CN115550359B - Event driven communication and robust control method based on heterogeneous multi-agent system - Google Patents
Event driven communication and robust control method based on heterogeneous multi-agent system Download PDFInfo
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Abstract
The embodiment of the invention provides an event-driven communication and robust control method of a heterogeneous multi-agent system, and relates to the technical field of distributed control of the multi-agent system. The method comprises the steps of distributing a virtual agent for each agent, achieving state consistency through an event-driven communication mechanism, constructing a tracking controller with robustness to bounded disturbance, enabling each agent to track the state of the virtual agent distributed corresponding to the virtual agent through the tracking controller, judging whether all isomorphic virtual agents achieve state consistency, enabling all the agents to achieve state tracking with the virtual agent distributed corresponding to each agent, and enabling the heterogeneous multi-agent system to achieve state synchronization. According to the invention, the heterogeneous multi-agent system with different kinetic model parameters and initial states achieves state synchronization through local information interaction, avoids a complicated controller parameter adjusting process, has strong usability, and has good expandability and plug-and-play characteristics.
Description
Technical Field
The invention relates to the technical field of distributed control of multi-agent systems, in particular to an event-driven communication and robust control method based on a heterogeneous multi-agent system.
Background
In recent decades, multi-agent cooperative control has become a hot point of research in the field of domestic and foreign control, and has wide application in the aspects of automatic driving vehicle formation running, air-ground cooperative combat, tactical missile cooperative burst prevention, multi-robot cooperative task allocation and the like. The event-driven communication mechanism is a communication strategy for triggering data transmission based on the occurrence of an event, and has extremely important application value in a scene with limited bandwidth. The problem of ad hoc network with underwater unmanned ships as communication relays is a problem of multi-agent cooperative control in a typical bandwidth-limited scene. The unmanned ship can replace human beings to complete various dangerous tasks such as hydrologic data acquisition, anti-diving, mine-hunting, communication relay, anti-intelligence reconnaissance and the like. Since the transmission distance of radio waves in sea water can generally reach only 100m under water, the acoustic waves are the best medium-long-distance transmission carrier under water. However, the absorption attenuation of seawater to sound waves rises along with the frequency index, so that the bandwidth of underwater acoustic communication is narrow, the communication rate is low, and the bit error rate is high. The frequency band of the underwater communication sonar of U.S. submarine equipment in the 60 th century is only in the range of 1.45-3.1 kHz. Therefore, when the number of unmanned submarines is excessive and the ocean noise is large, the challenge of completing high-quality data transmission service is large. In the cooperative control of multiple unmanned boats, compared with the traditional periodic transmission mechanism, the event-driven communication mechanism can effectively reduce the data transmission times, and accords with the characteristics of low bandwidth and low transmission rate of underwater acoustic communication.
In the research of multi-agent event-driven distributed control, literature B.Cheng and Z.Li,Fully Distributed Event-Triggered Protocols for Linear Multiagent Networks,IEEE Transactions on Automatic Control,vol.64,no.4,pp.1655-1662,April 2019. proposes a completely distributed event-driven control protocol for an isomorphic multi-agent system under an undirected communication topology structure, and does not need to rely on structural information of a global communication topology. Subsequently, document B.Cheng and Z.Li,Designing Fully Distributed Adaptive Event-Triggered Controllers for Networked Linear Systems With Matched Uncertainties,IEEE Transactions on Neural Networks and Learning Systems. presents a design approach for a robust event-driven control protocol for homogeneous multi-agent systems in the presence of bounded disturbances in the control channel. Literature Y.Qian,L.Liu and G.Feng,Distributed Dynamic Event-Triggered Control for Cooperative Output Regulation of Linear Multiagent Systems,IEEE Transactions on Cybernetics,vol.50,no.7,pp.3023-3032,July 2020. explores the event-triggered consistency problem of undirected heterogeneous multi-agent systems, using dynamic compensation mechanisms to design control laws, balancing the differences between different agent kinetic models. These works all deal with the multi-agent system event-driven control problem in duplex communication mode, and there is no efficient and easy engineering solution to the heterogeneous multi-agent system event-driven distributed control problem in simplex communication mode.
Based on the technical problems, the applicant provides a technical scheme of the application.
