The Experts below are selected from a list of 7227 Experts worldwide ranked by ideXlab platform
Hao Wang - One of the best experts on this subject based on the ideXlab platform.
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Wireless Network Dynamic Topology Routing Protocol Based on Aggregation Tree Model
International Conference on Networking International Conference on Systems and International Conference on Mobile Communications and Learning Technolo, 2006Co-Authors: Jialin Li, Hao WangAbstract:As the scale of the Network increases, especially wireless and mobile Networks comes into fashion, the problem of Network Dynamic topology management turns into a focus topic in the Network world. When Network information changes, frequent route computing and Network state updates can cause computing and traffic overhead, respectively. Therefore, minimum of influence to Network structure has been identified as one of the key issues in designing Dynamic Network routing protocols. A novel protocol, which is based on Aggregation Tree Routing Model (ATRM) as well as an effective ball-and-string algorithm, is introduced in this paper which aims to minimize the alteration of Network topology and to speed up the minimum cost route computation. This routing protocol is applicable to all kinds of Networks, including Internet, ad hoc and wireless sensor Networks. The simulations show that our protocol not only results in significantly lower overhead, but also gives high levels of Dynamic Network topology management performance while keeping practical.
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ICN/ICONS/MCL - Wireless Network Dynamic Topology Routing Protocol Based on Aggregation Tree Model
International Conference on Networking International Conference on Systems and International Conference on Mobile Communications and Learning Technolo, 2006Co-Authors: Jialin Li, Hao WangAbstract:As the scale of the Network increases, especially wireless and mobile Networks comes into fashion, the problem of Network Dynamic topology management turns into a focus topic in the Network world. When Network information changes, frequent route computing and Network state updates can cause computing and traffic overhead, respectively. Therefore, minimum of influence to Network structure has been identified as one of the key issues in designing Dynamic Network routing protocols. A novel protocol, which is based on Aggregation Tree Routing Model (ATRM) as well as an effective ball-and-string algorithm, is introduced in this paper which aims to minimize the alteration of Network topology and to speed up the minimum cost route computation. This routing protocol is applicable to all kinds of Networks, including Internet, ad hoc and wireless sensor Networks. The simulations show that our protocol not only results in significantly lower overhead, but also gives high levels of Dynamic Network topology management performance while keeping practical.
Xiuchen Jiang - One of the best experts on this subject based on the ideXlab platform.
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Power Distribution Network Dynamic Topology Awareness and Localization Based on Subspace Perturbation Model
IEEE Transactions on Power Systems, 2020Co-Authors: Nan Zhou, Gehao Sheng, Xiuchen JiangAbstract:Identifying Network Dynamic topology changes with limited measurement data is a primary challenge for power distribution system analysis. Existing methods require the measurement of the nodal voltage (both amplitudes and phase angles) of a majority of nodes, which means that large-scale installation of advanced monitors is necessary. In this paper, a distribution Network Dynamic topology awareness method that only requires a synchronized voltage amplitude measurement of a limited number of nodes is proposed. The key idea of the design is to relate Network topology changes (including line topology changes, node topology changes and switch actions) to the resultant perturbations in the voltage amplitude covariance matrix. Because perturbations can be identified with incomplete observations, the corresponding topology changes can be identified with limited measurements of voltage amplitude data. With no need for phase-angle measurement, only ordinary root mean square (RMS) based monitors are needed, which can be made available with a relatively minor investment. Simulation tests are performed with the IEEE 123-node system and 8500-node system. Remarkably, 80% of the topology changes can be detected with only 10% of the nodes equipped with monitors, and a 100% correct localization rate can be achieved with 50% of the nodes equipped with monitors.
Alois Knoll - One of the best experts on this subject based on the ideXlab platform.
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Adaptive neural Network Dynamic Surface Control: An evaluation on the musculoskeletal robot Anthrob
Robotics and Automation (ICRA) 2015 IEEE International Conference on, 2015Co-Authors: Martin Jantsch, Konstantinos Dalamagkidis, S Wittmeier, G. Herrmann, Alois KnollAbstract:The soft robotics approach is widely considered to enable robots in the near future to leave their cages and move freely in our modern homes and manufacturing sites. Musculoskeletal robots are such soft robots which feature passively compliant actuation, while leveraging the advantages of tendon-driven systems. Even though these robots have been intensively researched within the last decade, high-performance feedback control laws have only very recently been developed. In [1], a controller was developed utilizing Dynamic Surface Control (DSC), an extension to backstepping, with an adaptive neural Network compensator for joint as well as muscle friction. We compare these novel control strategies to Computed Force Control (CFC), an existing technique from the field of tendon-driven control, yielding highly improved trajectory tracking. The musculoskeletal robot Anthrob [2] serves as a benchmark.
