Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/124414
Type: Thesis
Title: Formation Control and Reconfiguration Strategy of Multi-Agent Systems
Author: Liu, Yutong
Issue Date: 2020
School/Discipline: School of Electrical and Electronic Engineering
Abstract: Multi-agent systems consist of multiple agents, which detect and interact with their local environments. The formation control strategy is studied to drive multi-agent systems to predefined formations. The process is important because the objective formation is designed such that the group achieves more than the sum of its individuals. In this thesis, we consider formation control strategies and reconfiguration strategy for multi-agent systems. The main research contents are as follows. A formation control scheme is proposed for a group of elliptical agents to achieve a predefined formation. The agents are assumed to have the same dynamics, and communication among the agents limited. The desired formation is realized based on the reference formation and the mapping decision. In the controller design, searching algorithms for both cases of minimum distance and tangents are established for each agent and its neighbors. In order to avoid collision, an optimal path planning algorithm based on collision angles, and a self-center-based rotation algorithm are also proposed. Moreover, randomized method is used to provide the optimal mapping decision for the underlying system. To optimize the former formation control scheme, an adaptive formation control strategy is developed. The multiple elliptical agents can form a predefined formation in any 2D space. The controller is based on the neighborhood of each agent and the optimal mapping decision for the whole group. The collision-free algorithm is built based on direction and distance of avoidance group of each agent. The controller for each agent is adaptive based on the number of elements in its avoidance group, the minimum distance it has and its desired moving distance. The proposed adaptive mapping scheme calculates the repetition rate of optimal mappings in screening group of mapping decisions. The new optimal mapping is constructed by the fixed repeating elements in former mappings and the reorganized elements which are not the same in each optimal mappings based on the screening group. An event-triggered probability-driven control scheme is also investigated for a group of elliptical agents to achieve a predefined formation. The agents are assumed to have the same dynamics, and the control law for each agent is only updated at its event sequence based on its own minimum collision time and deviation time. The collision time of each agent is obtained based on the position and velocity of the others, and the deviation time is linked with the distance between its current position and desired position. The probabilitydriven controller is designed to prevent the stuck problem among agents. The stuck problem for the group means that when the distance between vi agents is too close and their moving directions are crossed, the control input with deterministic direction will cause the agents not to move or to move slowly. To optimize the event-triggered probability-driven controller, a mappingadaptive strategy and an angle-adaptive scheme are also developed. The mapping-adaptive strategy is used to find the optimal mapping to decrease the sum of the moving distance for the whole group, while the angle-adaptive scheme is employed to let the distance between any two elliptical agents is large enough to further ensure there is no collision existed during execution. Reconfiguration strategy is considered for multiple predefined formations. A two-stage reconfiguration strategy is proposed for a group of agents to find its special formation, which can be seen as transition of the predefined formations, during idle time in order to minimize the reconfiguration time. The basic reconfiguration strategy combines with a random mapping algorithm to find optimal special formation. To meet the practical requirements, agents are modeled as circles or ellipses. The anti-overlapping strategies are built to construct the achievable special formation based on the geometric properties of circle and ellipse.
Advisor: Shi, Peng
Lim, Cheng-Chew
Dissertation Note: Thesis (Ph.D.) -- University of Adelaide, School of Electrical & Electronic Engineering, 2020
Keywords: Multi-agent systems
formation control
collision avoidance
random mapping algorithm
event-triggered
reconfiguration strategy
Provenance: This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legals
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