Disclosure of Invention
The invention aims to provide an event-driven communication and robust control method based on a heterogeneous multi-agent system, wherein a virtual agent is distributed to each agent in an event-driven communication mode, the state difference between the current time of the virtual agent and the last communication time is calculated, when the state difference exceeds a threshold value attenuating with time, the virtual agent transmits data to the neighbor agents, otherwise, the neighbor agents adopt open-loop prediction states of the virtual agents to construct a distributed control law, and the state difference between each agent and the corresponding virtual agent is converged in a field related to disturbance upper bound by a robust state tracking controller aiming at bounded disturbance in a robust tracking control mode.
The invention provides an event-driven communication and robust control method based on a heterogeneous multi-agent system, which comprises the steps of correspondingly distributing a virtual agent for each agent in the heterogeneous multi-agent system, enabling all the virtual agents to have the same model parameters, enabling each agent to achieve state consistency through an event-driven communication mechanism, constructing a tracking controller with robustness for bounded disturbance, enabling each agent to conduct state tracking on the virtual agent correspondingly distributed through the tracking controller, judging whether all the virtual agents with the same structure achieve state consistency, and enabling all the virtual agents to achieve state tracking with the virtual agent correspondingly distributed by each agent, so that the heterogeneous multi-agent system achieves state synchronization.
In the embodiment of the invention, compared with other similar technologies, the event-driven communication and robust control method of the heterogeneous multi-agent system has the characteristics of good expandability and plug and play, when a new agent is added or the communication topology is changed, the control law of other agents is not required to be redesigned, the self-adaptive coefficient is used for adjusting and adapting to different types of communication topological structures, and the global state synchronization can be ensured. In addition, the event-driven communication and robust control method of the heterogeneous multi-agent system can be used for a general directional communication topological structure with connectivity, the communication mode among all agents is unnecessary to be duplex communication, the practicability is high, the communication mechanism and control law design are simple, the complicated controller parameter adjusting process is avoided, and the usability is high.
In one embodiment, the event-driven communication mechanism refers to that when a data transmission event occurs, the state of the virtual agent allocated correspondingly to the neighbor of the agent is transmitted by the agent, when the data transmission event does not occur, no data transmission occurs, state prediction is performed by the virtual agent corresponding to the neighbor of the agent, the obtained predicted state value replaces the real-time state of the virtual agent, and only when the predicted state value exceeds an error threshold value, the data transmission event is triggered.
In one embodiment, the heterogeneous multi-agent system is set as a multi-agent system consisting of N agents and having connectivity, wherein the connectivity is that all agents are communicated by a channel consisting of one or more channels at any moment, and the channels are simplex channels or duplex channels.
In one embodiment, a virtual navigator is set outside the N agents, and a dynamics model of the virtual navigator is as follows:
Wherein, Representing a state vector of the virtual pilot at the time t, A 0 representing an initial system matrix of the virtual pilot, x 0 (t) representing an initial state vector of the virtual pilot at the time t, B 0 representing an initial input matrix of the virtual pilot, and u 0 (t) representing an initial control signal of the virtual pilot at the time t;
the kinetic model of the intelligent agent is as follows:
Wherein, Representing the derivative of the state vector of the ith agent with respect to time at t, A i representing the system matrix of the ith agent, x i (t) representing the state vector of the ith agent at t, B i representing the input matrix of the ith agent, u i (t) representing the control signal of the ith agent at t, I I.I. representing the Euclidean norm of the vector, omega i (t) representing the bounded disturbance of the ith agent during control execution at t, eta i >0 being the upper limit of the bounded disturbance.
In one embodiment, after one virtual pilot is set outside the N agents, the matrix licark equation is solved to obtain the positive definite matrix P 0:
wherein I is an identity matrix;
Each agent is assigned a virtual agent, and the system matrix of all virtual agents is consistent with the pilot and evolves according to the following dynamics model:
Wherein, Representing a derivative of a state vector of an ith virtual agent with respect to time at a time t, ζ i (t) represents a state vector of the ith virtual agent with respect to time t, ζ j (t) represents a state vector of a neighbor agent j of the ith agent with respect to time t, a ij represents a connection relationship between the i and the j neighbor agent, and if the j neighbor agent transmits the state vector ζ j (t) to the i, a ij =1, otherwise a ij＝0,cij (t) represents an adaptive coefficient between the i and the j, subject to the following evolution law:
Wherein, Representing the derivative of the adaptive coefficient with respect to time at time t, ρ i j representing the adjustable parameter between agent i and agent j,
Ζ i(t)-ζj(t)||2 represents the square of the euclidean norm of the virtual state difference of the i-th virtual agent and the virtual agent j;
The self-adaptive coefficient c ij (t) adjusts the growth rate according to the virtual state difference between two agents which are neighbors to each other, and stops growing when the two agents which are neighbors to each other keep synchronous, and the initial value c ij(0)≥0,ρij is more than 0.
