CN108762068A - A kind of multiple agent consistency control method with model uncertainty - Google Patents
A kind of multiple agent consistency control method with model uncertainty Download PDFInfo
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- CN108762068A CN108762068A CN201810423753.1A CN201810423753A CN108762068A CN 108762068 A CN108762068 A CN 108762068A CN 201810423753 A CN201810423753 A CN 201810423753A CN 108762068 A CN108762068 A CN 108762068A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/26—Special purpose or proprietary protocols or architectures
Abstract
The multiple agent consistency control method with model uncertainty that the invention discloses a kind of,Reduce the communication frequency between the calculation processing load of intelligent body processor and multiple agent,Each data traffic is also reduced,Under the communication mechanism that the communication frequency and single data traffic are reduced,Significantly reduce network transport load,Replace original agreement for carrying out approximate calculation hangover state derivative using numerical differentiation,The sampling period appropriate is chosen to ensure the realization of consistency,To improve the stability of system,And it additionally uses in conjunction with self-operating control strategy and the consistency of the self-adjusting control strategy based on model uncertainty controls scheduling scheme,To which effective solution is difficult to carry out in real network application condition or occurs in the prior art the problem of multiple agent Collaborative Control confusion dependent on the multiple agent consistency control mode of real-time continuous information exchange.
Description
Technical field
The present invention relates to MAS control technical field, specifically a kind of multiple agent one with model uncertainty
Cause property control method.
Background technology
In recent years, with many such as computer network, electronic communication, biotechnology, automation control and artificial intelligence
The cross development of section, core of the multi-agent network as distributed system control technology, has increasingly attracted numerous researchers
Concern and great interest.Multi-agent network is the important branch and complex system study of artificial intelligence study
In the highly important direction of one kind.
First, the definition of intelligent body is provided, intelligent body refers to the list for having independent sensor, processor and communication device
A equipment or machine, and there is certain self organization ability, learning ability and inferential capability.Therefore multi-agent system refers to one
A communication network being made of multiple intelligent bodies can be according to the topology of network between each intelligent body in the network model
Rule communicates, to achieve the purpose that cooperation, coordination, scheduling, management and control whole network system.So more
Intelligent volume grid can effectively distributed dynamic changes network-based control problem in the Coping with Reality world, to solving in network
Complexity problem has apparent advantage.Multi-agent network has been widely used in industry, agricultural, national defense and military and daily life
In the middle, and become a kind of effective Method and kit for analyzed complication system, designed and modeled.In conclusion
Cooperating with each other between multiple agent can complete more complicated work with smaller cost, and multi-agent system is in different society
The application of technical field helps to push social development, improves people's quality of life, promote the modernization of variant technical field
Degree.
One core of multi-agent network Collaborative Control studies a question and exactly controls the holding expection of its collective behavior, i.e., and one
Cause property control problem.Consistency control refers to the control to certain group behavior, and in this group, all individuals pass through one
The distributed protocol of part progressively reaches the state expected from one, determining, the initial setting of this behavior and all individuals
Whether value is identical unrelated.The consistency of multiple agent controls in formation control, cluster control, assembles and swarm and jointly control field
It suffers from and is widely applied.With the economic development with science and technology, unmanned aerial vehicle group control, multiple robots formation, wireless sensing network control
All use the modeling of multiple agent thought in system and congestion control etc. field.Wherein, consistency control problem is multiple agent net again
The basal core problem of network control, therefore the consistency control problem for studying multiple agent has great importance.
So far, the information interaction approach inside multi-agent network all relies on status information between each intelligent body mostly
Real-time continuous exchange, realize Time Continuous scheduling intelligence sample and interactive controlling mode.It is continuous with digitalized network
Development, network bandwidth it is ever-expanding simultaneously, on network various terminals node also at geometry situation increase, from save and rationally
From the perspective of Internet resources, the intelligence sample mode of Time Continuous scheduling is less applicable.If multiple agent system
System is run in the state of stablizing steady at one, without sampling, then the intelligence sample of this Time Continuous scheduling and interaction are controlled
The drawbacks of mode processed, is then shown, that is, when the calculation processing resource of waste intelligent body processor, second is that wasting mostly intelligent
The network bandwidth resources communicated between body.
