117 research outputs found

    Constructing tensegrity frameworks and related applications in multi-agent formation control

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    In deze thesis bestuderen we hoe tensigrity structuren te ontwerpen en de toepassing ervan in formaties van multi-agent systemen. Als eerste dragen we verschillende manieren voor om rigide, infinitesimaal rigide, en super stabiele tensigrity structuren te laten ‘groeien’. Hierna hebben we de virtueel tensigrity structuren toegepast voor het oplossen van formatie problemen. Verschillende regel-algoritmes zijn voorgedragen voor het manoeuvreren van de formatie. Als laatst is een gedistribueerde formatie volg-regelaar ontworpen waarbij tegelijkertijd de formatie vorm kan worden bereikt terwijl de formatie een externe referentie signaal volgt

    Event-triggered output consensus for linear multi-agent systems via adaptive distributed observer

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    summary:This paper investigates the distributed event-triggered cooperative output regulation problem for heterogeneous linear continuous-time multi-agent systems (MASs). To eliminate the requirement of continuous communication among interacting following agents, an event-triggered adaptive distributed observer is skillfully devised. Furthermore, a class of closed-loop estimators is constructed and implemented on each agent such that the triggering times on each agent can be significantly reduced while at the same time the desired control performance can be preserved. Compared with the existing open-loop estimators, the proposed estimators can provide more accurate state estimates during each triggering period. It is further shown that the concerned cooperative output regulation problem can be effectively resolved under the proposed control scheme and the undesirable Zeno behavior can be excluded. Finally, the effectiveness of the proposed results is verified by numerical simulations

    Distributed formation stabilization for mobile agents using virtual tensegrity structures

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    Global stabilization for triangular formations under mixed distance and bearing constraints

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    This paper addresses the triangular formation control problem for a system of three agents under mixed distance and bearing constraints. The main challenge is to find a fully distributed control law for each agent to guarantee the global convergence towards a desired triangular formation. To solve this problem, we invoke the property that a triangle can be uniquely determined by the lengths of its two sides together with the magnitude of the corresponding included angle. Based on this feature, we design a class of control strategies, under which each agent is only responsible for a single control variable, i.e., a distance or an angle, such that the control laws can be implemented in local coordinate frames. The global convergence is shown by analyzing the dynamics of the closed-loop system in its cascade form. Then we discuss some extensions on more general formation shapes and give the quadrilateral formation as an example. Simulation results are provided to validate the effectiveness of the proposed control strategies

    Self-organized Polygon Formation Control based on Distributed Estimation

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    This paper studies the problem of controlling a multi-robot system to achieve a polygon formation in a self-organized manner. Different from the typical formation control strategies where robots are steered to satisfy the predefined control variables, such as pairwise distances, relative positions and bearings, the foremost idea of this paper is to achieve polygon formations by injecting control inputs randomly to a few robots (say, vertex robots) of the group, and the rest follow the simple principles of moving towards the midpoint of their two nearest neighbors in the ring graph without any external inputs. In our problem, a fleet of robots is initially distributed in the plane. The socalled vertex robots take the responsibility of determining the geometric shape of the entire formation and its overall size, while the others move so as to minimize the differences with two direct neighbors. In the first step, each vertex robot estimates the number of robots in its associated chain. Two types of control inputs that serve for the estimation are designed using the measurements from the latest and the last two time instants respectively. In the second step, the self-organized formation control law is proposed where only vertex robots receive external information. Comparisons between the two estimation strategies are carried out in terms of the convergence speed and robustness. The effectiveness of the whole control framework is further validated in both simulation and physical experiments
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