In one embodiment, the state trajectory of the virtual pilot provides tracking targets for all virtual agents that remain synchronized with the pilot state under conditions that only utilize the virtual state of neighbors;
Setting the moment when the virtual agent sends real-time virtual state to the neighbor thereof as I.e. the transmission time of the kth data of the ith virtual agent;
The virtual agent checks the difference between the current virtual state and the virtual state at the previous transmission time in a fixed period Whether a dynamic threshold for decay over time is exceeded;
If it is
The virtual intelligent agent i sends a virtual state zeta i (t) to the neighbor of the virtual intelligent agent i, namely a data transmission event occurs, wherein mu >0, lambda >0 and tau >0 are all adjustable parameters, and the curve shape of the dynamic threshold is adjusted according to the adjustable parameters;
On the contrary, if
The data transmission event does not occur, i.e. the virtual agent does not send real-time virtual state to its neighbor, which generates the prediction information of the virtual agent i by using the virtual state at the last transmission timeI.e.
Wherein, Is thatState transition matrix of (a).
In one embodiment, the number and distribution of transmission event occurrences may be adjusted by changing a threshold curve, increasing the threshold may reduce the total number of event occurrences, and decreasing the threshold may increase the total number of event occurrences;
The state difference e (t) = [ e 1(t) … eN(t)]T ] between the virtual agent and the pilot will converge to a neighborhood related to the pilot input, i.e
ei(t)＝ζi(t)-x0(t);
Where lambda max(P0) and lambda min(P0) are the maximum and minimum eigenvalues of matrix P 0, respectively.
In one embodiment, the robust coefficient epsilon is set according to the magnitude of the disturbance amplitude of the bounded disturbance, so that excessive fluctuation of the system state caused by the disturbance is reduced, epsilon is reduced if the disturbance amplitude is larger, and epsilon is increased otherwise.
In one embodiment, the matrix licark equation is solved to obtain the positive definite matrix P i:
wherein, I is an identity matrix, A i is a system matrix of the ith agent, and B i is an input matrix of the ith agent;
searching a matrix L i, and meeting the following conditions:
Ai+BiLi＝A0;
A robust control law for agent i can be obtained:
u i (t) can complete state consistency between the virtual agent and the pilot and state tracking of the agent and the virtual agent, finally realize state synchronization of the heterogeneous multi-agent system, and tracking performance is related to a robust coefficient and a disturbance upper bound, namely:
Where t f is the total time period to achieve consistency.
Drawings
FIG. 1 is a flow chart of a method for event-driven communication and robust control based on a heterogeneous multi-agent system in accordance with a first embodiment of the present invention;
FIG. 2 is a diagram of a communication topology of multiple agents in the present invention;
FIG. 3 is a schematic diagram of the displacement of each agent under an event driven mechanism;
FIG. 4 is a schematic diagram of individual agent accelerations under an event driven mechanism;
FIG. 5 is a schematic diagram of individual agent speeds under an event driven mechanism;
FIG. 6 is a schematic diagram of the receipt time of each agent under an event driven mechanism;
FIG. 7 is a schematic diagram of individual agent accelerations under non-robust control;
fig. 8 is a schematic diagram of the speeds of the respective agents in the periodic transmission mechanism.
Detailed Description
The following detailed description of various embodiments of the present invention will be provided in connection with the accompanying drawings to provide a clearer understanding of the objects, features and advantages of the present invention. It should be understood that the embodiments shown in the drawings are not intended to limit the scope of the invention, but rather are merely illustrative of the true spirit of the invention.
In the following description, for the purposes of explanation of various disclosed embodiments, certain specific details are set forth in order to provide a thorough understanding of the various disclosed embodiments. One skilled in the relevant art will recognize, however, that an embodiment may be practiced without one or more of the specific details. In other instances, well-known devices, structures, and techniques associated with the present application may not be shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.
