Chen Shi-ming

An LCOR model for suppressing cascading failure in weighted complex networks

Based on the relationship between capacity and load, cascading failure on weighted complex networks is investigated, and a load-capacity optimal relationship (LCOR) model is proposed in this paper. Compared with three other kinds of load-capacity linear or non-linear relationship models in model networks as well as a number of real-world weighted networks including the railway network, the airports network and the metro network, the LCOR model is shown to have the best robustness against cascading failure with less cost. Furthermore, theoretical analysis and computational method of its cost threshold are provided to validate the effectiveness of the LCOR model. The results show that the LCOR model is effective for designing real-world networks with high robustness and less cost against cascading failure.

Exponential stability of networked control systems with short time delay

Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems. Based on the linear time-invariant process, the mathematic model of networked control systems is set up when the sensor and the actuator are time driven, the is event driven, and the network induced delay is not longer than a sampling period. Using the optimal control theory, the discrete optimal controller of the networked control system is designed. The structure of proposed controller is simple and convenient to use. The controller can render the networked control systems exponentially stable. In the end the simulation based on the unstable inverted pendulum is studied. The simulation results show the proposed method is effective.

Research on scalable swarming behavior integrating position aggregating and velocity synchronization

This paper propose a networked swarm model integrating aggregation of individualpsilas position, in which position topology of the networked swarm can be hold connective due to the individual aggregating force to each balance point, and synchronization of scalable swarming behavior can be implemented. The individual motion equation consist of the term approaching to the individualpsilas balance point and the term to the average angle of its neighbors, the weights of which is decided by the difference between the individualpsilas current position to its ideal balance position. Results show that synchronization of scalable swarming behavior can be implemented with this motion equation.