196 results about "Event triggered" patented technology

The present invention belongs to the field of smart power grids and power system automation control. Disclosed is a load emergency control method based on a dynamic event triggering mechanism, which method comprises: on the basis of an indicator of safe operation of a system, performing region division on a distribution network; proposing an adaptive load level division method based on user response willingness, and by taking the minimization of the system operation cost of the distribution network as an objective, establishing a precise load control model of the distribution network; and using a dynamic event triggering mechanism to reduce communication between substations and a master station of the distribution network, so as to realize effective exchange and precise execution of load control policy information. The method of the present invention can precisely realize precise control of a load, and can effectively alleviate communication transmission pressure of a distribution network, thereby ensuring the stability of a power grid and the continuous supply of critical loads.

The invention relates to the technical field of power system control, solves the problems of network attack, limited bandwidth and transmission delay of a power system in a signal transmission process and conservative DET parameter selection and controller design, and particularly relates to a power system dynamic event triggered load frequency control method under Dos attack and random delay. Comprising obtaining a continuous time system parameter matrix; setting an event triggering threshold function; state parameters facing Dos attack and random time delay conditions are set; constructing a state feedback controller; and collaborative design optimization is carried out by applying a GA optimization algorithm. Compared with a traditional control method, the method has the advantages that on the premise of ensuring the stability of the system, by optimizing event triggering conditions, the communication requirement and bandwidth occupation are remarkably reduced, the utilization efficiency of communication resources is improved, network congestion and delay possibly caused by frequent communication are reduced, and the service life of the system is prolonged. And the operation efficiency of the whole power system is improved.

According to the continuous self-adaptive integral sliding mode leader-following multi-robot affine formation control method based on the event triggering mechanism, distributed control and affine formation strategies are fused, a formation controller with high maneuverability and high robustness is constructed, the event triggering mechanism is introduced to reduce the communication load and the control frequency, and the control efficiency is improved. The method belongs to the technical field of multi-robot intelligent cooperative control. Aiming at the common problem of insufficient formation rigidity and flexibility in a multi-robot formation control task, the invention provides a cooperative control method capable of realizing various affine transformations such as zooming, rotating, shearing, coplanar and collinear, and the cooperative control method has good environmental adaptability and system performance.

The invention discloses an intelligent automobile double-event trigger control method aiming at double communication networks. The method comprises the following steps: initializing; establishing intelligence to judge whether an SC event triggering condition and a CA event triggering condition are met or not; solving a front wheel steering angle control instruction; and performing intelligent automobile double-event trigger control. According to the invention, a double-event trigger condition is designed to determine whether a state signal of an intelligent automobile path tracking type 1 fuzzy model is updated to a type 1 fuzzy time-lag controller or not and determine whether a front wheel steering angle control instruction calculated by the type 1 fuzzy time-lag controller is updated to an actuator module or not; communication resources of double communication networks are effectively saved; the method has the capability of efficiently avoiding the problem of communication congestion, can save a lot of communication resources, and improves the reliability of the intelligent automobile in the path tracking control process. The fuzzy time-delay controller is designed to calculate a front wheel steering angle control instruction, and the reliability of path tracking control of the intelligent automobile is ensured.

The invention relates to the technical field of cooperative control, in particular to an adaptive event triggering fixed time consistency control method for a multi-agent system, which comprises the following steps of: S1, constructing a nonlinear high-order multi-agent system mathematical model with uncertain dynamics; s2, constructing a Lyapunov function containing an uncertain parameter lower bound based on coordinate transformation; s3, designing an adaptive event trigger controller with a positive bounded function by using a backstepping control method, wherein the adaptive event trigger controller comprises a virtual controller, an adaptive law and an event trigger mechanism; and S4, through stability analysis, it is proved that the high-order nonlinear multi-agent with the uncertain dynamic state can achieve actual fixed time output consistency, Zeno behaviors are avoided, and the self-adaptive event triggering fixed time consistency control method of the multi-agent system has the advantages of being high in practicability and easy to popularize. The problem of actual fixed time output consistency of a high-order nonlinear multi-agent system is solved, and an existing actual fixed time output consistency result is popularized.

