3 research outputs found

    Improved crowd psychological model and control

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    The behavior of human crowd is an interesting phenomenon in which individuals are set as a collection that comprises of a highly dynamic social group. The crowd behaviors have been investigated by researchers over the years. Recent works include the study in modeling and controlling of the dynamic psychological behavior of crowds such as students’ behavior in a classroom or people’s behavior in a one-dimensional queue. In this paper, an improved version of the psychological crowd model has been proposed, where the social interaction between two individuals in a crowd is represented by a weightage, called the weight of social interaction. It has been shown that the inclusion of the social interaction weight has allowed social interactions between individuals to be included and results in a more accurate representation of the crowd’s psychological factors propagations. Since the psychological dynamics of crowd is naturally unstable, this paper also discusses the application of two nonlinear control approaches to stabilise the crowd to make it calm. Results show that for a crowd of n number of agents, the single-agent controller gives similar performance with the n-agent controller but with much less resources. The simulation results also show that it takes less amount of time to stabilise a crowd when the crowd model includes social interaction weights

    Review on psychological crowd model based on LeBon's theory

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    Irrational crowds tend to adapt herd mentality, having group behaviour and high suggestion through interaction. It is important to see how an irrational crowd can be controlled to prevent undesirable crowd attitude. This paper reviews existing models and the controllers to provide a comprehensive study for crowd control. It focuses on a comprehensive analysis of the control of psychological crowd, modelled using LeBon's theory; which defines the crowd behaviour in terms of crowd attitude. The crowd attitude is defined in terms of suggestibility and prestige and the crowd interaction is defined in terms of the interaction of prestige and suggestibility, which is naturally unstable. A controller is required to achieve stability. In this paper several control approaches are described and the best control approach is highlighted. The results conclude, the best control approach is using multiple control agents, since the control effort is reduced and the stabilizing time is improved

    A Targeting Approach To Disturbance Rejection In Multi-Agent Systems

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    This thesis focuses on deadbeat disturbance rejection for discrete-time linear multi-agent systems. The multi-agent systems, on which Spieser and Shams’ decentralized deadbeat output regulation problem is based, are extended by including disturbance agents. Specifically, we assume that there are one or more disturbance agents interacting with the plant agents in some known manner. The disturbance signals are assumed to be unmeasured and, for simplicity, constant. Control agents are introduced to interact with the plant agents, and each control agent is assigned a target plant agent. The goal is to drive the outputs of all plant agents to zero in finite time, despite the presence of the disturbances. In the decentralized deadbeat output regulation problem, two analysis schemes were introduced: targeting analysis, which is used to determine whether or not control laws can be found to regulate, not all the agents, but only the target agents; and growing analysis, which is used to determine the behaviour of all the non-target agents when the control laws are applied. In this thesis these two analyses are adopted to the deadbeat disturbance rejection problem. A new necessary condition for successful disturbance rejection is derived, namely that a control agent must be connected to the same plant agent to which a disturbance agent is connected. This result puts a bound on the minimum number of control agents and constraints the locations of control agents. Then, given the premise that both targeting and growing analyses succeed in the special case where the disturbances are all ignored, a new control approach is proposed for the linear case based on the idea of integral control and the regulation methods of Spieser and Shams. Preliminary studies show that this approach is also suitable for some nonlinear systems
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