53 results about "Consensus control" patented technology

The invention provides an unmanned aerial vehicle consistency control method based on a Stackelberg-Nash game, and relates to the technical field of multi-agent consistency and game optimization control. The method comprises the following steps: establishing a motion attitude nonlinear dynamic model of each unmanned aerial vehicle in a multi-unmanned aerial vehicle system, and defining a communication network topological relation; constructing a consistency error and a performance index function; the method comprises the following steps: establishing a layered Stackelberg-Nash game mechanism with a plurality of participants; utilizing a Bellman optimality principle to construct a coupling HJB equation to solve an optimization control strategy of the leader and the follower; and constructing a single evaluation network to estimate the optimization control strategy of the leader and the follower in each execution so as to realize an optimization control target. A favorable tool is provided for analyzing a series of control problems of master-slave consistency of multiple unmanned aerial vehicles in the control field, and the reliability of a control system can be enhanced to a certain extent.

The invention relates to an optimal consistency control method for a random multi-agent system with unknown control gain. The optimal consistency control method is suitable for leader following consistency control of the random multi-agent system with unknown control gain. According to the method, the system uncertainty is approximated by constructing a self-adaptive identifier; designing an observer based on a neural network to reconstruct an unknown control gain; a dynamic event triggering mechanism is introduced, an auxiliary dynamic variable and a dynamic threshold parameter are used for reducing the updating frequency of a controller, and communication and energy consumption are reduced; in combination with an act-critic reinforcement learning framework and based on a positive function related to a Bellman residual error, a neural network weight update rate is constructed, an optimal consistency controller is designed, and the algorithm complexity is simplified while the system stability is ensured. The method has high robustness and is suitable for efficient cooperative control of a multi-agent system in a complex environment.

The invention provides a time mark event triggering reinforcement learning multi-agent consistency control method and system, and relates to the technical field of multi-agent cooperative control. Establishing a multi-agent system dynamics model comprising a leader and a plurality of followers on the time mark; based on the state information of the leader and the follower, constructing a tracking error and consistency error dynamic equation between the intelligent agents; a reinforcement learning controller based on a neural network is constructed, and an optimal control strategy and a performance index function are approached; an event triggering mechanism is designed, and the controller is triggered to update only when the local error of the intelligent agent exceeds a dynamic threshold value; by constructing a Lyapunov function on a time scale and solving a linear matrix inequality condition, bounded consistency of the system is ensured, and a Zeno phenomenon is eliminated. Unified modeling and distributed safety control of the time scale multi-agent system in the non-ideal environment are achieved, communication resources are saved, the convergence speed is increased, and the robustness and practicability of the system are enhanced.

The invention provides an adaptive high-performance consistent control method for a multi-agent system under denial of service (DoS) attack, and a sensing unit comprises a state sensing module carried on each agent, obtains body state information in real time, and shares information with other agents through an adjacent communication network; the information is used for error calculation and local control decision, and meanwhile, communication quality and whether interruption occurs are judged, so that the observability and anti-disturbance capability of the system are enhanced; a distributed control unit controller is deployed in each intelligent body, error mapping and performance constraint are carried out, a time-varying performance boundary is constructed, a control law and a self-adaptive estimation law are designed, a communication execution unit is responsible for transmitting a trigger signal, state estimation or control input generated by the controller among the intelligent bodies, intermittent DoS attacks can be tolerated, and the control law and the self-adaptive estimation law are designed. And an automatic retransmission and timeout judgment mechanism is provided, so that reliable transmission of key data is guaranteed. State estimation, performance recovery and efficient communication can be realized in a DoS attack environment.

The invention discloses a consistency control method and system for second-order multi-agent iterative learning and a medium. The method comprises the steps that a second-order nonlinear CMANSs kinetic equation which is composed of N follower bodies and a leader body and has uncertainty disturbance is constructed; constructing a double-layer adaptive iterative learning control input model; controlling an input model based on the double-layer adaptive iterative learning so as to enable the tracking consistency error of the iterative learning of the second-order nonlinear CMANSs kinetic equation within a preset time range to be within a preset range; and on the basis of a Lyapunov function, the tracking consistency error of iterative learning in a preset time range is demonstrated in a preset range. Therefore, the method can control the input model through double-layer adaptive iterative learning, and ensures that the second-order nonlinear CMANSs can still realize robust tracking in an uncertain environment, thereby realizing tracking consistency of the second-order nonlinear CMANSs with uncertain disturbance in finite time.

