The Experts below are selected from a list of 852 Experts worldwide ranked by ideXlab platform
Guanrong Chen - One of the best experts on this subject based on the ideXlab platform.
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Designing Distributed Specified-Time Consensus Protocols for Linear Multiagent Systems Over Directed Graphs
IEEE Transactions on Automatic Control, 2019Co-Authors: Yu Zhao, Yongfang Liu, Guanghui Wen, Wei Ren, Guanrong ChenAbstract:This technical note addresses the distributed specified-time consensus protocol design problem for multiagent systems with general linear dynamics over directed graphs. By using motion planning approaches, a novel class of distributed consensus protocols are developed. With a prespecified settling time, the proposed protocols solve the consensus problem of linear multiagent systems over directed graphs containing a directed spanning tree. In particular, the settling time can be offline prespecified, according to task requirements. Compared with the existing results for multiagent systems, to our best knowledge, this is the first time specified-time consensus problems are raised and solved for general linear multiagent systems over directed graphs. Extensions to the specified-time formation flying are further studied for multiple satellites described by Hill equations.
Sung Jin Yoo - One of the best experts on this subject based on the ideXlab platform.
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connectivity preserving consensus tracking of uncertain nonlinear strict feedback multiagent systems an error transformation approach
IEEE Transactions on Neural Networks, 2018Co-Authors: Sung Jin YooAbstract:This brief addresses a distributed connectivity-preserving adaptive consensus tracking problem of uncertain nonlinear strict-feedback multiagent systems with limited communication ranges. Compared with existing consensus results for uncertain nonlinear lower triangular multiagent systems, the main contribution of this brief is to present an error-transformation-based design methodology to preserve initial connectivity patterns in the consensus tracking field, namely, both connectivity preservation and consensus tracking problems are considered for uncertain nonlinear lower triangular multiagent systems. A dynamic surface design based on nonlinearly transformed errors and neural network function approximators is established to construct the local controller of each follower. In addition, a technical lemma is derived to analyze the stability of the proposed connectivity-preserving consensus scheme in the Lyapunov sense.
Long Wang - One of the best experts on this subject based on the ideXlab platform.
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consensus of hybrid multi agent systems
IEEE Transactions on Neural Networks, 2018Co-Authors: Yuanshi Zheng, Long WangAbstract:In this brief, we consider the consensus problem of hybrid multiagent systems. First, the hybrid multiagent system is proposed, which is composed of continuous-time and discrete-time dynamic agents. Then, three kinds of consensus protocols are presented for the hybrid multiagent system. The analysis tool developed in this brief is based on the matrix theory and graph theory. With different restrictions of the sampling period, some necessary and sufficient conditions are established for solving the consensus of the hybrid multiagent system. The consensus states are also obtained under different protocols. Finally, simulation examples are provided to demonstrate the effectiveness of our theoretical results.
Zhi Liu - One of the best experts on this subject based on the ideXlab platform.
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neural network based adaptive leader following consensus control for a class of nonlinear multiagent state delay systems
IEEE Transactions on Systems Man and Cybernetics, 2017Co-Authors: Guoxing Wen, C Philip L Chen, Yanjun Liu, Zhi LiuAbstract:Compared with the existing neural network (NN) or fuzzy logic system (FLS) based adaptive consensus methods, the proposed approach can greatly alleviate the computation burden because it needs only to update a few adaptive parameters online. In the multiagent agreement control, the system uncertainties derive from the unknown nonlinear dynamics are counteracted by employing the adaptive NNs; the state delays are compensated by designing a Lyapunov–Krasovskii functional. Finally, based on Lyapunov stability theory, it is demonstrated that the proposed consensus scheme can steer a multiagent system synchronizing to the predefined reference signals. Two simulation examples, a numerical multiagent system and a practical multimanipulator system, are carried out to further verify and testify the effectiveness of the proposed agreement approach.
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observer based adaptive backstepping consensus tracking control for high order nonlinear semi strict feedback multiagent systems
IEEE Transactions on Systems Man and Cybernetics, 2016Co-Authors: C Philip L Chen, Guoxing Wen, Yanjun Liu, Zhi LiuAbstract:Combined with backstepping techniques, an observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, of which each follower agent is modeled in a semi-strict-feedback form. By constructing the neural network-based state observer for each follower, the proposed consensus control method solves the unmeasurable state problem of high-order nonlinear multiagent systems. The control algorithm can guarantee that all signals of the multiagent system are semi-globally uniformly ultimately bounded and all outputs can synchronously track a reference signal to a desired accuracy. A simulation example is carried out to further demonstrate the effectiveness of the proposed consensus control method.
Demange Jonathan - One of the best experts on this subject based on the ideXlab platform.
