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Dynamic multi-team antagonistic games model with incomplete information and its application to multi-UAV

IEEE/CAA Journal of Automatica Sinica 2015年第1期2卷 74-84页

作者： Zha, Wenzhong Chen, Jie Peng, Zhihong School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

At present, the studies on multi-team antagonistic games (MTAGs) are still in the early stage, because this complicated problem involves not only incompleteness of information and conflict of interests, but also selection of antagonistic targets. Therefore, based on the previous researches, a new framework is proposed in this paper, which is dynamic multi-team antagonistic games with incomplete information (DMTAGII) model. For this model, the corresponding concept of perfect Bayesian Nash equilibrium (PBNE) is established and the existence of PBNE is also proved. Besides, an interactive iteration algorithm is introduced according to the idea of the best response for solving the equilibrium. Then, the scenario of multiple unmanned aerial vehicles (UAVs) against multiple military targets is studied to solve the problems of tactical decision making based on the DMTAGII model. In the process of modeling, the specific expressions of strategy, status and payoff functions of the games are considered, and the strategy is coded to match the structure of genetic algorithm so that the PBNE can be solved by combining the genetic algorithm and the interactive iteration algorithm. Finally, through the simulation the feasibility and effectiveness of the DMTAGII model are verified. Meanwhile, the calculated equilibrium strategies are also found to be realistic, which can provide certain references for improving the autonomous ability of UAV systems. © 2014 Chinese Association of Automation.

关键词： Genetic algorithms

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Attitude control of Multiple Rigid Bodies with Uncertainties and Disturbances

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IEEE/CAA Journal of Automatica Sinica 2015年第1期2卷 2-10页

作者： Yuanqing Xia Ning Zhou Kunfeng Lu Yong Li the School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology the Qian Xuesen Laboratory of Space Technology China Academy of Space Technology

Decentralized attitude synchronization and tracking control for multiple rigid bodies are investigated in this paper. In the presence of inertia uncertainties and environmental disturbances, we propose a class of decentralized adaptive sliding mode control laws. An adaptive control strategy is adopted to reject the uncertainties and disturbances. Using the Lyapunov approach and graph theory, it is shown that the control laws can guarantee a group of rigid bodies to track the desired time-varying attitude and angular velocity while maintaining attitude synchronization with other rigid bodies in the formation. Simulation examples are provided to illustrate the feasibility and advantage of the control algorithm. © 2014 Chinese Association of Automation.

关键词： Adaptive control systems Algorithms Attitude control Environmental regulations Graph theory Rigid structures Sliding mode control Synchronization

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Solving the uncertain multi-objective multi-stage weapon target assignment problem via MOEA/D-AWA

Solving the uncertain multi-objective multi-stage weapon tar...

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Congress on Evolutionary Computation

作者： Juan Li Jie Chen Bin Xin Lihua Dou Zhihong Peng School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing P.R.China

ISBN: (纸本)9781509006243

The weapon target assignment (WTA) problem is a fundamental problem arising in defense-related applications of operations research. And the multi-stage weapon target assignment (MWTA) problem is the basis of dynamic weapon target assignment (DWTA) problems which commonly exist in practice. The MWTA problem considered in this paper is with uncertainties, namely the uncertain MWTA (UMWTA) problem, and is formulated into a multi-objective constrained combinatorial optimization problem with two competing objectives. Apart from maximizing damage to hostile targets, this paper follows the principle of minimizing ammunition consumption under the assumption that each element of the kill probability matrix follows four different probability distributions. In order to tackle the two challenges, i.e., multi-objective and the uncertainty, the multi-objective evolutionary algorithm based on decomposition with adaptive weight adjustment (MOEA/D-AWA) and the Max-Min robust operator are adopted to solve the problem efficiently. Then comparison studies between the MOEA/D-AWA and a single objective solver used for a relaxed formulation on solving both certain and uncertain instances of two different scaled MWTA problems which include four uncertain scenarios are conducted. Numerical results show that MOEA/D-AWA outperforms the single objective solver on solving both certain and uncertain multi-objective MWTA problems discussed in this paper. Comparisons between the results of the certain and uncertain formulation also indicate the necessity of the robust formulation of practical problems.

