For the consensus problem of time-varying multi-agent systems under time-varying topology connection, an event-triggered impulsive control protocol was proposed. In this protocol, for each agent, the controller would be updated only when the related state error exceeded a threshold, and the control inputs would be carried out only at the event triggering instants, and continuous communication between agents was avoided. This protocol would greatly reduce the cost of communication and control for network consensus. The sufficient conditions for the multi-agent systems with time-varying characteristics to achieve consensus under event-triggered impulsive control were analyzed based on the algebraic graph theory, Lyapunov stability and impulsive differential equation. At the same time, it was proved theoretically that there was no Zeno behavior in the event-triggered time sequences. Finally, the effectiveness of the obtained theoretical conclusion was verified through several numerical simulations.

In order to improve the robustness and efficiency of medical image encryption algorithm based on chaos, a new robust medical image encryption algorithm based on rapid chaotic scrambling named RMIEF-CS was presented. Firstly, the presented algorithm utilized two low dimensional chaotic systems to generate chaotic sequence with an alternating iterative way, and the problem of chaotic convergence due to computer precision was solved. Secondly, the data stream of plaintext image was firstly scrambled using the generated chaotic sequence, and the ciphertext was scrambled once again using a new chaotic sequence to obtain the final ciphertext image. In the second scrambling procedure, a bidirectional ciphertext feedback mechanism was used to enhance the security and robustness of RMIEF-CS. Because the proposed algorithm used the simple low chaotic system to generate key sequence, and did not need the time-consuming sort operation, it had good time efficiency and could be suitable for images with any shape. The simulation experimental results show that the presented algorithm has better encryption performance, and can decrypt the approximate image to the original medical image even if the ciphertext image has been damaged. In addition, compared with the method based on even scrambling and chaotic mapping, the time consumption of RMIEF-CS is reduced to 1/6. The presented algorithm is suitable for transmitting the medical image with large amount of data in real-time.