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Robust distributed Estimation for Linear Systems Under Intermittent Information

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2018年第4期63卷 973-988页

作者： Li, Yuchun Phillips, Sean Sanfelice, Ricardo G. Univ Calif Santa Cruz Dept Comp Engn Santa Cruz CA 95064 USA

We provide a comprehensive solution to the estimation problem of the state for a linear time-invariant system in a distributed fashion over networks that allow only intermittent information transmission. By attaching to each node an observer that employs information received from its neighbors triggered by asynchronous communication events, we propose a distributed state observer that guarantees global exponential stability of the zero estimation error set. The design of parameters is formulated as linear matrix inequalities. A thorough robustness analysis of the proposed observer to unmodeled dynamics, unknown communication times, as well as measurement and communication noise characterized in terms of input-to-state stability is presented. These properties of the proposed observer are shown analytically and validated numerically.

关键词： Communication networks distributed algorithms networked control systems nonlinear control systems robust stability state estimation system analysis and design

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distributed coordination for a class of non-linear multi-agent systems with regulation constraints

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IET CONTROL THEORY AND APPLICATIONS 2018年第1期12卷 1-9页

作者： Tang, Yutao Yi, Peng Beijing Univ Posts & Telecommun Sch Automat Beijing Peoples R China Univ Toronto Dept Elect & Comp Engn Toronto ON Canada

In this study, a multi-agent coordination problem with steady-state regulation constraints is investigated for a class of non-linear systems. Unlike the existing leader-following coordination formulations, a reference signal is not given by a dynamic autonomous leader but determined as the optimal solution of a distributed optimisation problem. Furthermore, the authors consider a global constraint having noisy data observations for the optimisation problem, which implies that the reference signal is not trivially available with the existing optimisation algorithms. To handle these challenges, the authors present a passivity-based analysis and design approach by using only local objective function, local data observation and exchanged information from their neighbours. The proposed distributed algorithms are shown to achieve the optimal steady-state regulation by rejecting the unknown observation disturbances for passive non-linear agents, which are persuasive in various practical problems. Applications and simulation examples are then given to verify the effectiveness of the proposed design.

关键词： distributed control nonlinear control systems optimisation multi-robot systems mobile robots distributed algorithms control system analysis control system synthesis distributed coordination nonlinear multiagent systems regulation constraints multiagent coordination problem passive nonlinear agents optimal steady-state regulation distributed algorithms information exchange local data observation local objective function passivity-based design approach passivity-based analysis approach noisy data observations global constraint distributed optimisation problem optimal solution reference signal steady-state regulation constraints

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distributed Contaminant Detection and Isolation for Intelligent Buildings

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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 2018年第6期26卷 1925-1941页

作者： Kyriacou, Alexis Michaelides, Michalis P. Reppa, Vasso Timotheou, Stelios Panayiotou, Christos G. Polycarpou, Marios M. Univ Cyprus Dept Elect & Comp Engn KIOS Res & Innovat Ctr Excellence CY-1678 Nicosia Cyprus Cyprus Univ Technol Dept Elect Engn Comp Engn & Informat CY-3036 Lemesos Cyprus

The automatic preservation of the indoor air quality (IAQ) is an important task of the intelligent building design in order to ensure the health and safety of the occupants. The IAQ, however, is often compromised by various airborne contaminants that penetrate the indoor environment as a result of accidents or planned attacks. In this paper, we provide the detailed analysis, implementation, and evaluation of a distributed methodology for detecting and isolating multiple contaminant events in large- scale buildings. Specifically, we consider the building as a collection of interconnected subsystems, and we design a contaminant event monitoring software agent for each subsystem. Each monitoring agent aims to detect the contaminant and isolate the zone where the contaminant source is located, while it is allowed to exchange information with its neighboring agents. For configuring the subsystems, we implement both exact and heuristic partitioning solutions. A main contribution of this paper is the investigation of the impact of the partitioning solution on the performance of the distributed contaminant detection and isolation (CDI) scheme with respect to the detectability and isolability of the contaminant sources. The performance of the proposed distributed CDI methodology is demonstrated using the models of real building case studies created on CONTAM.(1)

关键词： Contaminant detection distributed algorithms fault diagnosis indoor air quality (IAQ) monitoring intelligent buildings

