Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the ...Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the navigation test of the self-propelled model, the complex environment including various port facilities, navigation facilities, and the ships nearby must be considered carefully, because in this dense environment the impact of sea waves and winds on the model is particularly significant. In order to improve the security of the self-propelled model, this paper introduces the Q learning based on reinforcement learning combined with chaotic ideas for the model＇s collision avoidance, in order to improve the reliability of the local path planning. Simulation and sea test results show that this algorithm is a better solution for collision avoidance of the self navigation model under the interference of sea winds and waves with good adaptability.展开更多
Greater complexity and interconnectivity across systems embracing electrical power technologies has meant that cyber-security issues have attracted significant attention. In this paper a simulation environment for int...Greater complexity and interconnectivity across systems embracing electrical power technologies has meant that cyber-security issues have attracted significant attention. In this paper a simulation environment for intrusion detection system in IEC 61850 standard-based substation automation system is provided to test simulated attacks on IEDs （intelligent electronic devices）. Intrusion detection is the process of detecting malicious attacker, so it is an effective and mature security mechanism to protect electrical facility. However, it is not harnessed when securing IEC 61850 automated substation. To prove the detection capability of the system testing environment was developed to analyze and test attacks simulated with different test cases. It shows that the simulation environment works accordingly to various network traffic scenarios and eventually proves the functionality of intrusion detection system to be later deployed in the real IEC 61850 based substation automation system site.展开更多
基金Foundation item： Supported by the National Natural Science Foundation of China under Grant No.61100005.
文摘Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the navigation test of the self-propelled model, the complex environment including various port facilities, navigation facilities, and the ships nearby must be considered carefully, because in this dense environment the impact of sea waves and winds on the model is particularly significant. In order to improve the security of the self-propelled model, this paper introduces the Q learning based on reinforcement learning combined with chaotic ideas for the model＇s collision avoidance, in order to improve the reliability of the local path planning. Simulation and sea test results show that this algorithm is a better solution for collision avoidance of the self navigation model under the interference of sea winds and waves with good adaptability.
文摘Greater complexity and interconnectivity across systems embracing electrical power technologies has meant that cyber-security issues have attracted significant attention. In this paper a simulation environment for intrusion detection system in IEC 61850 standard-based substation automation system is provided to test simulated attacks on IEDs （intelligent electronic devices）. Intrusion detection is the process of detecting malicious attacker, so it is an effective and mature security mechanism to protect electrical facility. However, it is not harnessed when securing IEC 61850 automated substation. To prove the detection capability of the system testing environment was developed to analyze and test attacks simulated with different test cases. It shows that the simulation environment works accordingly to various network traffic scenarios and eventually proves the functionality of intrusion detection system to be later deployed in the real IEC 61850 based substation automation system site.