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Adaptive neural Network Dynamic surface control for musculoskeletal robots
53rd IEEE Conference on Decision and Control, 2014Co-Authors: Martin Jantsch, Konstantinos Dalamagkidis, S Wittmeier, G. Herrmann, Alois KnollAbstract:Musculoskeletal robots are a class of compliant, tendon-driven robots that can be used in robotics applications, as well as in the study of biological motor systems. Unfortunately, there is little progress in controlling such systems. Modern non-linear control approaches are used to overcome the challenges posed by the muscle compliance, the multi-DoF joints, as well as unmodeled Dynamic effects such as friction. A controller is derived for a generic model of musculoskeletal robots utilizing a multidimensional form of Dynamic Surface Control (DSC), an extension to backstepping. This controller is extended by an adaptive neural Network to compensate for both muscle and joint friction. The developed controllers are evaluated against the state of the art Computed Force Control (CFC), an application of feedback linearization, for a spherical joint which is actuated by five muscles.
Jialin Li - One of the best experts on this subject based on the ideXlab platform.
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Wireless Network Dynamic Topology Routing Protocol Based on Aggregation Tree Model
International Conference on Networking International Conference on Systems and International Conference on Mobile Communications and Learning Technolo, 2006Co-Authors: Jialin Li, Hao WangAbstract:As the scale of the Network increases, especially wireless and mobile Networks comes into fashion, the problem of Network Dynamic topology management turns into a focus topic in the Network world. When Network information changes, frequent route computing and Network state updates can cause computing and traffic overhead, respectively. Therefore, minimum of influence to Network structure has been identified as one of the key issues in designing Dynamic Network routing protocols. A novel protocol, which is based on Aggregation Tree Routing Model (ATRM) as well as an effective ball-and-string algorithm, is introduced in this paper which aims to minimize the alteration of Network topology and to speed up the minimum cost route computation. This routing protocol is applicable to all kinds of Networks, including Internet, ad hoc and wireless sensor Networks. The simulations show that our protocol not only results in significantly lower overhead, but also gives high levels of Dynamic Network topology management performance while keeping practical.
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ICN/ICONS/MCL - Wireless Network Dynamic Topology Routing Protocol Based on Aggregation Tree Model
International Conference on Networking International Conference on Systems and International Conference on Mobile Communications and Learning Technolo, 2006Co-Authors: Jialin Li, Hao WangAbstract:As the scale of the Network increases, especially wireless and mobile Networks comes into fashion, the problem of Network Dynamic topology management turns into a focus topic in the Network world. When Network information changes, frequent route computing and Network state updates can cause computing and traffic overhead, respectively. Therefore, minimum of influence to Network structure has been identified as one of the key issues in designing Dynamic Network routing protocols. A novel protocol, which is based on Aggregation Tree Routing Model (ATRM) as well as an effective ball-and-string algorithm, is introduced in this paper which aims to minimize the alteration of Network topology and to speed up the minimum cost route computation. This routing protocol is applicable to all kinds of Networks, including Internet, ad hoc and wireless sensor Networks. The simulations show that our protocol not only results in significantly lower overhead, but also gives high levels of Dynamic Network topology management performance while keeping practical.
Nan Zhou - One of the best experts on this subject based on the ideXlab platform.
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Power Distribution Network Dynamic Topology Awareness and Localization Based on Subspace Perturbation Model
IEEE Transactions on Power Systems, 2020Co-Authors: Nan Zhou, Gehao Sheng, Xiuchen JiangAbstract:Identifying Network Dynamic topology changes with limited measurement data is a primary challenge for power distribution system analysis. Existing methods require the measurement of the nodal voltage (both amplitudes and phase angles) of a majority of nodes, which means that large-scale installation of advanced monitors is necessary. In this paper, a distribution Network Dynamic topology awareness method that only requires a synchronized voltage amplitude measurement of a limited number of nodes is proposed. The key idea of the design is to relate Network topology changes (including line topology changes, node topology changes and switch actions) to the resultant perturbations in the voltage amplitude covariance matrix. Because perturbations can be identified with incomplete observations, the corresponding topology changes can be identified with limited measurements of voltage amplitude data. With no need for phase-angle measurement, only ordinary root mean square (RMS) based monitors are needed, which can be made available with a relatively minor investment. Simulation tests are performed with the IEEE 123-node system and 8500-node system. Remarkably, 80% of the topology changes can be detected with only 10% of the nodes equipped with monitors, and a 100% correct localization rate can be achieved with 50% of the nodes equipped with monitors.