The invention discloses an anti-attack bipartite consistency control method for a multi-agent system based on differential privacy, and belongs to the technical field of multi-agent control. Comprising the following steps: generating a label of each agent in a pre-constructed multi-agent system according to a random sampling process based on truncated normal distribution; according to the cooperative competition relationship among the agents in the multi-agent system, differentiated noise is injected into the state of each agent, and the noise state of each agent is obtained; sending the label and the noise state of each agent to a neighbor agent, and filtering the neighbor agent in each agent according to a differential privacy mechanism to obtain a safe neighbor agent set and a noise state thereof; and according to the security neighbor agent set, calculating anti-attack bipartite consistency control input of each agent, updating the state of each agent, and obtaining an anti-attack bipartite consistency control result. According to the method, the privacy protection level can be adjusted according to different conditions while differential privacy is guaranteed.

Systems and methods for performing calibration and calculating consensus inputs in the context of wind farm control (e.g., consensus control of wind turbines) are disclosed herein. A method for calibrating a wind turbine includes receiving internal wind turbine data from a wind turbine, receiving external wind turbine data for the wind turbine from a source external to the wind turbine, comparing the internal wind turbine data to the external wind turbine data, and determining a north offset for the wind turbine based on the comparison of the internal wind turbine data to the external wind turbine data.

The application discloses a method for adaptive secure consensus control of a multi-agent spatio-temporal dynamic system with unknown boundary nonlinearity under hybrid attacks, comprising the following steps: constructing a multi-agent spatio-temporal dynamic system model with unknown boundary nonlinearity and a virtual leader model; establishing a hybrid network attack model containing deception attacks and denial of service (Dos) attacks, and using an adaptive radial basis neural network to approximate the unknown boundary nonlinearity function; defining a consensus error signal to obtain a consensus state error system; designing a composite adaptive neural network secure boundary consensus control scheme, constructing a Lyapunov function for the error system, and obtaining a sufficient condition for the error system to realize mean square secure consensus control. The application effectively solves the problem that the traditional method is difficult to simultaneously cope with complex network attacks and unknown boundary nonlinear disturbances, and significantly improves the security and robustness of the system.

The application discloses a multi-AUV anti-communication noise mean square bounded consensus control method and system, relates to the cooperative control technical field of multi-underwater robot systems, and is based on a discrete linear dynamics model and a state measurement model of the multi-underwater robot system, designs a Kalman filter measurement base state estimator, solves filter gain and error covariance, and acquires optimal state estimation values of each robot; based on the discrete linear dynamics model and communication topology characteristics, a state estimation gain matrix and a coupling strength parameter satisfying topology constraints are solved; and based on the optimal state estimation values, the state estimation gain matrix and the coupling strength parameter, a distributed dynamic output feedback controller is designed, sufficient conditions for the multi-underwater robot system to realize mean square bounded consensus are obtained, the influence of communication packet loss and measurement noise on system consensus control is effectively inhibited, and mean square bounded state convergence of the multi-underwater robot system under a fixed undirected topology is realized.

The present application relates to the field of artificial intelligence and control technology, in particular to a nonlinear multi-agent system fixed-time consensus control method, device and medium. The control method takes the backstepping recursive method as the control design framework, proposes an adaptive fixed-time consensus controller based on an auxiliary compensation system, and solves the nonlinear multi-agent system consensus control problem under time-varying input delay. By providing and changing the control input signal by a person, the multi-agent system motion trajectory can be modified according to the demand. The time-varying input delay and unknown nonlinear function are considered in the system model, making the system more general. Among them, the unknown time-varying delay function is processed by constructing an auxiliary compensation system, and the unknown nonlinear function is processed by using a radial basis function neural network approximation. According to the fixed-time control related lemma, a practical fixed-time adaptive consensus control method is proposed to ensure that the consensus error of the multi-agent system converges to the neighborhood of the origin within a fixed time.