The invention provides a multi-agent self-triggering control method and system, each agent calculates a next triggering moment according to the information of the current moment and the information of an upstream neighbor agent, the calculated triggering moment is taken as a pre-triggering moment, and if other upstream neighbors are triggered before the pre-triggering moment, the other upstream neighbors are triggered before the pre-triggering moment. If yes, updating and calculating the pre-triggering moment, and otherwise, performing triggering control on the intelligent agent by taking the current pre-triggering moment as the triggering time; an event trigger parameter and a time trigger parameter are fused in the calculation process of the trigger moment. According to the method, the advantages of event triggering and time triggering are combined, communication and calculation in a specified mode only need to be carried out at the triggering moment, continuous communication and calculation are not needed, the communication efficiency is improved, the system stability is improved, and the energy consumption ratio is reduced.

The invention provides a motion control method of a coupled output limited Mecanum wheel trolley based on a neural network and event triggering, a storage medium, equipment and a computer program product. The motion control method comprises the following steps: adopting a conversion matrix of Mecanum wheels; establishing a dynamic model of the Mecanum wheel trolley; decoupling the coupling output limitation, and converting the coupling output limitation into time-varying non-coupling limitation; improving the design of a sliding mode surface by adopting an error conversion function and a barrier function, and constructing a sliding mode controller of a trolley with limited coupling output; constructing a neural network controller; introducing an event triggering mechanism, and constructing a neural network sliding mode controller for the coupled output limited trolley based on the neural network and sliding mode control; and verifying the stability of the designed controller. According to the invention, the trajectory tracking problem of the Mecanum wheel trolley with limited coupling output based on the neural network and event triggering is solved.

The invention provides a heterogeneous multi-agent system control method under a DoS attack based on an event triggering strategy. Robust cooperative control under a complex attack environment is realized through the following steps: S1, performing state description and topological structure modeling on a heterogeneous multi-agent system; s2, carrying out approximation on an unknown nonlinear function in the system; s3, restraining the error dynamic state through a performance function, and ensuring that the system response meets the preset precision; s4, designing a time-varying threshold function, and dynamically adjusting a trigger condition to reduce communication burden; s5, designing an anti-attack controller in combination with event triggering and a Lyapunov theory; s6, designing an adaptive law to carry out online estimation on disturbance; and S7, testing synchronization precision, communication efficiency and anti-attack performance based on a physical platform. According to the method, deep fusion of the event triggering mechanism and the preset performance constraint is realized for the first time, and the self-adaptive dynamic threshold strategy is introduced, so that malicious interference of DoS attacks on a communication link is effectively dealt with, and it is ensured that the heterogeneous nodes can still meet preset performance indexes in an attack scene.

The invention discloses a classification and grading alarm system based on multi-source data, relates to the technical field of industrial safety and workplace monitoring, and can solve the typical problems that in the prior art, alarm logic is rigid and single, data sources are static and isolated, an intelligent alarm verification mechanism is lacked, and intelligent analysis and management processes are separated. Through multi-source sensing equipment, an edge-cloud cooperative computing architecture, a multi-source event triggering engine, an innovative classification and grading alarm engine and an AI large model rechecking mechanism, event automatic handling measure execution and alarm information distribution are realized through an automatic linkage and notification subsystem; and finally, event closed-loop is completed by the event handling and closed-loop platform, so that efficient, accurate and automatic monitoring, alarming and closed-loop management of industrial and various working place security events are realized.

The invention discloses an event-triggered unmanned underwater vehicle model prediction control method, which can effectively reduce the calculation cost while ensuring the trajectory tracking performance by executing the motion and path planning of a UUV (Unmanned Underwater Vehicle) at different frequencies. When a trajectory tracking error reaches a preset threshold value or the UUV approaches a target trajectory end point, the system triggers generation of a new reference trajectory, so that the adaptability of path tracking is improved. According to the event triggering MPC algorithm, kinematics and dynamics models of the UUV are combined, it is ensured that a controller can accurately track a feasible reference trajectory, and therefore the gap between motion planning and control is effectively bridged.