Moreover, existing multi-agent system needs to rely on the consistency control mode of real-time continuous information exchange,
Challenge and difficulty are also encountered in practical applications.Because under many outdoor real network conditions, due to logical by network
Believe the limitation of environment, network communication bandwidth and transmission rate are limited, or even can not carry out effective information biography in part-time section
It is defeated, thus between each intelligent body controller accurate state information value be difficult to realize it is real-time continuous be exchanged with each other, this just leads
The multiple agent consistency control mode dependent on real-time continuous information exchange is caused to be difficult in many real network application conditions
Implement, or the problems such as multiple agent Collaborative Control is chaotic occurs.
Therefore, the consistency control method for how improving multiple agent, it is negative with the calculation processing for reducing intelligent body processor
Lotus mitigates network transport load, under the premise of communicating the frequency between reducing multiple agent, while ensuring multiple agent consistency
The validity of control becomes an important research direction of multiple agent consistency control technology field.
Invention content
The multiple agent consistency control method with model uncertainty that the purpose of the present invention is to provide a kind of, with solution
Certainly the problems mentioned above in the background art.
To achieve the above object, the present invention provides the following technical solutions：
A kind of multiple agent consistency control method with model uncertainty, includes the following steps：
S1 designs a bottom communication frame for capableing of Fusion Model uncertainty mechanism and dynamic codec, to carry more intelligence
Digital channel communication process between energy body controller, and phase is designed according to the bottom communication frame application time lag decomposition technique
The communication of algorithms answered, i.e. the controlling of sampling agreement of the single order multi-agent system consistency with hangover state derivative feedback；
S2 sets the quantification mechanism of communication instruction dynamic codec between MAS control device, to reduce the logical of communication instruction
Occupancy of the letter transmission to communication network bandwidth；
S3 determines that each intelligent body is meeting consistency in the multiple agent controlled according to scheduled consistency control strategy
Self-operating control strategy under control strategy state；
S4, the model uncertainty condition of setting intelligent body triggering communication, is designed full for each intelligent body in multiple agent
The distributed model uncertainty function of sufficient model uncertainty condition and excitation condition, determine that each intelligent body is independent of each other
Model uncertainty time series, and based on the quantification mechanism of communication instruction dynamic codec between MAS control device, if
It is fixed to correspond to the communication instruction sent when triggering communication due to different model uncertainty conditions, so that it is determined that the model of intelligent body is not
Deterministic policy；
S5, for each communication instruction for triggering communication due to each different model uncertainty condition, design disclosure satisfy that
The self-adjusting control strategy of being consistent property control strategy requirement between two neighboring intelligent body；
S6 sets the delay transmission between intelligent body after the interruption of communication network transient state when recovery communication and breakpoint transmission communication equipment
System；
S7, by the communication of algorithms of the bottom communication frame of above-mentioned determination, self-operating control strategy, model uncertainty strategy, from
Control strategy and delay transmission and breakpoint transmission communication mechanism are adjusted by being programmed into each intelligent body control in multiple agent
The control program of device processed, and control each model uncertainty information source of each intelligent body monitoring control devices intelligent body where it
Information change amount.
Compared with prior art, the beneficial effects of the invention are as follows：It is only needed between multiple agent uncertain in generation model
Property when can just occur information communication, reduce between the calculation processing load of intelligent body processor and multiple agent communication frequency
It is secondary, simultaneously because being communicated using digital channel between intelligent body, and is set for communication instruction and reduce what network bandwidth occupied
Dynamic codec quantification mechanism so that each data traffic is also reduced, in the communication frequency and single data traffic
Under the communication mechanism being reduced, network transport load is significantly reduced, substitution is original to carry out approximate meter using numerical differentiation
The agreement for calculating hangover state derivative, chooses the sampling period appropriate to ensure the realization of consistency, to improve the steady of system
It is qualitative, and additionally use in conjunction with self-operating control strategy and the consistency of the self-adjusting control strategy based on model uncertainty
Control scheduling scheme, it can be ensured that realize effective multiple agent consistency control, in the prior art to effective solution
Multiple agent consistency control mode dependent on real-time continuous information exchange be difficult to carry out in real network application condition or
There is the problem of multiple agent Collaborative Control confusion.
Specific implementation mode
The following is a clear and complete description of the technical scheme in the embodiments of the invention, it is clear that described embodiment
Only a part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, the common skill in this field
The every other embodiment that art personnel are obtained without making creative work belongs to the model that the present invention protects
It encloses.