The invention is suitable for the technical field of data communication, and provides a DMA-based leader-containing multi-agent system consistency control method, which comprises the following steps: establishing a leader-containing multi-agent system model and a binary value communication model; performing binary processing on the data in the DDR, storing the data, collecting initial state information of a leader agent and a follower agent, obtaining corresponding sampling data, and storing the corresponding sampling data in the DDR through a DMA controller; the binary state information stored in the DDR is called through the DMA to complete interaction between the information data; obtaining an estimated value of a neighbor state according to a two-set value identification algorithm; and the follower i performs operation by using the estimated value and the state value of the follower i, updates the state of the follower i and stores the updated state information in a DDR (Double Data Rate) through DMA (Direct Memory Access). A DMA (Direct Memory Access) technology is introduced in a data communication process, and the two-set value state information of the nodes is directly and efficiently carried to a system memory from a buffer area, so that the efficient transmission of the state information between the nodes is realized.

The application discloses a kind of group consensus control methods of leader-following nonlinear multi-agent system, comprising: step one: in group multi-agent system, sub-system is divided;Select an agent as leader agent in each sub-system;Step two: each agent is regarded as a mass point obeying single integrator motion model, and the nonlinear dynamics model of each agent in group multi-agent system is established;Step three: the communication connection network between agent is established;Step four: design control protocol and adaptive state observer, initialize each agent state value and state observation value;Step five: the corresponding control protocol is calculated by the current state value of each agent and convergence target, and each agent executes next action;Step six: the adaptive law is calculated using the current state and observation value of agent;Step seven: the state value of each agent after executing action is obtained using state observer.

The invention discloses a self-adjusting predetermined performance consistency control method for a multi-agent system, and the method comprises the steps: building a mathematical model of the multi-agent system, and defining a synchronization error of a follower agent; describing an information interaction relationship among the agents in the multi-agent system based on a graph theory; defining a performance constraint of a synchronization error and a self-adjusting performance boundary function, and introducing a boundary adjusting mechanism with a safety interval detection function to dynamically adapt to disturbance; mapping the synchronization error constrained by the predetermined performance boundary into an unconstrained variable through error conversion and a barrier function; and on the basis of a backstepping method, designing a virtual controller of each order, a final actual controller and an adaptive rate, and realizing cooperative tracking control of the multi-agent system. According to the method, the problems of initial condition feasibility, fixed performance boundary rigid constraint and symmetric performance limitation can be solved, burst interference can be dealt with through a self-regulation mechanism while overshoot, convergence time and steady-state precision are ensured, and the robustness of the system is remarkably improved.

The application provides a two-part consensus control method for a cooperation-competition multi-agent system under a double-constrained autonomous decision DoS attack, introduces an attack energy state, an exposure risk state, an internal decision strength and a DoS attack indication function, establishes a double-constrained autonomous decision DoS attack model, designs a hysteresis switching logic, deduces an attack duration upper bound, a dormancy time lower bound and a unified duty cycle upper bound, designs a distributed state feedback control protocol, and constructs a two-part consensus error system; based on Lyapunov stability analysis, a sufficient condition for the system to realize two-part consensus is established, a distributed state feedback controller gain is solved, and two-part consensus control of the cooperation-competition multi-agent system under the DoS attack is realized. Compared with the prior art, the application can explain the attack start-stop behavior from the evolution of the attacker's internal state, and under the joint constraint of attack energy consumption and exposure risk, the modeling rationality of the attack behavior, the anti-DoS attack ability of the system and the controller engineering implementation are improved.

The application provides a distributed inverse optimal consensus control method and system for a multi-single-arm manipulator, and belongs to the technical field of robot intelligent control; the method comprises the following steps: constructing a state dynamics model of the multi-single-arm manipulator, constructing a consensus error of each follower manipulator according to a communication topological relation of the multi-single-arm manipulator, constructing an asymmetric time-varying preset performance boundary, transforming the error into an unconstrained consensus error through an obstacle type error, and designing a first-step virtual controller and a second-step error variable; adopting an RBF neural network to approximate an unknown comprehensive nonlinear function in the second step and designing an adaptive updating law; decomposing an actual control input into a backstepping compensation item and a terminal inverse optimal item, determining an actual control input of each follower manipulator, and applying the actual control input to the multi-single-arm manipulator. The application can guarantee that signals of a closed-loop system are bounded, make the consensus error satisfy a preset performance constraint, and avoid directly solving an HJB equation.

