Distributed finite time tracking control method for multi-robot system in view of interference and model uncertainty

Abstract

The invention discloses a distributed finite time tracking control method for a multi-robot system in view of interference and model uncertainty, and relates to a control method for a multi-robot system. In order to solve the problems of poor robustness of the existing control method for the multi-robot control system and heavy overall communication burden of the multi-robot system, the method comprises the steps of establishing a dynamical model FORMULA (shown in the specification) of a pilot robot and a dynamical model FORMULA (shown in the specification) of each following robot in the multi-robot system, and calculating a weighted adjacent matrix A and a Laplacian matrix in a directed graph theory of the multi-robot system; and then designing a distributed finite time tracking control law FORMULA (shown in the specification) of the multi-robot system, so that each following robot follows the pilot robot with a dynamic time change locus within finite time and finite time tracking control of the multi-robot system is completed. The method is applicable in the field of control of multi-robot systems.

Description

technical field

[0001] The invention relates to a control method of a multi-robot system. Background technique

[0002] With the development of computer technology and wireless communication technology, multi-robot coordination and cooperation has become possible and has been applied more and more. Using multiple robots to form a formation has many advantages, and it can complete tasks that are difficult for a single robot to complete. In the industrial field, replace humans to complete some operations in dangerous or harsh environments, such as handling, classification, rounding up, etc.; in the aviation field, use multi-space robots, alien detection robots to explore unknown planets, and maintain space stations. Reduce costs and improve system reliability and safety; in the medical field, multiple micro-robots enter the human body to conduct in-depth inspection and diagnosis of diseased parts. From the perspective of multi-robot system control framework, multi-robot form...

Examples

specific Embodiment approach 1

[0036] Distributed finite-time tracking control method for multi-robot systems considering disturbance and model uncertainty,

[0037] Based on the following assumptions:

[0038] (1) The time-varying control input u of the pilot robot N+1 is unknown to all following robots, and its upper bound information Can be obtained by some following robots;

[0039] (2) Generalized interference is time-varying and unknown, satisfying in is an unknown, bounded, normal constant; define d ‾ = m a x ( d ‾ 1 , ... , d ‾ N ) ;

[0040] (3) The directed graph G has a directed spanning tree;

[0041] A distributed finite-time tracking control method for multi-robot syst...

specific Embodiment approach 2

[0054] The specific implementation steps of step 2 of the present embodiment are as follows:

[0055] For a multi-robot system, including N follower robots, To follow the robot assembly, is the set of pilot robots, and the set of multi-robot systems is ν=ν L ∪ν F ;

[0056] The communication topology between robots is represented by a directed graph G=(ν,ε), where ν is the set of all nodes, is the set of all edges; for robot i and robot j, edge (ν i ,ν j )∈ε means that robot j can receive information from robot i, but the opposite is not necessarily true; node ν i The neighbors of are defined as satisfying (ν j ,ν i ) ∈ ε relation of all robots j set, denoted as N i ={ν j :(ν j ,ν i )∈ε}; j is a serial number different from robot i;

[0057] The weighted adjacency matrix A of the directed graph = [a ij ] is defined as: if (v j ,v i )∈ε, then a ij = 1, otherwise a ij = 0; it is generally assumed that the node itself does not have connectivity, that is, a i...

specific Embodiment approach 3

[0068] The specific implementation steps of step 3 of the present embodiment are as follows:

[0069] Define the error function for following the robot and for:

[0070] e i F x ( t ) = Σ j F = 1 N a i F j F ( q i F - q j F ) + b i F ( q i F ...

technical field

[0001] The invention relates to a control method of a multi-robot system. Background technique

[0002] With the development of computer technology and wireless communication technology, multi-robot coordination and cooperation has become possible and has been applied more and more. Using multiple robots to form a formation has many advantages, and it can complete tasks that are difficult for a single robot to complete. In the industrial field, replace humans to complete some operations in dangerous or harsh environments, such as handling, classification, rounding up, etc.; in the aviation field, use multi-space robots, alien detection robots to explore unknown planets, and maintain space stations. Reduce costs and improve system reliability and safety; in the medical field, multiple micro-robots enter the human body to conduct in-depth inspection and diagnosis of diseased parts. From the perspective of multi-robot system control framework, multi-robot form...

Examples

specific Embodiment approach 1

[0036] Distributed finite-time tracking control method for multi-robot systems considering disturbance and model uncertainty,

[0037] Based on the following assumptions:

[0038] (1) The time-varying control input u of the pilot robot N+1 is unknown to all following robots, and its upper bound information Can be obtained by some following robots;

[0039] (2) Generalized interference is time-varying and unknown, satisfying in is an unknown, bounded, normal constant; define d ‾ = m a x ( d ‾ 1 , ... , d ‾ N ) ;

[0040] (3) The directed graph G has a directed spanning tree;

[0041] A distributed finite-time tracking control method for multi-robot syst...

specific Embodiment approach 2

[0054] The specific implementation steps of step 2 of the present embodiment are as follows:

[0055] For a multi-robot system, including N follower robots, To follow the robot assembly, is the set of pilot robots, and the set of multi-robot systems is ν=ν L ∪ν F ;

[0056] The communication topology between robots is represented by a directed graph G=(ν,ε), where ν is the set of all nodes, is the set of all edges; for robot i and robot j, edge (ν i ,ν j )∈ε means that robot j can receive information from robot i, but the opposite is not necessarily true; node ν i The neighbors of are defined as satisfying (ν j ,ν i ) ∈ ε relation of all robots j set, denoted as N i ={ν j :(ν j ,ν i )∈ε}; j is a serial number different from robot i;

[0057] The weighted adjacency matrix A of the directed graph = [a ij ] is defined as: if (v j ,v i )∈ε, then a ij = 1, otherwise a ij = 0; it is generally assumed that the node itself does not have connectivity, that is, a i...

specific Embodiment approach 3

[0068] The specific implementation steps of step 3 of the present embodiment are as follows:

[0069] Define the error function for following the robot and for:

[0070] e i F x ( t ) = Σ j F = 1 N a i F j F ( q i F - q j F ) + b i F ( q i F ...

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