Research On Nonlinear System Based On Event Triggering And Network Attack

In recent decades,due to the advantages of Neural Networks(NNs)in self-adaptation and anti-interference,the successful applications in the fields of rainfall forecasting,pattern recognition,and optimization systems have aroused the research interest of scholars,and have affected all walks of life.For the nonlinear system studied in this article,it is a networked control systems(NCSs)composed of sensors,controllers,actuators and networks.Due to communication redundancy,bandwidth waste and various external attacks,the stability of the system is affected.This is a huge security hazard to the country and people's property security.Countries around the world are gradually paying attention to these issues and looking for solution.Therefore,it is necessary to design a suitable controller to stabilize neural networks and nonlinear systems.First of all,there are many unresolved problems within the network control system.Aiming at the problem of network congestion caused by bandwidth,how to make full use of the load of network bandwidth and reduce the transmission of redundant data,which greatly improves the transmission efficiency and performance of the system.Due to the delay of the neural network and the communication delay between the various devices in the system,the impact on the system performance cannot be underestimated,and how to minimize its harm is very important.Secondly,in addition to the internal problems of the network control system itself,the most harmful external factor is the cyber attacks.There are various forms of cyber attacks,and the most serious ones are deception attacks and denial of service(Do S).For cyber attacks,how to design a targeted controller so that the control system can still maintain good robustness has important practical significance.In view of the above situation and the various difficulties faced,this paper designs a reasonable controller to solve the above problems.The expanded content is as follows:(1)The discrete event trigger scheme is embedded in the control system.Each sensor in the system determines the locally transmitted signal by the discrete trigger scheme.The transmission of redundant data is greatly reduced,and the update parameters of the neural network decrease at the same time.The random cyber attack is modeled as a kind of nonlinear function,and the network reliability is guaranteed.Combining the above methods to reconstruct the control system,using Lyapunov-Krasovskii Function(LKF),Jenson inequality,etc.to verify the stability of the system.(2)In view of the cumulative dynamic cyber attack scenarios,reconstruct the random attack function,not only propose an integral function that satisfies the constraint conditions,but also reduce its constraint,consider a variety of time incentives,and add multiple time delays to the system,and then apply non-linear processing technology and other means to prove the stability of the controller.(3)Combining the characteristics of event trigger mechanism error,the trigger scheme is reconstructed,and a closed-loop control system is established based on the adaptive event trigger mechanism and two types of random cyber attack functions.With the introduction of random parameters,cyber attacks can occur at any time and switch to each other.Under the consideration of multiple delays and adaptive conditions,an enhanced LKF is constructed,and the control theory is verified in conjunction with the turbine system.