The application belongs to the field of multi-agent system control, and relates to a finite time consensus control method for a leader-follower multi-agent system, comprising the following steps: constructing a communication topology graph G of the leader-follower multi-agent system; the leader-follower multi-agent system comprises a plurality of followers and a leader; constructing a multi-agent dynamics system; the multi-agent dynamics system comprises a leader dynamics system and a follower dynamics system; performing finite time consensus control on the leader-follower multi-agent system by using a traction control method based on the communication topology graph G and the multi-agent dynamics system; in the traction control, the topological condition is relaxed, the traction control gain is corrected according to the neighbor communication gain, the follower obtains its control input through the information of the neighbor follower, the probability convergence is ensured even if part of the followers cannot indirectly obtain the leader information, the anti-interference ability is enhanced, the convergence speed is improved, and the communication resource consumption is reduced.

The application relates to the technical field of agent consistency control, and proposes a multi-agent attack-resistant consistency control method and system based on a double-layer observer, a double-layer observer framework combining an independent virtual twin layer and a network physical layer is constructed, a safe state benchmark is continuously generated by the independent virtual twin layer based on local output, instead of relying on neighbor node interaction information, the Byzantine behavior detection accuracy and the malicious node isolation reliability are improved, the resource consumption caused by continuous communication is reduced through an event-triggered updating mechanism of the network physical layer, and dynamic threshold detection, node classification, communication edge weight updating and cooperative topology reconstruction are combined, Byzantine nodes are isolated from the cooperative topology without pre-knowing the upper bound of the number of attack nodes and without relying on strong robustness topology conditions, so that the elastic consistency tracking of follower nodes to leader nodes is realized in an open network environment, and the system security, control performance and communication efficiency are considered.

This application discloses a multi-agent distributed adaptive dynamic dual-event triggered consensus control method and system, belonging to the field of multi-agent system control technology. It includes online approximation of unknown nonlinear terms using a radial basis function neural network and constructing a disturbance observer to estimate composite uncertainties, providing an achievable disturbance estimation signal for control compensation. Furthermore, it recursively designs virtual control and adaptive laws within a dynamic surface control framework, avoids derivative explosion in backstep design using a first-order filter, and combines constraint potential functions to handle state constraints, ensuring the boundedness of the closed-loop signal. It constructs control update trigger times and communication reporting trigger times separately, and designs trigger functions based on the errors of the two branches to reduce the control update and communication overhead of the networked system.

This invention provides a finite-time consistency control method for multi-manipulator systems with output constraints. Addressing the cooperative control problem of multi-manipulator systems with model uncertainties, external disturbances, and output constraints, this invention proposes a finite-time convergent adaptive control strategy based on a backstepping design framework, combined with an event-triggered mechanism and a fuzzy logic system. First, a dynamic model of the follower manipulator is established, and the synchronization state error is defined. Second, a cascaded Lyapunov function is designed to handle the output constraints, and the fuzzy logic system is used to approximate the model uncertainties. Third, an event-triggered mechanism is constructed to save communication resources, and control and adaptive laws are designed based on finite-time convergence theory. Simulation results show that the proposed method enables multiple manipulators to achieve high-precision trajectory tracking consistency within a finite time, with the tracking error strictly controlled within a minimal range. The control voltage always meets the output constraints, improving system safety and engineering applicability.

The application provides a consistency control method of a discrete time heterogeneous multi-agent system, aiming at the consistency control problem of a first-order and second-order heterogeneous multi-agent system with multiplicative noise, a distributed control protocol under a multiplicative noise environment is provided, under the distributed control protocol, the consistency problem of the heterogeneous multi-agent system is further converted into the stability problem of a discrete time random system with multiplicative noise. Then, a proper Lyapunov function is constructed, a stability analysis method of the equation is provided, for a leader-follower heterogeneous multi-agent system, sufficient conditions of mean square and almost sure consistency are obtained, proper control gains are solved, and the consistency control of the discrete time heterogeneous multi-agent system under the multiplicative noise environment is realized. The application has the beneficial effects that the influence of the measurement information on the multiplicative measurement noise is greatly reduced, and the consistency control of the heterogeneous multi-agent system is realized.