Throughout the specification and claims, unless the context requires otherwise, the word "comprise" and variations such as "comprises" and "comprising" will be understood to be open-ended, meaning of inclusion, i.e. to be interpreted to mean "including, but not limited to.
Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
As used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. It should be noted that the term "or" is generally employed in its sense including "or/and" unless the context clearly dictates otherwise.
In the following description, for the purposes of clarity of presentation of the structure and manner of operation of the present invention, the description will be made with the aid of directional terms, but such terms as "forward," "rearward," "left," "right," "outward," "inner," "outward," "inward," "upper," "lower," etc. are to be construed as convenience, and are not to be limiting.
A first embodiment of the present invention relates to an event-driven communication and robust control method based on a heterogeneous multi-agent system, as shown in fig. 1, comprising the steps of:
Step 101, correspondingly distributing a virtual agent for each agent in a heterogeneous multi-agent system, so that all the virtual agents have the same model parameters, and enabling each agent to reach a consistent state through an event-driven communication mechanism;
102, constructing a tracking controller with robustness to bounded disturbance, and enabling each intelligent agent to carry out state tracking on virtual intelligent agents correspondingly distributed to each intelligent agent through the tracking controller;
Step 103, judging whether the virtual intelligent agents with all isomorphic states are consistent, if so, continuing to step 104, and if not, repeating step 102;
and 104, judging that all the intelligent agents and the virtual intelligent agents correspondingly distributed to each intelligent agent realize state tracking, if the state tracking is realized, achieving state synchronization for the heterogeneous multi-intelligent-agent system, ending all the steps, and otherwise, repeatedly entering the step 102.
The event-driven communication mechanism is that when a data transmission event occurs, the state of the virtual agent correspondingly allocated to the neighbor of the agent is transmitted by the agent, when the data transmission event does not occur, no data transmission occurs, state prediction is performed by the virtual agent corresponding to the neighbor of the agent, the obtained predicted state value replaces the real-time state of the virtual agent, and only when the predicted state value exceeds an error threshold value, the data transmission event is triggered. That is, when an event occurs, the agent transmits the state of its own virtual agent to its neighbors, and when an event does not occur, no data transmission occurs, and neighbors replace real-time states with predicted states of their own virtual agents.
In one example, the heterogeneous multi-agent system is set as a multi-agent system composed of N agents and having connectivity, wherein the connectivity is that all agents are communicated by a channel composed of one or more channels at any moment, and the channels are simplex channels or duplex channels.
As shown in fig. 2, in the communication topology of the heterogeneous multi-agent system, L ij represents the difference in desired positions between agents, and the states of the agents are displacement, velocity, and acceleration, respectively, i.e., x i(t)＝[si vi ai]T. The agent i transmits status information only to the immediately following agent j and maintains a certain distance L ij therefrom.
Setting a virtual pilot outside the N intelligent agents, wherein the dynamic model of the virtual pilot is as follows:
Wherein, Representing a state vector of the virtual pilot at the time t, A 0 representing an initial system matrix of the virtual pilot, x 0 (t) representing an initial state vector of the virtual pilot at the time t, B 0 representing an initial input matrix of the virtual pilot, and u 0 (t) representing an initial control signal of the virtual pilot at the time t;
the kinetic model of the intelligent agent is as follows:
Wherein, Representing the derivative of the state vector of the ith agent with respect to time at t, A i representing the system matrix of the ith agent, x i (t) representing the state vector of the ith agent at t, B i representing the input matrix of the ith agent, u i (t) representing the control signal of the ith agent at t, I I.I. representing the Euclidean norm of the vector, omega i (t) representing the bounded disturbance of the ith agent during control execution at t, eta i >0 being the upper limit of the bounded disturbance.
After a virtual pilot is set outside the N agents, solving a matrix Li-Card equation to obtain a positive definite matrix P 0:
wherein I is an identity matrix;
Each agent is assigned a virtual agent, and the system matrix of all virtual agents is consistent with the pilot and evolves according to the following dynamics model:
Wherein, Representing a derivative of a state vector of an ith virtual agent with respect to time at a time t, ζ i (t) represents a state vector of the ith virtual agent with respect to time t, ζ j (t) represents a state vector of a neighbor agent j of the ith agent with respect to time t, a ij represents a connection relationship between the i and the j neighbor agent, and if the j neighbor agent transmits the state vector ζ j (t) to the i, a ij =1, otherwise a ij＝0,cij (t) represents an adaptive coefficient between the i and the j, subject to the following evolution law:
Wherein, Representing the derivative of the adaptive coefficient with respect to time at time t, ρ ij representing the adjustable parameter between agent i and agent j,
Ζ i(t)-ζj(t)||2 represents the square of the euclidean norm of the virtual state difference of the i-th virtual agent and the virtual agent j;
The self-adaptive coefficient c ij (t) adjusts the growth rate according to the virtual state difference between two agents which are neighbors to each other, and stops growing when the two agents which are neighbors to each other keep synchronous, and the initial value c ij(0)≥0,ρij is more than 0.