In the embodiment of the present invention, a kind of multiple agent consistency control method with model uncertainty, including it is following
Step：
S1 designs a bottom communication frame for capableing of Fusion Model uncertainty mechanism and dynamic codec, to carry more intelligence
Digital channel communication process between energy body controller, and phase is designed according to the bottom communication frame application time lag decomposition technique
The communication of algorithms answered, i.e. the controlling of sampling agreement of the single order multi-agent system consistency with hangover state derivative feedback；
Currently, for the research of complication system collaboration and consistency control problem, focuses on and how to have improved digital communications network
Service efficiency on come.Under real network condition, due to limitations such as network communication bandwidth and transmission rates, intelligent body sensor
Between accurate state information value be difficult to be exchanged with each other in real time, the transmission of analog signal is during practical communication in addition
It is easy to be interfered, therefore analog signal just must first be converted into digital signal when communication channel is transmitted, and believes with simulation
It number compares, digital signal can reduce occupancy of the amount of communication data to network bandwidth, so needing to design by quantifying and encoding
One bottom communication frame for capableing of Fusion Model uncertainty mechanism and dynamic codec carries the information in digital channel
Communication process, and the corresponding communication of algorithms is gone out according to the bottom communication Frame Design.
S2 sets the quantification mechanism of communication instruction dynamic codec between MAS control device, to reduce communication instruction
Communications to the occupancy of communication network bandwidth；
In real figure network, the load capacity of equipment is limited, therefore it is particularly significant to develop suitable quantification mechanism
, it avoids excessively quantifying, saves the valuable communication resource.Therefore it needs to study quantization, coding, decoding and delay etc. situations such as
Under multiple agent digital network reach the inherent mechanism of consistency, propose a set of effective quantification mechanism, it is appropriate to determine
Quantizing factor is reasonably quantified, so that saving valuable network bandwidth to the full extent.
S3 determines that each intelligent body is meeting one in the multiple agent controlled according to scheduled consistency control strategy
Self-operating control strategy under cause property control strategy state；
According to corresponding bottom communication frame and scheduled consistency control strategy, the model of setting intelligent body triggering communication is not
Certainty condition, and the distributed model uncertainty function of reasonable design and excitation condition, determine that intelligent body is independent of each other
Model uncertainty time series, using its neighbours' intelligent body in the information of respective model uncertainty moment point, design is accordingly
Control strategy, find multi-agent network and reach the adequate condition of consistency, and it also requires formulating multiple agent in non-mould
Self-operating control strategy under type uncertainty state, and then the communication frequency between multiple agent is reduced, mitigate network transmission
Load, makes net-work control performance being optimal as far as possible.
S4, the model uncertainty condition of setting intelligent body triggering communication, sets for each intelligent body in multiple agent
Meter meets the distributed model uncertainty function and excitation condition of model uncertainty condition, determines that each intelligent body is only each other
Vertical model uncertainty time series, and based on the quantification machine of communication instruction dynamic codec between MAS control device
System sets the communication instruction for corresponding to and sending when triggering communication due to different model uncertainty conditions, so that it is determined that intelligent body
Model uncertainty strategy；
S5, for each communication instruction for triggering communication due to each different model uncertainty condition, design disclosure satisfy that
The self-adjusting control strategy of being consistent property control strategy requirement between two neighboring intelligent body；
S6 sets the delay transmission between intelligent body after the interruption of communication network transient state when recovery communication and breakpoint transmission communication equipment
System；
S7, by the communication of algorithms of the bottom communication frame of above-mentioned determination, self-operating control strategy, model uncertainty strategy, from
Control strategy and delay transmission and breakpoint transmission communication mechanism are adjusted by being programmed into each intelligent body control in multiple agent
The control program of device processed, and control each model uncertainty information source of each intelligent body monitoring control devices intelligent body where it
Information change amount；
For each intelligent body, in the state that it meets consistency control strategy between other intelligent bodies, if monitoring
The information change or information change amount of its each model uncertainty information source are not up to corresponding model uncertainty condition,
Intelligent body controller then uses self-operating control strategy to control the operating status of intelligent body where it, if monitoring any
The information change amount of model uncertainty information source reaches corresponding model uncertainty condition, then according to model uncertainty plan
The corresponding communication instruction of corresponding model condition of uncertainty slightly is sent to the controller of neighbours' intelligent body, and in the hair of communication instruction
It is taken into account during sending using delay transmission and breakpoint transmission communication mechanism, if intelligent body controller is received from neighbours' intelligent body
Communication instruction is then instructed according to respective communication and is adjusted to the operating status of intelligent body where it according to self-adjusting control strategy
Whole, until with after being consistent property of the neighbours' intelligent body control strategy requirement, intelligent body controller then continues to use self-operating
Control strategy controls the operating status of intelligent body where it；Hereby it is achieved that the consistency control of multiple agent.