The application discloses a kind of multi-unmanned aerial vehicle formation event trigger consistency control methods based on neural tangent kernel, comprising the following steps: according to multi-unmanned aerial vehicle cooperative formation scene, linear system dynamics model is established to each unmanned aerial vehicle;According to the linear system dynamics model, introduce neural tangent kernel mechanism, extract the dynamic characteristics of multi-unmanned aerial vehicle;Based on the neural tangent kernel mechanism, design adaptive event trigger function, determine whether to trigger the information interaction and control update between unmanned aerial vehicles;According to the result of information interaction and control update, the parameter of adaptive event trigger mechanism is dynamically adjusted, and the allocation of communication resources between multi-unmanned aerial vehicles is optimized;According to the optimized parameter, adaptive event trigger mechanism is fused with multi-unmanned aerial vehicle consistency control protocol, and the formation control of multi-unmanned aerial vehicle is realized.The application can solve the key problems such as communication bottleneck and system robustness faced by multi-unmanned aerial vehicle formation control in actual industrial scene, and has significant technological progress.

This invention relates to a fault-tolerant binary consensus control method for a fixed-time heterogeneous multi-UAV system. The method includes establishing a dynamic model of the multi-UAV system and a topology diagram of UAV communication symbols; designing a distributed adaptive fixed-time observer to estimate the system matrix, state vector, and upper bound of the leader UAV's control input; designing time-varying gain and disturbance compensation terms to construct a fixed-time fault-tolerant cooperative controller and solve for the control input of the following UAVs; and designing the parameters of the distributed adaptive fixed-time observer and the fixed-time fault-tolerant cooperative controller. This invention ensures that the system achieves consensus quickly and robustly even under conditions of information localization, actuator failure, and unknown input disturbances, significantly improving the reliability and practicality of heterogeneous multi-agent systems in complex real-world environments.

This invention relates to the field of multi-agent control technology and discloses a multi-agent dynamic event-triggered fixed-time binary consensus control method. The method includes constructing a signed undirected topological graph, Laplace matrix, and mathematical model of the multi-agent system to determine the binary consensus control objective; establishing a binary consensus controller, sampling the event triggering speed of each agent and inputting it into the controller, further obtaining measurement error, event triggering function, and dynamic event triggering threshold to determine the dynamic triggering conditions; and calculating the fixed convergence time upper limit of the multi-agent dynamic event-triggered binary consensus controller, ensuring that the multi-agent system can achieve binary consensus within a fixed time under any initial state. The controller designed in this invention can achieve binary consensus among multiple agents, making it applicable not only to multi-agent cooperative scenarios but also to multi-agent competitive scenarios, thus having a wider range of applications.

The invention relates to a hybrid vehicle group consistency control method considering a heterogeneous spacing strategy and delay compensation under a digital twin network, and belongs to the field of intelligent vehicles and intelligent traffic. According to the method, a mixed traffic scene including various heterogeneous vehicles is considered, a mixed vehicle group information flow topological structure is designed, and a mixed vehicle group is divided into a plurality of subgroups; designing a space strategy between heterogeneous vehicles in the hybrid vehicle group, and respectively establishing a network-connected automatic vehicle model, an automatic driving vehicle model and an improved traditional person driving vehicle model in the hybrid vehicle group; and constructing a digital twinborn body for each heterogeneous vehicle in the hybrid vehicle group, forming a digital twinborn body of the subgroup by the digital twinborn bodies corresponding to the heterogeneous vehicles in the same subgroup, and establishing a hybrid vehicle group cooperative consistency control strategy based on a time delay compensation mechanism under a digital twinborn network. According to the method, the consistent stability of cooperative driving between the sub-groups and between the heterogeneous vehicles in the sub-groups can be ensured, and the heterogeneous vehicles can be ensured to quickly track different expected vehicle distances.

The invention relates to a system (1) for controlling a field device (2), wherein the system (1) comprises a server pool (6) comprising servers for operating instances of a virtual control application; the system (1) comprises a network proxy device (23), configured to receive a status update message from the field device (2), comprising status data, and to send replicated status update messages comprising the status data to each instance of the virtual control application assigned to the field device (2); the network proxy device (23) is configured to receive respective control response messages of each of the instances of the virtual control application and to perform a consensus-based decision making procedure to evaluate consensus control data based on the control data provided by the instances of the virtual control application and to send a control response message comprising the consensus control data to the field device (2).

