87 results about "Consensus control" patented technology

The invention discloses a multi-agent cooperative control system based on side event triggering and a method thereof. The method comprises the following steps: establishing each multi-agent optimal cooperative control model; calculating the optimal cooperative control model through a Bellman optimal method and a cost function of each agent to obtain an optimal cooperative control strategy of each agent; constructing an evaluation neural network, and obtaining a cooperative control strategy based on an edge event by using a generalized strategy iterative algorithm; a Lyapunov function based on a local cost function is constructed, and a multi-agent edge event triggering rule is established; the cooperative control strategy based on the edge event and the edge event triggering rule are applied to the multiple agents to solve the cooperative consensus control problem of the multiple agents under the condition that communication is limited; according to the method disclosed by the invention, a good collaborative effect can be ensured, and meanwhile, a side event trigger control protocol is utilized to realize data sampling and control updating of a point-to-point level between nodes, so that the communication loss and calculation burden of multiple agents are effectively reduced.

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 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 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 finite time consistency control method for a high-order all-drive uncertain multi-agent system. The finite time consistency control method comprises the following steps: firstly, constructing a dynamic equation model of the high-order all-drive uncertain non-linear multi-agent system; designing a finite time integral sliding mode surface; according to the established multi-agent system dynamic equation model and the designed finite time integral sliding mode surface, adopting an adaptive control method to estimate unknown parameters of the system, and obtaining an equivalent distributed adaptive finite time integral sliding mode controller; based on a pole assignment method, linear parameters which meet system performance requirements and are involved in a finite time integral sliding mode surface and a corresponding controller are obtained; the designed controller is substituted into a high-order all-drive uncertain nonlinear multi-agent system, and the finite time consistency control target is achieved. The method not only fully reflects the advantages of the high-order all-drive theory in the aspect of nonlinear system control, but also lays an important foundation for the fusion development of the high-order all-drive theory and the traditional control theory.

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 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.

The invention relates to the technical field of unmanned ship formation consistency control, in particular to a finite time self-adaptive adjustment multi-unmanned ship formation consistency control method and system, and the method comprises the steps: defining auxiliary variables according to a dynamic equation, nonlinear dynamic characteristics and external disturbance of each unmanned ship; constructing a finite time consistency control law and an adaptive law according to the auxiliary variables and conditions for realizing bounded consistency of the multi-unmanned ship system; determining a closed-loop error controller according to the position error, the speed error, the finite time consistency control law and the adaptive law; constructing a Lyapunov function according to the auxiliary variable and a closed-loop error controller; the error stability verification of the position and the speed of each unmanned ship is realized through a Lyapunov function; and based on a finite time consistency control law, multi-unmanned ship formation consistency control is realized. The problems of disturbance compensation with more general state related disturbance and finite time formation consistency control are solved.

The application provides a multi-agent system mean square consensus control method under hybrid attack, relates to the technical field of intelligent control, and comprises the following steps: establishing a multi-agent system model, designing a controller, on the basis, constructing an error system between a follower agent and a leader, and establishing a mean square consensus condition of the multi-agent system under a deception attack and a DOS attack, so that the multi-agent system is controlled to realize leader-following mean square consensus. The application improves the control strategy by comprehensively considering the possible deception attack and DOS attack during the working period of the multi-agent system, so that the leader-follower mean square bounded consensus is realized, and the control efficiency and control precision are improved.

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 is applicable to the field of cooperative control of a multi-agent system, realizes self-repairing of a damaged network through network state verification and network topology reconstruction, establishes an autonomous interaction model of an agent based on a dynamic containment strategy, and provides an elastic consistency control method for the multi-agent system under network attack. The method comprises the following steps: determining a multi-agent system model; constructing a state estimation vector of the intelligent agent, determining a relationship between nodes in combination with a maximum consistency method, and verifying a communication network connectivity state; determining the characteristics of the connected components based on the identifiers of the information agents, and enabling the connected components with the information agents to be randomly connected with the connected components without the information agents to realize topology reconstruction; convergence of the constructed observer and the controller is fixed time convergence. According to the method, the conventional cooperative control method is theoretically expanded, so that the dependence on the network connectivity is reduced, and a more complex interaction relationship between the intelligent agents in the dynamic network can be processed.

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 present invention discloses a method for consistency control of multiple robotic arms based on event triggering under limited communication. The method comprises: establishing a multi-robotic arm system model for the multi-robotic arm system based on algebraic graph theory; performing algorithmic control on each robotic arm of the multi-robotic arm system model through a distributed consistency control algorithm; when performing consistency control on each robotic arm, controlling the communication between each robotic arm through a preset event triggering communication protocol; when multiple robotic arms need to send status information, allocating communication channels to the multiple robotic arms through a preset channel scheduling strategy. The technical solution in the embodiment of the present invention improves the utilization rate of the robotic arm communication channel and improves the use of limited channels by designing a channel scheduling strategy based on event triggering under limited channel conditions.