The invention provides a self-adaptive fixed time tracking control method based on event triggering, which is used for solving the technical problem that a virtual control law is easy to generate singularity in the traditional backstepping method design. The method comprises the following steps: establishing a mathematical model of a non-strict feedback nonlinear system with input time delay, and introducing an auxiliary system to counteract delay influence; an error dynamic system is obtained through coordinate transformation; according to system fixed time convergence, designing a piecewise function, introducing a backstepping method to design a controller and an adaptive law, using an RBFNN to approach an unknown function therein, designing a virtual control signal corresponding to each error signal, and obtaining an actual controller and an adaptive law; according to the actual self-adaptive controller, event triggering conditions are designed, when the event triggering moment is reached, the event triggering conditions containing input are triggered, and information transmission and response are carried out. An event triggering mechanism is designed, the number of times of control instruction transmission is reduced, communication resources are saved, and rapid convergence and safe operation of the system state are achieved.

The invention discloses a multi-agent sliding mode safety control method based on dynamic event triggering under hybrid network attack, and the control method comprises the following steps: building a multi-agent system model comprising spoofing attack and DoS attack; in order to cope with hybrid network attacks, an integral sliding mode surface function is constructed, an online estimation method is provided, and an unknown network attack mode can be estimated in real time in the absence of prior information; a novel self-adaptive sliding mode controller is developed, and the accessibility of a preset sliding mode surface is ensured; by introducing an auxiliary variable, a dynamic and static event triggering mechanism in the framework is considered, so that the use of communication resources is minimized; a Lyapunov stability theory and a finite time method are utilized to analyze the convergence of the multi-agent system under the control strategy. According to the control method provided by the invention, the influence of spoofing attack and DoS attack on the system can be eliminated, so that the state of the multi-agent system is consistent within finite time.

The invention relates to a bridge crane game model-free optimal control method based on event triggering, and the method comprises the steps: collecting a state vector of a bridge crane in real time, and building a nonlinear multi-player system model of the bridge crane; estimating an unknown dynamic function and an input gain matrix on line in the input identifier neural network; according to an event triggering mechanism, whether triggering is conducted or not is judged based on the error between the current state vector and the state vector of the recently-triggered sampling; if so, triggering a dynamic updating instruction; under a non-zero sum game framework, obtaining an optimal value function gradient based on an estimation result and a current state vector through a self-adaptive evaluator network, and generating an event triggering optimal control law of each player based on a sampled state vector; and the event triggering optimal control law is processed by a zero-order retainer and then is output as a physical driving signal to control the operation of the bridge crane. Compared with the prior art, the method has the advantages of high applicability, high disturbance resistance, high accuracy and the like.

The invention discloses a wind power generation system model prediction control method and device based on event triggering. The method comprises the following steps: establishing a wind power generation system model; based on the wind power generation system model, whether an event triggering mechanism is activated or not is judged according to the deviation between the current state and the target state of the system and the maximum sampling interval time; designing an LMPC algorithm based on event triggering: if an event triggering mechanism is activated, solving an optimization problem in a finite time domain to obtain an optimal control sequence of the system, and fusing Lyapunov function constraint to ensure the closed-loop stability of the system; wherein the optimization problem takes a minimum weighted sum of a system output tracking error and a control input variable quantity as a target; and deploying the LMPC algorithm based on event triggering into a control device of the wind power generation system so as to realize optimal control of the wind power generation system. The stability and robustness of the wind power generation control system can be effectively improved.

The invention discloses a double-event triggering model prediction control method and system for a multi-working-condition industrial system, and the method comprises the steps: enabling a working condition change trigger to judge whether a new working condition occurs in the industrial system or not according to the data in an identification data buffer, and triggering the online updating of a prediction model if the new working condition occurs in the industrial system; the disturbance trigger judges whether a disturbance event triggering condition is achieved or not according to the data in the identification data buffer, and if the disturbance event triggering condition is achieved, optimization solution of the optimization controller is triggered; the optimization controller calculates a control sequence required by the industrial system in a next period of time based on the current prediction model; the control sequence buffer is used for storing the control sequence and the prediction output generated by the optimization controller. According to the method, the control precision can be improved, and meanwhile, the computing resource overhead is greatly saved.