The state track of the virtual navigator provides tracking targets for all virtual agents, and the all virtual agents keep synchronous with the state of the navigator under the condition that only the virtual states of neighbors can be utilized;
Setting the moment when the virtual agent sends real-time virtual state to the neighbor thereof as I.e. the transmission time of the kth data of the ith virtual agent;
The virtual agent checks the difference between the current virtual state and the virtual state at the previous transmission time in a fixed period Whether a dynamic threshold for decay over time is exceeded;
If it is
The method includes that the difference between the virtual state at the current moment and the virtual state at the last sending moment is large, if the virtual intelligent agent does not send the virtual state to the neighbor of the virtual intelligent agent in time, the virtual intelligent agent of the neighbor of the virtual intelligent agent is difficult to achieve state synchronization with the virtual intelligent agent of the virtual intelligent agent, and at the moment, the virtual intelligent agent i sends a virtual state zeta i (t) to the neighbor of the virtual intelligent agent i, namely a data transmission event occurs, wherein mu >0, lambda >0 and tau >0 are all adjustable parameters, and the curve shape of the dynamic threshold is adjusted according to the adjustable parameters;
On the contrary, if
The data transmission event does not occur, i.e. the virtual agent does not send real-time virtual state to its neighbor, which generates the prediction information of the virtual agent i by using the virtual state at the last transmission timeI.e.
Wherein, Is thatState transition matrix of (a).
In one embodiment, the number and distribution of transmission event occurrences may be adjusted by changing a threshold curve, increasing the threshold may reduce the total number of event occurrences, and decreasing the threshold may increase the total number of event occurrences;
The state difference e (t) = [ e 1(t) … eN(t)]T ] between the virtual agent and the pilot will converge to a neighborhood related to the pilot input, i.e
ei(t)＝ζi(t)-x0(t);
Where lambda max(P0) and lambda min(P0) are the maximum and minimum eigenvalues of matrix P 0, respectively.
In one embodiment, the robust coefficient epsilon is set according to the magnitude of the disturbance amplitude of the bounded disturbance, so that excessive fluctuation of the system state caused by the disturbance is reduced, epsilon is reduced if the disturbance amplitude is larger, and epsilon is increased otherwise.
In one embodiment, the matrix licark equation is solved to obtain the positive definite matrix P i:
wherein, I is an identity matrix, A i is a system matrix of the ith agent, and B i is an input matrix of the ith agent;
searching a matrix L i, and meeting the following conditions:
Ai+BiLi＝A0;
A robust control law for agent i can be obtained:
u i (t) can complete state consistency between the virtual agent and the pilot and state tracking of the agent and the virtual agent, finally realize state synchronization of the heterogeneous multi-agent system, and tracking performance is related to a robust coefficient and a disturbance upper bound, namely:
Where t f is the total time period to achieve consistency.
A tracking controller, which is robust to bounded perturbations, causes each agent to track its assigned virtual agent. When the states of all isomorphic virtual agents are consistent and all agents realize the state tracking of the self virtual agents, the states of the heterogeneous multi-agent system are synchronous.
The following describes the implementation effect of the present invention by means of specific examples, and a longitudinal dynamics model of the vehicle is selected as a model of each agent:
Wherein, n=4, τ 0＝0.5,τ1＝0.5882,τ2＝0.4348,τ3 =0.4;
The initial state x1＝[2020]T,x2＝[150.50.6]T,x3＝[8 0.3 0.3]T,x4＝[2 0.5 0.2]T; of each agent is L ij =7, the adaptive parameter c ij(0)＝2,k21＝0.1,κ32＝0.01,κ43 =0.01, the adjustable parameter between each agent is ρ 21＝0.1,ρ32＝0.01,ρ43 =0.01, other adjustable parameters, such as μ=0.2, λ=0.001, τ=0.05, the bounded disturbance is η i =1, the robust coefficient is ε=0.2, and the fixed check period t=0.05 s of the set event.