The multiple agent consistency control method with model uncertainty only needs between multiple agent that mould is occurring
Information communication can just occur when type uncertainty, reduce between the calculation processing load of intelligent body processor and multiple agent
The frequency is communicated, simultaneously because being communicated using digital channel between intelligent body, and reduction network bandwidth is set for communication instruction
The dynamic codec quantification mechanism of occupancy so that each data traffic is also reduced, in the communication frequency and single data
Under the communication mechanism that the traffic is reduced, network transport load is significantly reduced, substitution is original to be come using numerical differentiation
The agreement of approximate calculation hangover state derivative chooses the sampling period appropriate to ensure the realization of consistency, is to improve
The stability of system, and additionally use in conjunction with self-operating control strategy and the self-adjusting control strategy based on model uncertainty
Consistency controls scheduling scheme, it can be ensured that effective multiple agent consistency control is realized, to which effective solution is existing
Multiple agent consistency control mode in technology dependent on real-time continuous information exchange is difficult in real network application condition
Implement or occur the problem of multiple agent Collaborative Control confusion.
The above are merely the preferred embodiment of the present invention, it is noted that for those skilled in the art, not
Under the premise of being detached from present inventive concept, several modifications and improvements can also be made, these should also be considered as the protection model of the present invention
It encloses, these all do not interfere with the effect and patent practicability that the present invention is implemented.
Claims (1)
1. a kind of multiple agent consistency control method with model uncertainty, which is characterized in that include the following steps：
S1 designs a bottom communication frame for capableing of Fusion Model uncertainty mechanism and dynamic codec, to carry more intelligence
Digital channel communication process between energy body controller, and phase is designed according to the bottom communication frame application time lag decomposition technique
The communication of algorithms answered, i.e. the controlling of sampling agreement of the single order multi-agent system consistency with hangover state derivative feedback；
S2 sets the quantification mechanism of communication instruction dynamic codec between MAS control device, to reduce the logical of communication instruction
Occupancy of the letter transmission to communication network bandwidth；
S3 determines that each intelligent body is meeting consistency in the multiple agent controlled according to scheduled consistency control strategy
Self-operating control strategy under control strategy state；
S4, the model uncertainty condition of setting intelligent body triggering communication, is designed full for each intelligent body in multiple agent
The distributed model uncertainty function of sufficient model uncertainty condition and excitation condition, determine that each intelligent body is independent of each other
Model uncertainty time series, and based on the quantification mechanism of communication instruction dynamic codec between MAS control device, if
It is fixed to correspond to the communication instruction sent when triggering communication due to different model uncertainty conditions, so that it is determined that the model of intelligent body is not
Deterministic policy；
S5, for each communication instruction for triggering communication due to each different model uncertainty condition, design disclosure satisfy that
The self-adjusting control strategy of being consistent property control strategy requirement between two neighboring intelligent body；
S6 sets the delay transmission between intelligent body after the interruption of communication network transient state when recovery communication and breakpoint transmission communication equipment
System；
S7, by the communication of algorithms of the bottom communication frame of above-mentioned determination, self-operating control strategy, model uncertainty strategy, from
Control strategy and delay transmission and breakpoint transmission communication mechanism are adjusted by being programmed into each intelligent body control in multiple agent
The control program of device processed, and control each model uncertainty information source of each intelligent body monitoring control devices intelligent body where it
Information change amount.
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| CN110196554A (en) * | 2019-05-27 | 2019-09-03 | 重庆邮电大学 | A kind of safety compliance control method of multi-agent system |
| CN110308659A (en) * | 2019-08-05 | 2019-10-08 | 沈阳航空航天大学 | Uncertain multi-agent system mixing with time delay and switching topology triggers consistent control method |
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Cited By (5)
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| CN109541944A (en) * | 2018-12-20 | 2019-03-29 | 哈尔滨理工大学 | Discrete networks multi-agent system finite-time control method containing communication delay |
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| CN110308659A (en) * | 2019-08-05 | 2019-10-08 | 沈阳航空航天大学 | Uncertain multi-agent system mixing with time delay and switching topology triggers consistent control method |
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