Research on Distributed Cooperative Control Strategy of Microgrid Hybrid Energy Storage Based on Adaptive Event Triggering

Distributed collaborative control strategies for microgrids often use periodic time to trigger communication,which is likely to enhance the burden of communication and increase the frequency of controller updates,leading to greater waste of communication resources.In response to this problem,a distributed cooperative control strategy triggered by an adaptive event is proposed.By introducing an adaptive event triggering mechanism in the distributed controller,the triggering parameters are dynamically adjusted so that the distributed controller can communicate only at a certain time,the communication pressure is reduced,and the DC bus voltage deviation is effectively reduced,at the same time,the accuracy of power distribution is improved.The MATLAB/Simulink modeling and simulation results prove the correctness and effectiveness of the proposed control strategy.

ICPS multi-target constrained comprehensive security control based on DoS attacks energy grading detection and compensation

Aiming at the industry cyber-physical system(ICPS)where Denial-of-Service(DoS)attacks and actuator failure coexist,the integrated security control problem of ICPS under multi-objective constraints was studied.First,from the perspective of the defender,according to the differential impact of the system under DoS attacks of different energies,the DoS attacks energy grading detection standard was formulated,and the ICPS comprehensive security control framework was constructed.Secondly,a security transmission strategy based on event triggering was designed.Under the DoS attack energy classification detection mechanism,for large-energy attacks,the method based on time series analysis was considered to predict and compensate for lost data.Therefore,on the basis of passive and elastic response to small energy attacks,the active defense capability against DoS attacks was increased.Then by introducing the conecomplement linearization algorithm,the calculation methods of the state and fault estimation observer and the integrated safety controller were deduced,the goal of DoS attack active and passive hybrid intrusion tolerance and actuator failure active fault tolerance were realized.Finally,a simulation example of a four-capacity water tank system was given to verify the validity of the obtained conclusions.

Observer-based event-triggered networked multi-drives speed consensus

The problem of having an identical speed when dealing with multiple motors always exists in the industry.There are several methods to address the problem,but all the methodologies have two common drawbacks.Firstly,the control design requires continuous information on the desired speed and the actual speed of motors;secondly,it is sometimes difficult to directly measure the speed variables.In the proposed study,both of these drawbacks are addressed by designing an observer-based event-triggered networked multi-agent system.The proposed method uses the leader following consensus approach with a centralized event triggering control design so that whenever a follower's speed diverges from that of the leader,an event is triggered,which communicates and resets all the agents to the leader's speed.Moreover,an observer is designed such that the ith agent uses its jth neighbor agent and observer speed information to estimate the leader's speed.The stability of the proposed design is formulated by Lyapunov stability,while the simulation results endorse the design concepts and energy saving.

Study on control strategy of CAN bus network based on event triggered mode

In order to reduce the load rate of CAN bus and improve the real-time performance of control system, CAN bus control system of a pure electric vehicle is studied. Communication messages of each node are optimized and redefined by sorting the message into three types： control message, status message and alann message. Event triggered mode is added to the communication way of CAN bus, and the communication control strategy of the vehicle is made. It is proved that CAN bus load rate of control system is reduced after optimization, and the real-time performance of communication is improved effectively.

Statistical properties of seismic foreshocks and aftershocks associated with longwall mining:Implications from the Epidemic Type Aftershock Sequence model

The control and management of mining-induced seismic hazards have attracted ever-rising attention,especially in underground longwall coal mines,where continuous mining activities dynamically alter the stress states and induce seismic events.In this work,the Epidemic Type Aftershock Sequence(ETAS)model was applied to formulate the aftershock catalogue of mining-induced seismicity and investigate the formation of event triggering associated with longwall mining.The conventional Baiesi and Paczuski method(2004)was used to separate longwall mining-induced seismic events into triggered and nontriggered catalogues.The latter catalogue contains both non-triggering(NT)-isolated events that do not trigger subsequent events and NT-parent events of the former catalogue.Statistical properties of triggered events were analysed spatially and temporally.The temporal triggering sequence follows the Omori-Utsu law,where the temporal decay of aftershocks is influenced by the magnitude of NT-parent events in mining-induced seismicity.The spatial distribution of aftershocks follows an inverted U-shaped relationship with distance to their corresponding NT-parent events.The quantitative forecasting of triggered events was performed based on the nonhomogeneous Poisson distribution,which achieved a good consistency with their NT-parent events.Amongst the non-triggered catalogue,NT-isolated events are concentrated ahead of NT-parent events,potentially acting as foreshocks for the latter.