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Optimum energy resource scheduling in a microgrid using a distributed algorithm framework

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SUSTAINABLE CITIES AND SOCIETY 2018年 37卷 222-231页

作者： Rokni, Seyed Ghasem Mirbabaee Radmehr, Masoud Zakariazadeh, Alireza Islamic Azad Univ Aliabad Katoul Branch Dept Elect Engn POB 49417-93451 Aliabad Katoul Iran Univ Sci & Technol Mazandaran Dept Elect & Comp Engn POB 48518-78195 Behshahr Iran

Smart Energy Management System (SEMS) as the mastermind of microgrid is a robust software to manage both demands and generation units. Moreover, SEMS sets optimal regulations between different energy resources. A centralized solution for MG energy management system requires high computational capabilities due to a nonlinear and discrete nature of the problem. In this paper, a distributed energy management system called Alternating Direction Method of the multiplier (ADMM) has been proposed in order to jointly schedule the central controller as well as local controllers. The algorithm considers optimal power flow equations within the distributed energy management problem. The proposed distributed algorithm has been investigated on a typical MG and the efficiency of the algorithm has been evidenced through case studies. Our findings show that the proposed method decrease the operational cost of MG.

关键词： distributed algorithms Micro-grid Optimization Energy management system Dual decomposition Energy scheduling

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A distributed Short-Term Load Forecasting Method Based on Local Weather Information

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IEEE SYSTEMS JOURNAL 2018年第1期12卷 208-215页

作者： Liu, Dunnan Zeng, Long Li, Canbing Ma, Kunlong Chen, Yujiao Cao, Yijia Elect Power Univ Dept Econ & Management Beijing 100000 Peoples R China Hunan Univ Dept Elect Engn Changsha 410000 Hunan Peoples R China Jinhua Power Supply Co State Grid Corp China Jinhua 321000 Peoples R China

A centralized forecasting method is difficult to accurately follow load variation and weather diversity throughout the region in a bulk power system that covers a large geographical area. A distributed load forecasting method based on local weather information is proposed in this paper. First, the bulk power system is partitioned into some subnets based on local weather information. Second, separate forecasting models are established for subnets. These models are selected from load forecasting model base, which includes neural network, autoregressive integrated moving average model, autoregressive and moving average, gray model, and so on. Cosine distance is used to evaluate the similarity between vectors of influencing factors, so that representative samples can be selected from large data sets as training set for local load forecasting models. Finally, a system load forecasting model is developed to aggregate local load forecasts. Case study shows the advantages of the proposed method in a bulk power system.

关键词： Data mining distributed algorithms forecasting power system management prediction methods

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A distributed Intersection Management Protocol for Safety, Efficiency, and Driver's Comfort

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IEEE INTERNET OF THINGS JOURNAL 2018年第3期5卷 1924-1935页

作者： Liang, Xiaoyuan Yan, Tan Lee, Joyoung Wang, Guiling New Jersey Inst Technol Dept Comp Sci Newark NJ 07102 USA Ant Financial Technol Lab Hangzhou 310000 Peoples R China New Jersey Inst Technol Dept Civil & Environm Engn Newark NJ 07102 USA

Improving safety and convenience is always the top priority in designing today's intelligent transportation system. In this paper, we study the problem of how to manage vehicle traffic at intersections by jointly considering safety, driver's comfort, and efficiency, in vehicular ad hoc networks. We propose a distributed intersection management protocol (DIMP), which distributedly coordinates vehicle traffic from different directions by making vehicles exchange critical driving information and adaptively react based on the information. DIMP dynamically guides vehicles to adjust their speed in a way such that both safety and driver's comfort are satisfied. By following DIMP, vehicles can pass the intersections safely and efficiently at a comfortable speed during acceleration/deceleration. We extensively evaluate DIMP, and the evaluation results show that DIMP is both effective and efficient in managing vehicle traffic at intersections.