The invention relates to the technical field of bipartite consistency of a multi-agent system, and discloses a bipartite consistency control method of a second-order multi-agent system under a switching topology, which aims at bipartite consistency control without time delay and with communication time delay, considers a second-order multi-agent system consisting of n agents, determining a second-order multi-agent system model and parameters; determining a topological structure of the system under the switching topology according to the second-order multi-agent system model and the parameters thereof; designing a bipartite consistency control protocol of the second-order multi-agent system considering no time delay and communication time delay constraints; and the sufficient condition that the second-order multi-agent system meets the dichotomy consistency under the condition of no time delay and communication time delay in the switching topology is obtained. Compared with the prior art, the problem of dichotomy consistency of the second-order multi-agent system under the conditions of no time delay and communication time delay is solved.

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 invention discloses a fixed-time consensus control method for an unmanned boat with actuator failure. According to the fixed-time consensus control method for an unmanned boat with actuator failure, even if the unmanned boat system is affected by actuator failure, unknown time-varying control gain and external interference, the tracking error of the system can converge to the vicinity of the origin within a fixed time, and the convergence time is independent of the initial state of the system. By targeting the influence of factors such as actuator failure, external interference and time-varying control gain on the unmanned boat system, the system has higher control accuracy. In addition, an event trigger mechanism is designed in the controller to alleviate communication pressure, and a fixed-time consensus controller is designed based on backstepping technology, neural network adaptive control technology and fixed-time stable control theory. Finally, the proposed method is simulated. The simulation results show that it has good tracking accuracy and effectively saves communication resources.

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.

A system for the cryptographically-secure, autonomous control of devices comprising, connected to or remotely operating devices in an electrically powered network and the transaction of the benefits, costs or value created by or transacted through the devices in this electrically powered network.

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 present invention claims protection for a secure grouping consensus control method for heterogeneous unmanned systems under DoS attacks. The cluster control of unmanned systems is a typical application of the consensus collaborative control of multi-agent systems, and the multi-agent system is specifically elaborated in the content of this patent. It includes using matrix knowledge to transform the dynamic models of second-order agents and first-order agents to obtain the dynamic equations of an equivalent homogeneous system; considering that project engineering is generally deployed in an open environment, introducing more complex and variable multi-channel independent DoS attacks to enhance the robustness of the system; introducing an estimator to eliminate the adverse effects brought by multi-channel independent DoS attacks and accelerate the convergence of the system; agents and their estimators need to distinguish the information transmitted by neighbor nodes and process the information separately according to the secure consensus protocol; the control protocol for agent state update additionally considers the case of different state dimensions in heterogeneous systems, which can ensure the ultimate realization of secure grouping consensus of multi-agent systems.

The present invention relates to a method for specified-time cooperative control of a high-order multi-agent system with unknown states, which includes: Step 1, setting the expected total time for bounded consensus arrival as T, setting the precise reconstruction time of the agent state information as D, and satisfying D < T; Step 2, building a specified-time observer for each agent; Step 3, designing a fully distributed edge-based adaptive control protocol; Step 4, obtaining a specified-time consensus control protocol for a fully distributed multi-agent linear system based on the observer. The present invention, aiming at a high-order linear system, introduces a specified-time observer to solve the problem that the agent state information cannot be accurately obtained, and alleviates the rigid demand of the multi-agent system for high-cost sensor and other accessory equipment; introduces an edge-based adaptive control protocol to avoid the need of the control protocol for global information; successfully extends the specified-time consensus control of multi-agents to a high-order linear system, and improves the applicability of the specified-time consensus control scheme.

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.

This invention is applicable to the field of cooperative control of multi-agent systems. It achieves autonomous repair of damaged networks through network state verification and network topology reconstruction, and establishes an autonomous interaction model of agents based on a dynamic restraint strategy. It provides a resilient consistency control method for multi-agent systems under network attacks. The method includes: determining the multi-agent system model; constructing state estimation vectors for agents, confirming relationships between nodes using the maximum consensus method, and verifying the connectivity state of the communication network; determining the characteristics of connected components based on the identifiers of information agents, and randomly connecting connected components with and without information agents to achieve topology reconstruction; the convergence of the constructed observer and controller is fixed-time convergence. This invention theoretically extends existing cooperative control methods, reducing their dependence on network connectivity and enabling them to handle more complex interactions between agents in dynamic networks.