The application discloses a kind of event trigger control-based heterogeneous multi-agent system consistency control method, the heterogeneous multi-agent system contains m first-order multi-agent, N-m second-order multi-agent, communication is carried out through weighted undirected network;First, according to the convergence of the heterogeneous multi-agent system to consistency, the position of agent converges to the average value of position, and the speed converges to 0, define the average value of position convergence;Then the consistency problem of the heterogeneous multi-agent system is converted into a stability problem, and the consistency control of the heterogeneous multi-agent system is realized by piecewise control input rate and event trigger control.The application combines the event trigger control of combined measurement method, inherits the consistency of first-order second-order heterogeneous multi-agent system, reduces the loss of communication resources.The condition of matrix Q is that its minimum singular value is greater than 0, to reduce the conservativeness of event trigger condition.

The invention relates to the technical field of unmanned aerial vehicle cluster cooperative control, and discloses an unmanned aerial vehicle cluster hierarchical disturbance control compliance consistency control method based on data driving, and the method comprises the following steps: S101, building a dynamic model of a multi-unmanned aerial vehicle cluster system under the action of multi-source disturbance; s102, designing a preset time distributed observer to estimate the state information of the leader; s103, designing an unknown nonlinear term in a projection-based parameter estimator estimation system; s104, constructing a preset time nonlinear interference observer for unmeasurable interference; and S105, designing a disturbance control compliant switching controller based on data driving. According to the method, active control and reasonable utilization of interference are achieved, the safety and dynamic performance of the system are remarkably improved while high-precision consistency is guaranteed, the energy consumption of the system is effectively reduced by restraining unnecessary track correction, actuator saturation and structural damage are avoided, and the reliability of the system is improved. Therefore, the efficiency and economy of collaborative operation of the multi-unmanned aerial vehicle cluster are comprehensively improved.

The application discloses a kind of under DoS attack based on dynamic event triggering's spacecraft formation system's self-adapting consistency control method.The method is first based on multi-agent consistency model theory, establishes the multi-agent system model of multi-agent spacecraft formation system, then consider based on time series DoS attack, by the frequency and duration of DoS attack are analyzed and researched, to solve the consistency problem of multi-agent spacecraft formation under DoS attack, then design a dynamic event triggering mechanism to reduce communication transmission frequency, and it is proved that there is no Zeno behavior existence, finally based on Lyapunov stability theory analysis, design a kind of event triggered distributed adaptive controller, solve the consistency problem of multi-spacecraft formation.The method is applied to multi-spacecraft formation system, guarantee the normal operation of system under DoS attack.

This invention relates to the field of distributed multi-agent research technology and discloses a design method for a dynamic event-driven consensus protocol under a switching topology, comprising the following steps: S1, constructing the agent network structure and dynamic equations of the multi-agent network using Markov functions; S2, establishing an event-triggered mechanism for communication between agents; S3, constructing a Brownian motion model of measurement errors; S4, constructing a consensus control protocol for the multi-agent network under a Markov switching topology. This design method for a dynamic event-driven consensus protocol under a switching topology, when considering the random dynamics of topology switching, allows some followers to obtain the leader's state information and exchange information with their neighbors, coordinating control to suppress noise and achieve state consistency with the leader. A novel dynamic event-triggered control mechanism is used to determine the communication frequency between nodes, establish appropriate communication timing, avoid communication congestion, and thus save energy.

The invention relates to the technical field of unmanned surface vessel control, in particular to a distributed safety consistency control method for an unmanned surface vessel, and the method comprises the steps: obtaining system model parameter information; constructing a state observer of the RBFNNs based on the system model parameter information; unavailable state information during the DoS attack period is reconstructed based on the state observer of the RBFNNs; unavailable state information in the DoS attack period is reconstructed based on a state observer of the RBFNNs, a distributed fixed-time adaptive controller based on a backstepping method is determined, and an unknown nonlinear function is processed online for dynamic compensation; introducing an adaptive event triggering controller based on the distributed fixed time adaptive controller, and determining an event triggering condition; based on the Lyapunov theory, it is verified that the system state error can converge to a small neighborhood near a zero point within fixed time under DoS attack, and the convergence speed of the system is improved under the condition that safety consistency is guaranteed.