The total number of times that the virtual pilot agent 0 and its follower agent 1-2 send status to their trailing agents 1-3 is 66s, 70s and 70s, respectively. Under the traditional periodic transmission strategy, 300 data are required to be sent within 15s to complete the task of multi-vehicle state synchronization. Thus, the method can save more than 75% of transmission times compared with a periodic transmission strategy. As shown in fig. 4, the solid black line represents the acceleration trace of the virtual pilot, and it can be seen that the bounded disturbance on the control-execution system causes the acceleration signal to shake, the acceleration curve is not smooth, and the acceleration distribution at each moment is discontinuous. As can be seen from fig. 3 and 5, the multi-agent system eventually achieves synchronization with pilot speed and acceleration, and maintains a certain formation. As can be seen from fig. 5, the distribution of transmission timings under the event-driven communication mechanism is not uniform on the time axis, which is a clear difference from the periodic transmission mechanism. As can be seen from a comparison of the acceleration curves of fig. 4 and 7, without introducing a robust control, the acceleration jitter amplitude will be larger than if a robust control was introduced. As can be seen from comparison of the speed curves of fig. 5 and fig. 8, the control effect is not significantly reduced after the event-driven mechanism is introduced, and the event-driven communication mechanism can greatly reduce the communication time between the intelligent agents on the premise of ensuring similar control performance, compared with the conventional periodic transmission mechanism.
While the preferred embodiments of the present invention have been described in detail above, it should be understood that aspects of the embodiments can be modified, if necessary, to employ aspects, features and concepts of the various patents, applications and publications to provide yet further embodiments.
These and other changes can be made to the embodiments in light of the above detailed description. In general, in the claims, the terms used should not be construed to be limited to the specific embodiments disclosed in the specification and the claims, but should be construed to include all possible embodiments along with the full scope of equivalents to which such claims are entitled.
Claims (8)
1. An event-driven communication and robust control method based on a heterogeneous multi-agent system, comprising the steps of:
Distributing a virtual agent to each agent in the heterogeneous multi-agent system correspondingly, so that all the virtual agents have the same model parameters, and enabling each agent to reach a consistent state through an event-driven communication mechanism;
Constructing a tracking controller with robustness to bounded disturbance, and enabling each intelligent agent to carry out state tracking on virtual intelligent agents correspondingly distributed to each intelligent agent through the tracking controller;
judging whether all isomorphic virtual agents reach the state consistency, and if all the virtual agents are in state tracking with the virtual agents correspondingly distributed by each agent, synchronizing the states of the heterogeneous multi-agent system;
The event-driven communication mechanism is that when a data transmission event occurs, the state of the virtual agent correspondingly allocated to the neighbor of the agent is transmitted by the agent, when the data transmission event does not occur, no data transmission occurs, state prediction is performed by the virtual agent corresponding to the neighbor of the agent, the obtained predicted state value replaces the real-time state of the virtual agent, and only when the predicted state value exceeds an error threshold value, the data transmission event is triggered.
2. The method for event-driven communication and robust control based on heterogeneous multi-agent system according to claim 1, wherein the heterogeneous multi-agent system is configured as a multi-agent system comprising N agents with connectivity, wherein the connectivity is that all agents are connected by a path comprising one or more channels at any time, and the channels are simplex channels or duplex channels.
3. The heterogeneous multi-agent system-based event-driven communication and robust control method of claim 2, wherein a virtual pilot is set outside the N agents, and a dynamics model of the virtual pilot is:
Wherein, Representing a state vector of the virtual pilot at the time t, A 0 representing an initial system matrix of the virtual pilot, x 0 (t) representing an initial state vector of the virtual pilot at the time t, B 0 representing an initial input matrix of the virtual pilot, and u 0 (t) representing an initial control signal of the virtual pilot at the time t;
the kinetic model of the intelligent agent is as follows: ||ωi(t)||≤ηi,1≤i≤N;
Wherein, Representing the derivative of the state vector of the ith agent with respect to time at t, A i representing the system matrix of the ith agent, x i (t) representing the state vector of the ith agent at t, B i representing the input matrix of the ith agent, u i (t) representing the control signal of the ith agent at t, I I.I. representing the Euclidean norm of the vector, omega i (t) representing the bounded disturbance of the ith agent during control execution at t, eta i >0 being the upper limit of the bounded disturbance.