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Un modèle d'environnement pour la simulation multiniveau - Application à la simulation de foules
2012Co-Authors: Demange Jonathan, Koukam Abder, Galland StéphaneAbstract:Cette thèse propose un modèle organisationnel et holonique de l'environnement pour la simulation des déplacements de piétons dans des bâtiments. Une foule de piétons peut être considérée comme un système composé d'un grand nombre d'entités en interaction, dont la dynamique globale ne peut se réduire à la somme des comportements de ses composants. La simulation multiniveau fondée sur les modèles Multiagents holoniques constitue une approche permettant d'analyser la dynamique de tels systèmes. Elle autorise leur analyse en considérant plusieurs niveaux d'observation (microscopique, mésoscopique et macroscopique) et prend en compte les ressources de calcul disponibles. Dans ces systèmes, l'environnement est considéré comme l'une des parties essentielles. La dynamique des piétons composant la foule est alors clairement distinguée de celle de l'environnement dans lequel ils se déplacent. Un modèle organisationnel décrivant la structure et la dynamique de l'environnement est proposé. L'environnement est structurellement décomposé en zones, sous-zones, etc. Les organisations et les rôles de cet environnement sont projetés dans une société d'agents ayant en charge de simuler la dynamique de l'environnement et les différentes missions qui lui sont classiquement assignées dans les systèmes Multiagents. Ce modèle précise également les règles de passage entre deux niveaux d'observation. Ainsi, chaque agent appartenant au modèle de l'environnement tente d'utiliser une approximation des comportements de ses sous-zones afin de limiter la consommation de ressources durant la simulation. La qualité de l'approximation entre ces deux niveaux d'observation est évaluée avec des indicateurs énergétiques. Ils permettent de déterminer si l'agent approxime correctement les comportements des agents associés aux sous-zones. En sus du modèle organisationnel et holonique proposé, nous présentons un modèle concret de la simulation de voyageurs dans un terminal d'aéroport. Ce modèle concret est implanté sur les plateformes JaSIM et Janus.This work presents a holonic organizational model of the environment for the simulation of pedestrians in buildings. A crowd of pedestrians is considered as a system composed of a large number of interacting entities. The global dynamics of this system cannot be reduced to the sum of the behaviors of its components, Multilevel simulation based on holonic multiagent models is one approach to analyze the dynamics of such systems. It allows their analysis by considering several levels of observation (microscopic, mesoscopic and macroscopic) and the available computing resources. In these systems, the environment is considered as an essential part. The behavior of the crowd is clearly distinguished from the behavior of the environment in which the pedestrians move. An organizational model is proposed to describe the structure and the dynamics of the indoor environment. This environment is structurally divided into areas, sub-areas, etc. Organizations and roles are mapped into a society of agents in charge of simulating the dynamics of the environment and their various missions in multiagent systems. This model also specifies the rules for changing the level of observation dynamically. Thus, each agent belonging to the model of the environment tries to use an approximation of behaviors of its sub-zones, and at the same time to minimize the resource consumption. The quality of the approximation between these two levels is evaluated with energy-based indicators. They help to determine if the agent approximates the behaviors of its sub-agents correctly. In addition to the organizational and holonic model proposed in this work, we present a concrete model of the simulation of passengers in an airport terminal. This concrete model is implemented on the platforms JaSIM and Janus.BELFORT-UTBM-SEVENANS (900942101) / SudocSudocFranceF
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A model of environment for the multilevel simulation : Application to the crowd simulation
2012Co-Authors: Demange JonathanAbstract:Cette thèse propose un modèle organisationnel et holonique de l'environnement pour la simulation des déplacements de piétons dans des bâtiments. Une foule de piétons peut être considérée comme un système composé d'un grand nombre d'entités en interaction, dont la dynamique globale ne peut se réduire à la somme des comportements de ses composants. La simulation multiniveau fondée sur les modèles Multiagents holoniques constitue une approche permettant d'analyser la dynamique de tels systèmes. Elle autorise leur analyse en considérant plusieurs niveaux d'observation (microscopique, mésoscopique et macroscopique) et prend en compte les ressources de calcul disponibles. Dans ces systèmes, l'environnement est considéré comme l'une des parties essentielles. La dynamique des piétons composant la foule est alors clairement distinguée de celle de l'environnement dans lequel ils se déplacent. Un modèle organisationnel décrivant la structure et la dynamique de l'environnement est proposé. L'environnement est structurellement décomposé en zones, sous-zones, etc. Les organisations et les rôles de cet environnement sont projetés dans une société d'agents ayant en charge de simuler la dynamique de l'environnement et les différentes missions qui lui sont classiquement assignées dans les systèmes Multiagents. Ce modèle précise également les règles de passage entre deux niveaux d'observation. Ainsi, chaque agent appartenant au modèle de l'environnement tente d'utiliser une approximation des comportements de ses sous-zones afin de limiter la consommation de ressources durant la simulation. La qualité de l'approximation entre ces deux niveaux d'observation est évaluée avec des indicateurs énergétiques. Ils permettent de déterminer si l'agent approxime correctement les comportements