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Multi-agent distributed model prediction control method and system

A model predictive control, multi-agent system technology, applied in the field of multi-agent systems, can solve the problems of complex stability guarantee methods and high requirements for communication topology, to ensure iterative feasibility, simplify implementation and parameter adjustment. Effect

Active Publication Date: 2021-04-20
HUNAN UNIV
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Problems solved by technology

[0004] There are still many deficiencies in the existing distributed model predictive control methods for multi-agent systems, especially the high requirements for the communication topology, and the stability guarantee method is relatively complicated

Method used

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Embodiment Construction

[0057] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0058] Such as figure 1 As shown, the multi-agent distributed model predictive control method provided by the embodiment of the present invention includes:

[0059] Step 1, describe the dynamic equation of the agent in the multi-agent system (as shown in formula (1)), record the set containing all control inputs as the control input set Record all other agent sets that can be received by agent i as the neighbor set Record all other agent sets that can receive the broadcast information of agent i as the neighbor set Record the set of broadcast information representing whether the agent i can receive the pilot agent as the traction set Define the pull-in neighbor set as And the communication topology in the multi-agent system is a double-front vehicle-following type;

[0060] x i (t+1)=Ax i (t)+Bu i (t) (1)

[0061] In the formula:

[006...

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Abstract

The invention discloses a multi-agent distributed model prediction control method and system. The method comprises the steps that 1 a kinetic equation of an intelligent agent is described, and parameters are defined; 2 the intelligent agent broadcasts the assumed state track of the future Np + 1 step of the intelligent agent and receives the assumed state track broadcasted by the intelligent agent in a neighbor set to the intelligent agent out of the neighbor set; 3 a future Np step optimal control input sequence and a future Np + 1 step optimal state sequence are solved; 4 the intelligent agent uses the first element of the optimal control input sequence for the current moment t, the second to Np-1 elements of the optimal control input sequence are used as assumed input tracks of the moment t + 1, and the second to Np elements of the optimal state sequence are used as assumed state tracks of the moment t + 1; and 5 a join terminal is input, and the steps 2 to 5 are repeated through single-step recursion. The method can guarantee the iteration feasibility, is suitable for a wide range of communication topology types, and simplifies the implementation and parameter adjustment in practical application.

Description

technical field [0001] The invention relates to the technical field of multi-agent systems, in particular to a multi-agent distributed model predictive control method and system. Background technique [0002] A multi-agent system is a system composed of multiple agents interacting in an environment. In recent decades, with the popularization of mobile communication and computing technology, the distributed cooperative control technology of multi-agent systems has emerged and has been widely used in many fields. For example, multi-agent distributed model predictive control is used in the collaborative operation of multiple autonomous underwater robots and the collaborative driving of multiple intelligent networked vehicles, which can significantly improve the efficiency and reliability of multi-vehicle operations and runtime. [0003] Because the actual system has the characteristics of complex model, large scale, many variables and many constraints, traditional control meth...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/00
Inventor 边有钢谭艳谢国涛王晓伟秦洪懋秦晓辉徐彪秦兆博胡满江丁荣军
Owner HUNAN UNIV
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