The invention discloses an event-triggered asynchronous hybrid control method for metal rolling, and belongs to the technical field of metal rolling and networked control. The method comprises the steps that a Roesser type two-dimensional system model is constructed based on a mathematical model in the metal rolling process; a two-dimensional event triggering transmission mechanism depended on by a detection mode is introduced into the network control system; designing an asynchronous controller, and constructing a two-dimensional Markov closed-loop system based on the controller; based on a Lyapunov direct method and a Schur complementary method, a non-linear matrix inequality form is adopted, a random stability criterion of a two-dimensional Markov closed-loop system is proposed, and it is ensured that the criterion meets H (infinity) / L2-L (infinity) mixed performance requirements; and optimizing the criterion, and designing a state feedback controller based on the optimized criterion. According to the method, the random stability of the metal rolling process can be ensured, the burden of a communication channel can be effectively relieved, and the problem of mode mismatching between a controlled object and a controller is solved.

The invention discloses a microgrid power quality optimization control method and device based on an event trigger mechanism, and the method comprises the steps: 1, generating a sinusoidal voltage through droop control, and solving a bus voltage through virtual impedance control; 2, extracting harmonic current of the power distribution network, and constructing a virtual impedance expression; step 3, constructing a leader-follower distributed controller based on time triggering according to the extracted harmonic current of the power distribution network and the communication network of the micro-grid; and 4, determining a trigger condition of the leader-follower distributed controller, triggering the leader-follower distributed controller when the trigger condition is satisfied, generating virtual impedance, and controlling each inverter to perform distributed cooperative control based on harmonic power equalization. According to the invention, the inverter can be controlled to absorb different harmonic powers, and the electric energy quality of the micro-grid is improved.

The invention provides a high-order multi-agent event triggering predefined time consensus control method under a spoofing attack, which comprises the following steps: modeling the spoofing attack as an unknown bounded nonlinear disturbance signal, and non-linearly coupling the nonlinear disturbance signal with a system state through a time-varying coefficient; through a distributed predefined time state observer, the real state of the agent masked by the attack is estimated in real time through neighborhood information interaction, and an attack signal is separated; dynamically adjusting control parameters through an adaptive law based on observer output and post-attack state difference so as to compensate state deviation caused by the attack; each agent is provided with a local control law, the input of the local control law is an observer estimation state of the agent and a neighbor, an acceleration item is introduced into the control law, and a preset convergence time upper bound is realized through preset parameters; parameters of the control law are updated based on local adjacency information of a Laplacian matrix, and distributed consensus tracking is completed only depending on states of adjacent agents.

The invention relates to the technical field of system consistency cooperative control, in particular to a multi-unmanned aerial vehicle intelligent body system consistency control method, which comprises the following steps of: establishing a multi-unmanned aerial vehicle intelligent body system model; designing a distributed controller, wherein the distributed controller is based on adaptive coupling gain and control gain; a double-event trigger mechanism is constructed and comprises an event trigger mechanism A and an event trigger mechanism B, and the trigger time sequence of the event trigger mechanism B is a subset of the trigger time sequence of the event trigger mechanism A; introducing a time-varying auxiliary function into the double-event triggering mechanism; carrying out stability analysis through a Lyapunov function and an auxiliary function; the method has remarkable advantages in the aspects of communication resource saving, system stability, distributed control, sesame behavior avoidance and the like; by introducing a double-event triggering mechanism, a time-varying auxiliary function and a self-adaptive distributed control law, consumption of communication resources is reduced, stability and consistency of the system are guaranteed, and the method is suitable for various practical application scenes.

This paper proposes a fixed-time formation control method for underactuated underwater vehicles based on an event-triggered mechanism. A virtual AUV is designed to track a leader AUV that only provides position information. An adaptive speed regulation law is also designed for the virtual AUV, enabling the follower AUV to track a reference position via the virtual AUV without requiring the leader's speed information. Furthermore, an event-triggered mechanism is introduced to intelligently trigger the follower AUV's control input. This method designs an adaptive speed regulator for the virtual AUV, transforming the formation control problem into a trajectory generation and tracking problem. An event-triggered mechanism is added to the controller to reduce the number of executions and minimize actuator wear and resource waste. Theoretical analysis demonstrates that all tracking errors in the closed-loop system converge to the neighborhood of the origin within a fixed time. This method has the advantages of low information transmission, low computational complexity, and low energy consumption, making it valuable for implementation in marine engineering.