4. The heterogeneous multi-agent system-based event-driven communication and robust control method of claim 3, wherein after a virtual pilot is set outside the N agents, solving a matrix licarpa's equation to obtain a positive definite matrix P 0:
wherein I is an identity matrix;
Each agent is assigned a virtual agent, and the system matrix of all virtual agents is consistent with the pilot and evolves according to the following dynamics model:
Wherein, Representing a derivative of a state vector of an ith virtual agent with respect to time at a time t, ζ i (t) represents a state vector of the ith virtual agent with respect to time t, ζ j (t) represents a state vector of a neighbor agent j of the ith agent with respect to time t, a ij represents a connection relationship between the i and the j neighbor agent, and if the j neighbor agent transmits the state vector ζ j (t) to the i, a ij =1, otherwise a ij＝0,cij (t) represents an adaptive coefficient between the i and the j, subject to the following evolution law:
Wherein, Representing the derivative of the adaptive coefficient with respect to time at time t, ρij represents an adjustable parameter between agent i and agent j,
Ζ i(t)-ζj(t)||2 represents the square of the euclidean norm of the virtual state difference of the i-th virtual agent and the virtual agent j;
The self-adaptive coefficient c ij (t) adjusts the growth rate according to the virtual state difference between two agents which are neighbors to each other, and stops growing when the two agents which are neighbors to each other keep synchronous, and the initial value c ij(0)≥0,ρij is more than 0.
5. The method for event-driven communication and robust control based on a heterogeneous multi-agent system of claim 4,
The state track of the virtual navigator provides tracking targets for all virtual agents, and the all virtual agents keep synchronous with the state of the navigator under the condition that only the virtual states of neighbors can be utilized;
Setting the moment when the virtual agent sends real-time virtual state to the neighbor thereof as I.e. the transmission time of the kth data of the ith virtual agent;
The virtual agent checks the difference between the current virtual state and the virtual state at the previous transmission time in a fixed period Whether a dynamic threshold for decay over time is exceeded;
If it is
The virtual intelligent agent i sends a virtual state zeta i (t) to the neighbor of the virtual intelligent agent i, namely a data transmission event occurs, wherein mu >0, lambda >0 and tau >0 are all adjustable parameters, and the curve shape of the dynamic threshold is adjusted according to the adjustable parameters;
On the contrary, if
The data transmission event does not occur, i.e. the virtual agent does not send real-time virtual state to its neighbor, which generates the prediction information of the virtual agent i by using the virtual state at the last transmission timeI.e.
Wherein, Is thatState transition matrix of (a).
6. The heterogeneous multi-agent system based event driven communication and robust control method of claim 5, wherein the number and distribution of transmission event occurrences can be adjusted by changing a threshold curve, wherein increasing the threshold reduces the total number of event occurrences, and wherein decreasing the threshold increases the total number of event occurrences;
The state difference e (t) = [ e 1(t)…eN(t)]T ] between the virtual agent and the pilot will converge to a neighborhood related to the pilot input, i.e
ei(t)＝ζi(t)-x0(t);
Where lambda max(P0) and lambda min(P0) are the maximum and minimum eigenvalues of matrix P 0, respectively.
7. The method for event-driven communication and robust control based on heterogeneous multi-agent system according to claim 5, wherein the robust coefficient epsilon is set according to the magnitude of the disturbance amplitude of the bounded disturbance, so as to reduce excessive fluctuation of the system state caused by the disturbance, and if the disturbance amplitude is larger, epsilon is reduced, otherwise epsilon is increased.
8. The heterogeneous multi-agent system-based event-driven communication and robust control method of claim 7, wherein solving a matrix licarpi equation yields a positive definite matrix P i:
wherein, I is an identity matrix, A i is a system matrix of the ith agent, and B i is an input matrix of the ith agent;
searching a matrix L i, and meeting the following conditions:
Ai+BiLi＝A0;
A robust control law for agent i can be obtained:
u i (t) can complete state consistency between the virtual agent and the pilot and state tracking of the agent and the virtual agent, finally realize state synchronization of the heterogeneous multi-agent system, and tracking performance is related to a robust coefficient and a disturbance upper bound, namely:
Where t f is the total time period to achieve consistency.
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