sufficient condition such that the filtering error system is asymptotically stable in the mean-square sense and also with a prescribed H _∞ performance level. The filter gain parameters are determined by solving a convex optimization problem. Finally, the simulation study on the networked truck-trailer system is presented to show the effectiveness of the proposed estimator design.

This paper is concerned with the distributed estimation problem in sensor networks subjected to unknown attacks. Network attacks are considered to exist in two classes of channels: 1) communication channels from the plant to sensors and 2) communication channels among sensors. The status of an attack is viewed as a stochastic phenomenon, and the transmitted information will be affected when the attacker successfully carries out an attack on the related data packet. Based on the sensors' own measurements and their neighbors' local information, a novel distributed estimation model against two-channel stochastic attacks is presented. A sufficient condition on the existence of the desired distributed H _∞ estimators is derived and the distributed estimator gains are designed by solving a linear matrix inequality. Two illustrative examples are provided to demonstrate the effectiveness of the new design techniques.

This paper is concerned with the set-membership estimation problem for complex networks subject to unknown but bounded attacks. Adversaries are assumed to exist in the nonsecure communication channels from the nodes to the estimators. The transmitted measurements may be modified by an attack function with added noise that is determined by the adversary but unknown to the estimators. A novel set-membership estimation model against unknown but bounded attacks is presented. Two sufficient conditions are derived to guarantee the existence of the set-membership estimators for the cases that the attack functions are linear and nonlinear, respectively. Two strategies for the design of the set-membership estimator gains are presented. The effectiveness of the proposed estimator design method is verified by two simulation examples.

In practical engineering, the sampling intervals of networked control systems are often subject to undesirable physical constraints, which results in noisy sampling intervals. In view of this, we focus on the linear plants without unknown parameters and investigate the stabilization problem of networked control systems with noisy sampling intervals and stochastic time-varying delays. First, a closed-loop discrete-time stochastic system, whose system matrices are characterized by high nonlinearity and randomness, is obtained by considering the noisy sampling intervals and stochastic time-varying delays in a unified framework. Second, an equivalent yet tractable stochastic-augmented model is established with the aid of matrix exponential computation. With a confluent Vandermonde matrix associated with the minimal polynomial and Kronecker product operation, the mathematical expectation of a product of three matrices, including the system matrix of the stochastic-augmented model and its transpose, is calculated. Based on this, a stabilization controller is designed such that the stochastic stability of the original discrete-time stochastic system is guaranteed. Finally, an illustrative example with four different cases is provided to verify the effectiveness of the designed method.