In this paper, consensus problem of multiple Euler-Lagrange systems is studied in the presence of both model uncertainties and exogenous disturbance. Only nominal parameters of Lagrange dynamics are assumed to be avai...
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In this paper, consensus problem of multiple Euler-Lagrange systems is studied in the presence of both model uncertainties and exogenous disturbance. Only nominal parameters of Lagrange dynamics are assumed to be available. A distributed control algorithm combined with the extended state observer, which is adopted to estimate unmodelled dynamics and external disturbance, is first presented in this note such that all the agents can asymptotically reach a consensus. Moreover, the consensus with switching topology is also reachable with the proposed controller. Finally, simulation examples of networked manipulator systems are provided to show the effectiveness of the controller.
Cluster control system to realize mutual coordination between individual objects must determine the control and the information relationship in terms of logical and physical aspects. Study these problems of the system...
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Cluster control system to realize mutual coordination between individual objects must determine the control and the information relationship in terms of logical and physical aspects. Study these problems of the system structure, system structure and control can be combined and ensure smooth information flow and control flow in the system and the framework for the interaction between the individual. Cluster controlalgorithm ensure cooperation among multiple control individual effectively, to deal with an emergency to be able to react quickly, improve the real-time performance and effectiveness of control system. This paper proposed a new methodology to Group Intelligence control by using a distributed control algorithm and a Swarm Intelligence algorithm to optimize the path of the individual of the cluster and the real-time control of each object. In the first part of this paper, we introduced the appearance and the development of Group Intelligence control system. Then, the paper proposed our methodology of the proposed Group Intelligence control system.
It is known that demand and supply power balancing is an essential method to operate power delivery system and prevent blackouts caused by power shortage. In this paper, we focus on the implementation of demand respon...
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It is known that demand and supply power balancing is an essential method to operate power delivery system and prevent blackouts caused by power shortage. In this paper, we focus on the implementation of demand response strategy to save power during peak hours by using Smart Grid. It is obviously impractical with centralized power control network to realize the real-time control performance, where a single central controller measures the huge metering data and sends control command back to all customers. For that purpose, we propose a new architecture of hierarchical distributed power control network which is scalable regardless of the network size. The sub-controllers are introduced to partition the large system into smaller distributed clusters where low-latency local feedback power control loops are conducted to guarantee control stability. Furthermore, sub-controllers are stacked up in an hierarchical manner such that data are fed back layer-by-layer in the inbound while in the outbound control responses are decentralized in each local sub-controller for realizing the global objectives. Numerical simulations in a realistic scenario of up to 5000 consumers show the effectiveness of the proposed scheme to achieve a desired 10% peak power saving by using off-the-shelf wireless devices with IEEE802.15.4g standard. In addition, a small-scale power control system for green building test-bed is implemented to demonstrate the potential use of the proposed scheme for power saving in real life.
Due to the limited energy supply, energy efficiency is the most important issue for wireless sensor networks. In addition, next generation networks are also expected to support QoS sensitive data services. In this pap...
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Due to the limited energy supply, energy efficiency is the most important issue for wireless sensor networks. In addition, next generation networks are also expected to support QoS sensitive data services. In this paper, a new online sensor network management scheme is developed for energy efficiency and QoS provisioning. To satisfy these conflicting requirements, the proposed scheme consists of clustering and routing algorithms. Without global network information, the online control paradigm is realized in a distributed way. Therefore, the principle contributions of these algorithms are its scalability and responsiveness to current network situations. Simulation results indicate the superior performance of the proposed schemes, while other schemes cannot offer such an attractive performance balance.
This study proposes a distributed control algorithm for coverage in unknown environments with networked mobile sensors. The control law is derived according to the online neural network estimation of the sensory funct...
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ISBN:
(纸本)9781424453610
This study proposes a distributed control algorithm for coverage in unknown environments with networked mobile sensors. The control law is derived according to the online neural network estimation of the sensory function of the environments. In contrary to previous adaptive approaches, a major advantage of the proposed method is that due to the neural network nonlinear approximation property, it is not restricted to multi Gaussian sensory functions. Simulation results show that the proposed controller outperforms the previous adaptive approaches in the sense of performance and convergence rate.
Asset protection is a behavior in which a team of robots establishes a formation around a resource marked as an asset in a hostile environment in order to protect the asset from threats. The robots are assumed to be h...
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Asset protection is a behavior in which a team of robots establishes a formation around a resource marked as an asset in a hostile environment in order to protect the asset from threats. The robots are assumed to be homogeneous and run a decentralized controlalgorithm and possess a repulsive quality to the threats. Previous works in this area have used centralized control or considered the use of many robots. This work aims at developing an algorithm that is both decentralized, and able to protect assets using only a few robots. In order to provide this behavior an algorithm coined the Asset Guarding Intelligent System (AeGIS), was developed and analyzed. Using AeGIS, each robot will detect an asset move towards it and form a protective formation around it. AeGIS utilizes Quadratic Artificial Potential Fields (QAPFs) as the robot’s path planning module. As such the fields are designed to move the robots into formation, avoid collisions, and in turn protect assets. AeGIS is tested using Leviathan—an event-driven simulator designed to test groups of autonomous swarm robots employing distributed control algorithms. The success rate of different variations of AeGIS were tested. Additionally, the number of threats, robots employing AeGIS, and the number and mobility of assets were varied to observe their effect on the success rate. The simulation results show that with sufficient number of robots, the assets, static or mobile are well protected against 20 modeled threats. Through these results it is shown that AeGIS is a solution to the asset protection problem.
This paper introduces a measure of communication complexity for a two-agent distributedcontrol system where controls are subject to finite bandwidth communication constraints. The proposed complexity measure is an ex...
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This paper introduces a measure of communication complexity for a two-agent distributedcontrol system where controls are subject to finite bandwidth communication constraints. The proposed complexity measure is an extension of the idea of communication complexity defined in distributed computing. Applying this classical concept to control problems with finite communication constraints leads to a new perspective and a host of new questions, some of which are investigated in this paper. In particular, one can connect the proposed complexity with the traditional communication complexity via upper bound and lower bound inequalities. Moreover, the proposed complexity is shown to be intricately related to the dynamical characteristics of the underlying system.
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