des agents associés aux sous-zones. En sus du modèle organisationnel et holonique proposé, nous présentons un modèle concret de la simulation de voyageurs dans un terminal d'aéroport. Ce modèle concret est implanté sur les plateformes JaSIM et Janus.This work presents a holonic organizational model of the environment for the simulation of pedestrians in buildings. A crowd of pedestrians is considered as a system composed of a large number of interacting entities. The global dynamics of this system cannot be reduced to the sum of the behaviors of its components, Multilevel simulation based on holonic multiagent models is one approach to analyze the dynamics of such systems. It allows their analysis by considering several levels of observation (microscopic, mesoscopic and macroscopic) and the available computing resources. In these systems, the environment is considered as an essential part. The behavior of the crowd is clearly distinguished from the behavior of the environment in which the pedestrians move. An organizational model is proposed to describe the structure and the dynamics of the indoor environment. This environment is structurally divided into areas, sub-areas, etc. Organizations and roles are mapped into a society of agents in charge of simulating the dynamics of the environment and their various missions in multiagent systems. This model also specifies the rules for changing the level of observation dynamically. Thus, each agent belonging to the model of the environment tries to use an approximation of behaviors of its sub-zones, and at the same time to minimize the resource consumption. The quality of the approximation between these two levels is evaluated with energy-based indicators. They help to determine if the agent approximates the behaviors of its sub-agents correctly. In addition to the organizational and holonic model proposed in this work, we present a concrete model of the simulation of passengers in an airport terminal. This concrete model is implemented on the platforms JaSIM and Janus
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Un modèle d'environnement pour la simulation multiniveau - Application à la simulation de foules
HAL CCSD, 2012Co-Authors: Demange JonathanAbstract:This work presents a holonic organizational model of the environment for the simulation of pedestrians in buildings. A crowd of pedestrians is considered as a system composed of a large number of interacting entities. The global dynamics of this system cannot be reduced to the sum of the behaviors of its components, Multilevel simulation based on holonic multiagent models is one approach to analyze the dynamics of such systems. It allows their analysis by considering several levels of observation (microscopic, mesoscopic and macroscopic) and the available computing resources. In these systems, the environment is considered as an essential part. The behavior of the crowd is clearly distinguished from the behavior of the environment in which the pedestrians move. An organizational model is proposed to describe the structure and the dynamics of the indoor environment. This environment is structurally divided into areas, sub-areas, etc. Organizations and roles are mapped into a society of agents in charge of simulating the dynamics of the environment and their various missions in multiagent systems. This model also specifies the rules for changing the level of observation dynamically. Thus, each agent belonging to the model of the environment tries to use an approximation of behaviors of its sub-zones, and at the same time to minimize the resource consumption. The quality of the approximation between these two levels is evaluated with energy-based indicators. They help to determine if the agent approximates the behaviors of its sub-agents correctly. In addition to the organizational and holonic model proposed in this work, we present a concrete model of the simulation of passengers in an airport terminal. This concrete model is implemented on the platforms JaSIM and Janus.Cette thèse propose un modèle organisationnel et holonique de l'environnement pour la simulation des déplacements de piétons dans des bâtiments. Une foule de piétons peut être considérée comme un système composé d'un grand nombre d'entités en interaction, dont la dynamique globale ne peut se réduire à la somme des comportements de ses composants. La simulation multiniveau fondée sur les modèles Multiagents holoniques constitue une approche permettant d'analyser la dynamique de tels systèmes. Elle autorise leur analyse en considérant plusieurs niveaux d'observation (microscopique, mésoscopique et macroscopique) et prend en compte les ressources de calcul disponibles. Dans ces systèmes, l'environnement est considéré comme l'une des parties essentielles. La dynamique des piétons composant la foule est alors clairement distinguée de celle de l'environnement dans lequel ils se déplacent. Un modèle organisationnel décrivant la structure et la dynamique de l'environnement est proposé. L'environnement est structurellement décomposé en zones, sous-zones, etc. Les organisations et les rôles de cet environnement sont projetés dans une société d'agents ayant en charge de simuler la dynamique de l'environnement et les différentes missions qui lui sont classiquement assignées dans les systèmes Multiagents. Ce modèle précise également les règles de passage entre deux niveaux d'observation. Ainsi, chaque agent appartenant au modèle de l'environnement tente d'utiliser une approximation des comportements de ses sous-zones afin de limiter la consommation de ressources durant la simulation. La qualité de l'approximation entre ces deux niveaux d'observation est évaluée avec des indicateurs énergétiques. Ils permettent de déterminer si l'agent approxime correctement les comportements des agents associés aux sous-zones. En sus du modèle organisationnel et holonique proposé, nous présentons un modèle concret de la simulation de voyageurs dans un terminal d'aéroport. Ce modèle concret est implanté sur les plateformes JaSIM et Janus
