Bo Chen

H∞ Filtering for Markovian Switching Genetic Regulatory Networks with Time-Delays and Stochastic Disturbances

This paper is concerned with thexa0H∞ filtering problem for a class of nonlinear Markovian switching genetic regulatory networks (GRNs) with time-delays, intrinsic fluctuation and extrinsic noise. The delays, which exist in both the translation process and feedback regulation process, are not dependent on the system model. The intrinsic fluctuation is described as a state-dependent stochastic process, while the extrinsic noise is modeled as an arbitrary signal with bounded energy, and no exact statistics about the noise are required to be known. The aim of the problem addressed is to design a Markovian jump linear filter to estimate the true concentrations of mRNA and protein through available measurement outputs. By resorting to the Lyapunov functional method and some stochastic analysis tools, it is shown that if a set of linear matrix inequalities (LMIs) is feasible, then the desired linear filter exists. The designed filter ensures asymptotic mean-square stability of the filtering error system and two prescribed L2-induced gains from the noise signals to the estimation errors. Finally, an illustrative example is given to demonstrate the effectiveness of the approach proposed.

H∞ filtering for discrete-time genetic regulatory networks with random delays

The H(∞) filtering problem is investigated in this paper for a class of discrete-time genetic regulatory networks (GRNs) with random delays. The addressed filtering problem is to estimate the concentrations of mRNA and protein, and the filtering error system is modeled as a Markovian switched system. By using a properly constructed Lyapunov function, a sufficient condition is derived in terms of linear matrix inequalities (LMIs), which can guarantee stochastic stabilization of the filtering error system. Then, an optimization problem with LMIs constraints is established to design an H(∞) filter which ensures an optimal H(∞) disturbance attenuation level. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed results.

Exponential convergence rate estimation for neutral BAM neural networks with mixed time-delays

This paper is concerned with the exponential stability analysis problem for a class of neutral bidirectional associative memory neural networks with mixed time-delays, where discrete, distributed and neutral delays are involved. By utilizing the delay decomposition approach and an appropriately constructed Lyapunov–Krasovskii functional, some novel delay-dependent and decay rate-dependent criteria for the exponential stability of the considered neural networks are derived and presented in terms of linear matrix inequalities. Furthermore, the maximum allowable decay rate can be estimated based on the obtained results. Three numerical examples are given to demonstrate the effectiveness of the proposed method.

Energy-Efficient Weighted Observation Fusion Kalman Filtering with Randomly Delayed Measurements

This paper is concerned with the weighted observation fusion Kalman filtering problem for a class of multi-sensor fusion systems with random measurement delays and energy constraints. To reduce the energy consumptions, each sensor intermittently sends information to the fusion center in a random way. By using the full rank decomposition approach, the observation fusion equation is derived. Without resorting to the augmentation technique, optimal weighted observation fusion Kalman filter (WOFKF) is given, and it is proved that the performance of the WOFKF is equivalent to that of the centralized fusion Kalman filter. Simulations show the effectiveness of the proposed fusion methods.

Distributed Fault-Tolerant Consensus Protocol for Fuzzy Multi-Agent Systems

A distributed actuator fault-tolerant strategy for fuzzy multi-agent systems is investigated in this paper. The proposed strategy utilizes an adaptive methodology in designing the consensus control. Compared with well-known consensus analysis, this paper devotes to the fault effect in analyzing multi-agent consensus problem. We conducted a Lyapunov stability analysis to unfold the advantages of proposed method in the distributed fault-tolerant control. Simulation example is provided to demonstrate the effectiveness of the theoretical results.