The invention relates to the field of unmanned vehicle cooperative system control and the field of malicious network attack defense, in particular to a design method for an event triggering mechanism under the condition that a large unmanned vehicle cooperative system faces asynchronous denial of service (DoS) attack and communication resource shortage. Particularly, the invention provides a signal transmission strategy based on a dynamic event triggering mechanism by considering the condition that a signal transmission channel in the unmanned vehicle cooperative system bears asynchronous DoS attacks, and communication resources are saved on the premise of ensuring the performance requirements of the system. A switching method based on a network attack time sequence is designed, and a switching system thought and a Lyapunov stability theory are utilized to obtain a sufficient condition that the attenuation rate of each subsystem of the unmanned vehicle system is consistent with the unmanned vehicle in the system under the asynchronous DoS attack. The invention designs an equivalent attenuation rate method, and discloses a relationship between the maximum attack intensity which can be borne by an unmanned vehicle system and parameters in an event triggering mechanism, so that the method disclosed by the invention can be used for solving the problem in actual application by adjusting design parameters according to an actual network attack environment and a control target. And the response speed and the attack bearing capacity of the system are balanced.

The invention discloses a switching system dynamic quantization control method and device based on event-triggered communication, and the method comprises the steps: building a continuous time switching linear system model for a switching system, and giving a system stability guarantee mechanism; designing a dynamic quantizer for the continuous time switching linear system model, giving a dynamic quantization parameter and a dynamic quantization updating strategy, and cooperatively designing an event triggering mechanism according to a state variable of the system and the dynamic quantization parameter; and designing a switching law according to an event triggering mechanism, and adjusting dynamic quantization parameters of the system to realize stable control of the system. On the premise of ensuring the system performance, the communication frequency and calculation burden of the system can be reduced, the resource utilization efficiency of the system can be improved, the method can be widely applied to the fields of network control systems, industrial automation systems and the like, and an effective solution is provided for solving the control problem of a complex system.

The invention relates to the field of soft-bodied robot control, in particular to a soft-bodied robot trajectory tracking control method based on event triggering model predictive control, which comprises the following steps: step 1, on the basis of a segmented constant curvature hypothesis of a soft-bodied robot, considering system uncertainty including unmodeled dynamics and exogenous disturbance; establishing a software robot dynamic model and converting the software robot dynamic model into a state space model; 2, designing an event triggering model prediction control strategy based on the state space model of the soft robot; 3, a dynamic event trigger threshold value and a dynamic prediction time domain method are introduced to improve the calculation efficiency; 4, the recursion feasibility and closed-loop stability of a control strategy are ensured through parameter design; and 5, performing simulation analysis on the end tracking of the soft robot by applying the designed event triggering model prediction control strategy.

The invention provides a 5G communication optimization method and system of an urban rail transit train operation control system based on event trigger control. The method comprises the following steps: modeling communication interference based on the frequency and duration of the communication interference in the operation of an urban rail transit train to obtain a hybrid system of the communication interference; establishing a hybrid system model of a train group in a random transmission delay scene by combining a preset 5G communication optimization algorithm based on event trigger control based on the hybrid system of communication interference; based on the hybrid system model, a new communication period and a new control strategy are obtained, and train group operation control optimization in a random transmission delay scene is realized. The communication interference model in the 5G communication optimization method based on event trigger control is closer to the actual characteristics of communication interference, the random transmission delay caused by uncertain communication interference is reproduced, and the method is closer to the actual initiation scene.

The invention discloses a multi-mechanical-arm system random predefined time control method based on event triggering, belongs to the technical field of control, is used for time control of a multi-mechanical-arm system, and comprises the steps that a kinetic equation of the multi-mechanical-arm system is introduced, a track error tracking system is introduced, and a consensus error of the multi-mechanical-arm system is obtained; an unknown function in a kinetic equation of the multi-mechanical-arm system is estimated, a virtual control signal, a self-adaption rate and an event triggering mechanism are designed according to a self-adaption backstepping method, and stability analysis is conducted in combination with the Lyapunov stability theory. An event triggering mechanism is adopted at the same time, the updating frequency of the controller is reduced, and consensus errors of the experimental multi-mechanical-arm system can be converged into a small neighborhood within predefined time of 1 s in combination with the consensus errors of the experimental multi-mechanical-arm system.