Impact of circumferential inlet distortion on different types of stall inceptions in a transonic compressor

The application of higher bypass ratios and lower pressure ratios significantly reduces specific fuel consumption with the development of turbofan engines.However,it also increases the risk of flow separation at the intake,leading to severe circumferential non-uniform inlet conditions.This study aimed to present an experimental investigation on instability evolutions of the compressor under circumferential non-uniform inlet conditions.Two stall inceptions regarding the different spatial scales and initial locations were selected to investigate this issue.The experiments were carried out on one tested rig,which the stall inceptions verified with the rotational speeds.At 65%design rotational speed(X),the stall inception was the spike,which was triggered by disturbances within serval pitches scale at the tip.Consequently,the spike-type stall inception was sensitive to circumferential distortion and led to a shrunk stall margin of the compressor.With the rotational speed increasing to 88%X,the stall inception switched to partial surge,which was induced by the flow blockage in the hub region around the full-annular.The results indicated that the partial surge was insusceptible to the circumferential distortion,which caused an extended stall margin with a lower stalled mass flow rate.In summary,the influence of distortion on the stability of the target compressor was found to be determined by the stall inception.

Event Type Recognition Based on Trigger Expansion

Event extraction is an important research point in information extraction, which includes two important sub-tasks of event type recognition and event argument recognition. This paper describes a method based on automatic expansion of the event triggers for event type recognition. The event triggers are first extended through a thesaurus to enable the extraction of the candidate events and their candidate types. Then, a binary classification method is used to recognize the candidate event types. This method effectively improves the unbalanced data problem in training models and the data sparseness problem with a small corpus. Evaluations on the ACE2005 dataset give a final F-score of 61.24%, which outperforms traditional methods based on pure machine learning.

Event-triggered adaptive finite time trajectory tracking control for an under actuated vessel considering unknown time-varying disturbances

This paper aims to solve the finite-time trajectory tracking problem of underactuated surface ships under the influence of dynamic uncertainty,unknown external time-varying interference and limited communication resources.An event-triggered robust adaptive finite-time trajectory tracking control method for underactuated ships is designed by combining the existing trajectory tracking control methods and engineering needs in actual navigation.It can obviously improve the tracking accuracy of the ship,and complete the tracking task safely and efficiently.This scheme transforms the composite uncertain vector synthesized by uncertain parameters and external disturbances into a linear parameterized form.Next,considering the limitation of communication resources,a relative threshold event triggering mechanism is introduced to further extend the triggering time interval on the basis of the fixed threshold triggering scheme.Then,an event-triggered robust adaptive finite-time trajectory tracking control scheme is designed for underactuated ships,and a rigorous stability proof is provided through Lyapunov stability theory.Simulation experiment is carried out in MATLAB and the results show that the finite-time trajectory tracking control scheme proposed in this paper can effectively solve the problems of dynamic uncertainty.unknown time-varying external interference and limitation of communication resources.This paper can provide theoretical support for the autonomous navigation of intelligent ships.

Interacting multiple model-based ETUKF for efficient state estimation of connected vehicles with V2V communication

Accurate prediction of the motion state of the connected vehicles,especially the preceding vehicle(PV),would effectively improve the decision-making and path planning of intelligent vehicles.The evolution of vehicle-tovehicle(V2V)communication technology makes it possible to exchange data between vehicles.However,since V2V communication has a transmission interval,which will result in the host vehicle not receiving information from the PV within the time interval.Furthermore,V2V communication is a time-triggered system that may occupy more communication bandwidth than required.On the other hand,traditional estimation methods of the PV state based on individual models are usually not applicable to a wide range of driving conditions.To address these issues,an event-triggered unscented Kalman filter(ETUKF)is first employed to estimate the PV state to strike a balance between estimation accuracy and communication cost.Then,an interactive multi-model(IMM)approach is combined with ETUKF to form IMMETUKF to further improve the estimation accuracy and applicability.Finally,simulation experiments under different driving conditions are implemented to verify the effectiveness of IMMETUKF.The test results indicated that the IMMETUKF has high estimation accuracy even when the communication rate is reduced to 14.84%and the proposed algorithm is highly adaptable to different driving conditions.