关键词： Automotive engineering distributed algorithms vehicular ad hoc networks vehicle safety

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A distributed Algorithm for Solving Positive Definite Linear Equations Over Networks With Membership Dynamics

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2018年第1期5卷 215-227页

作者： Lu, Jie Tang, Choon Yik Shanghai Tech Univ Sch Informat Sci & Technol Shanghai 200031 Peoples R China Univ Oklahoma Sch Elect & Comp Engn Norman OK 73019 USA

This paper considers the problem of solving a symmetric positive definite system of linear equations over a network of agents with arbitrary asynchronous interactions and membership dynamics. The latter implies that each agent is allowed to join and leave the network at any time, for infinitely many times, and lose all its memory upon leaving. We develop Subset Equalizing (SE), a distributed asynchronous algorithm for solving such a problem. To design and analyze SE, we introduce a novel time-varying Lyapunov-like function, defined on a state space with changing dimension, and a generalized concept of network connectivity, capable of handling such interactions and membership dynamics. Based on them, we establish the boundedness, asymptotic convergence, and exponential convergence of SE, along with a bound on its convergence rate. Finally, through extensive simulation, we show that SE is effective in a volatile agent network and that a special case of SE, termed Groupwise Equalizing, is significantly more bandwidth/energy efficient than two existing algorithms in multi-hop wireless networks.

关键词： distributed algorithms dynamic networks multi-agent systems

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Formation Control of Multiple Unmanned Aerial Vehicles by Event-Triggered distributed Model Predictive Control

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IEEE ACCESS 2018年 6卷 55614-55627页

作者： Cai, Zhihao Zhou, Hui Zhao, Jiang Wu, Kun Wang, Yingxun Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Beihang Univ Flying Coll Beijing 100191 Peoples R China

This paper proposes an event-triggered model predictive control (MPC) scheme for the formation control of multiple unmanned aerial vehicles (UAVs). A distributed MPC framework is designed in which each UAV only shares the information with its neighbors, and the obtained local finite-horizon optimal control problem (FHOCP) can be solved by a swarm intelligent optimization algorithm. An event-triggered mechanism is proposed to reduce the computational burden for the distributed MPC scheme, which takes into consideration the predictive state errors as well as the convergence of cost function. Furthermore, a safedistance-based strategy for no-fly zone avoidance is developed and integrated into the local cost function for each FHOCP. Numerical simulations show that the proposed event-triggered distributed MPC is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.

关键词： Unmanned aerial vehicles (UAVs) formation control distributed algorithms predictive control event-triggered no-fly zone avoidance

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distributed Stopping for Average Consensus in Digraphs

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2018年第3期5卷 957-967页

作者： Manitara, Nicolaos E. Hadjicostis, Christoforos N. Univ Cyprus Dept Elect & Comp Engn CY-1678 Nicosia Cyprus

We consider how iterative strategies for asymptotic average consensus in directed graphs (digraphs) can be adapted so that the nodes can determine, in a distributed fashion, a stopping criterion that allows them to terminate the execution of the iteration when approximate average consensus has been reached. The nodes are said to have reached approximate average consensus when each of them has a value that is close (in a way that we precisely define) to the desirable average. In a digraph, the absence of bidirectional communication links makes this task particularly challenging, due to the presence of asymmetric information (for a pair of nodes, only one of them may be aware of a discrepancy and may have no direct way of informing the other). The proposed algorithms can be used to cap the number of transmissions that are required in order to reach (approximate) average consensus, and we provide simulation studies that analyze performance with respect to this metric, and provide comparisons against existing work.

关键词： Approximate average consensus distributed algorithms distributed stopping multi-agent control

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A distributed Algorithm for Computing a Common Fixed Point of a Finite Family of Paracontractions

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2018年第9期63卷 2833-2843页

作者： Fullmer, Daniel Morse, A. Stephen Yale Univ Dept Elect Engn New Haven CT 06520 USA

A distributed algorithm is described for finding a common fixed point of a family of m > 1 nonlinear maps M-i : R-n -> R-n assuming that each map is a paracontraction and that at least one such common fixed point exists. The common fixed point is simultaneously computed by m agents assuming each agent i knows only M-i , the current estimates of the fixed point generated by its neighbors, and nothing more. Each agent recursively updates its estimate of a fixed point by utilizing the current estimates generated by each of its neighbors. Neighbor relations are characterized by a time-varying directed graph N(t). It is shown under suitably general conditions on N(t), that the algorithm causes all agent estimates to converge to the same common fixed point of the m nonlinear maps.

关键词： distributed algorithms multi-agent systems nonlinear dynamical systems optimization

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