The invention discloses an energy countercurrent prevention method based on fuzzy control and event trigger control, and the method comprises the following steps: 1, collecting system data, including a photovoltaic inverter and a related ammeter, an energy storage device and a related ammeter, and a main incoming line ammeter; 2, performing fuzzy control based on the current total incoming line power and upper and lower limits, and determining that the system enters an overload mode, a safety mode or an event trigger module; step 3, preventing countercurrent through an event trigger control module, and judging whether event trigger exists or not by integrating minimum trigger interval control judgment: if yes, entering step 4, and if not, entering step 5; otherwise, continuing to maintain the existing state, and skipping the control strategy; 4, dispatching a photovoltaic power generation and energy storage module, and compensating the residual power gap; and 5, recording and updating a system state, and circularly executing the steps. The real-time performance and the like of the anti-reflux control system are guaranteed.

The event triggering robust model prediction control method for the maglev train suspension system comprises the following steps: S1, considering the influence of track irregularity interference, and establishing a mathematical model of the maglev train suspension system interfered by the track irregularity; s2, according to the established mathematical model of the suspension system and the state of the balance point of the suspension system, obtaining a tracking error model of the suspension system; s3, establishing an equivalent linear model, and calculating an equivalent state constraint and a control input constraint; s4, designing an event triggering robust model predictive control strategy by considering the state constraint and the control input constraint; s5, verifying recursive feasibility and system stability of the event-triggered robust model predictive control strategy; according to the method, the influence of track irregularity on the suspension system of the electromagnetic suspension train is eliminated, the suspension precision of the suspension system is improved, and the problems of calculation pressure and communication resource shortage caused by high-frequency control in the suspension control process of the magnetic suspension train are relieved on the basis of ensuring the suspension stability of the magnetic suspension train.

The invention relates to the technical field of event-driven control, in particular to an event-driven control method for a rescue robot, which comprises the following steps of: extracting event triggering conditions, triggering time sequence data and state parameters based on identification and serial number management of various events in a rescue environment; event type classification, spatial region partitioning and triggering probability modeling are carried out in combination with an SPFA algorithm, the corresponding relation between an event and a response state can be accurately mapped in the space-time dimension, the structural expression and state scheduling capability of a complex environment is enhanced, path optimization is carried out in combination with weights, and the path optimization efficiency is improved. Quantitative allocation of response resources and quantitative evaluation of response execution efficiency can be realized, a response path cost model is constructed by adopting a Dijkstra algorithm, and a mapping relation between path suitability and a triggering probability is compared, so that dynamic screening of an optimal path can be realized under an environment constraint condition; and the execution accuracy of the response path and the task completion collaboration are improved.

The invention discloses a circuit system data driving event trigger control method based on a Koopman operator. According to the method, a circuit system linearization method based on the Koopman operator is designed, then a data-based event trigger control method is established, the effectiveness of the proposed method is demonstrated, and the problem of data-driven event trigger control of the circuit system based on the Koopman operator and incapable of modeling is effectively relieved.

The invention discloses a multi-agent cooperative tracking control method based on dual-channel event triggering. The method comprises the following steps: constructing a nonlinear multi-agent system mathematical model with uncertain dynamics; defining a tracking error function and constructing an error system by utilizing coordinate transformation; designing a virtual controller of each order by using a backstepping control method; designing a dual-channel event triggering mechanism, actual controller input and an adaptive law; and performing multi-agent cooperative tracking control according to the designed dual-channel event triggering mechanism and the controller. By adopting the control signal updating and parameter updating control strategy based on the dual-channel event triggering mechanism, unnecessary communication and calculation can be reduced, and the effect of remarkably reducing the burden of communication resources and calculation resources is achieved. By adopting an event triggering mechanism and an extended Hamming code redundant coding technical means, the security protection of control signal transmission can be realized, and the technical effects of improving the anti-attack capability of the system and guaranteeing the data integrity in an open network environment are achieved.