关键词： Weapons Uncertainty Discrete wavelet transforms Optimization Robustness decision making Evolutionary computation

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Adaptive key SURF feature extraction and application in unmanned vehicle dynamic object recognition

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Journal of Beijing Institute of Technology 2015年第1期24卷 83-90页

作者：杜明芳王军政李静李楠李多扬 Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Automation School Beijing Union University

A new method based on adaptive Hessian matrix threshold of finding key SRUF （ speeded up robust features） features is proposed and is applied to an unmanned vehicle for its dynamic object recognition and guided navigation. First, the object recognition algorithm based on SURF feature matching for unmanned vehicle guided navigation is introduced. Then, the standard local invariant feature extraction algorithm SRUF is analyzed, the Hessian Metrix is especially discussed, and a method of adaptive Hessian threshold is proposed which is based on correct matching point pairs threshold feedback under a close loop frame. At last, different dynamic object recognition experi- ments under different weather light conditions are discussed. The experimental result shows that the key SURF feature abstract algorithm and the dynamic object recognition method can be used for un- manned vehicle systems.

关键词： dynamic object recognition key SURF feature feature matching adaptive Hessianthreshold unmanned vehicle

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Autonomous landing of a quadrotor on an UGV

Autonomous landing of a quadrotor on an UGV

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IEEE International Conference on Mechatronics and Automation

作者： Mengyin Fu Kuan Zhang Yang Yi Chao Shi Nanjing University of Science and Technology Nanjing China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

ISBN: (纸本)9781509023974

This paper provides a complete solution for landing a quadrotor Unmanned Aerial Vehicle (UAV) on an Unmanned Ground Vehicle (UGV) in the outdoor environment. An image-based visual servo control law and a GPS-based navigation method are proposed, and the former method acquires the visual feedback from the camera attached to the quadrotor, while the latter strategy is used when the visual feedback is absent. For achieving more precise and stable performance in visually guided landing process, we design a specific landing marker that can provide different features as the distance between the quadrotor and landing target changes. Meanwhile, the corresponding detection and recognition algorithms are raised. Finally, a simulation experiment is carried out to validate the proposed vision algorithms and control strategies.

关键词： Visualization Cameras Unmanned aerial vehicles Mathematical model Land vehicles Navigation Servosystems

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Stability Analysis of Event-triggered Networked control systems with Time-Varying Delay 34

Stability Analysis of Event-triggered Networked Control Syst...

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第三十四届中国控制会议

作者： WANG Zhao SUN Jian CHEN Jie School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467374439

Networked control systems(NCSs) are facing a great challenge from the limitation of network communication resources. Event-triggered control(ETC) is often used to reduce the amount of communications while still keeping a satisfactory performance of the system, by transmitting the state measurements only when an event-triggered condition is met. However,some network-induced problems would happen inevitably, such as communication delay. The delay can degrade the control performance significantly and can even lead to instability. In this paper, we study an NCS considering both ETC and time-varying delay, which is rare in the literature. We formulate the system as a discretized piecewise linear system with exponential uncertainty. Then the model is embedded in a polytopic approximation with better structure suitable for stability *** conditions are derived in terms of linear matrix inequalities(LMIs). Finally, the developed method is illustrated by a numerical example.

关键词： Networked control system,event-triggered control,time-varying delay,piecewise linear system,polytopic approximation,stability

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Consensus for networked multi-agent systems with unknown communication delays

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Journal of the Franklin Institute 2016年第16期353卷 4176-4190页

作者： Xiaoyu Liu Lihua Dou Jian Sun Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing 100081 PR China School of Automation Beijing Institute of Technology 100081 P.R. China

The problem of consensus for linear discrete-time networked multi-agent systems with directed topologies and communication delays is investigated in this paper. The communication delays are assumed to be constant but unknown. A consensus protocol is designed to compensate for the unknown delays based on the networked predictive control scheme. A sufficient condition for the consensus of multi-agent systems is derived. Finally, a numerical example is given to illustrate that the consensus protocol proposed in this paper is effective.

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Iterative search with emulating nodes' local movement on range-free sensor network localization 34

Iterative search with emulating nodes' local movement on ran...

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第三十四届中国控制会议

作者： QIAO Dapeng GUO Zongben MA Hongwei SHI Shuguang School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Aerospace Control Devices

ISBN: (纸本)9781467374439

This paper proposes an iterative evolutionary algorithm with emulating nodes' local movement for searching the best localization accuracy in range-free scenario. All localization methods face a trade-off between the solution quality and computation cost. When sensor network localization in range-free scenario is considered as a constraint satisfaction problem, localization will reach the highest accuracy but with huge computation complexity. To solve the constraint satisfaction, some characteristics that only exist in range-free localization problem are utilized as heuristics in the search of nodes' positions. They are summarized as simple and complex movement to emulate nodes' local movement, and proved to be effective to find a suitable searching direction and jump out of local-minimums existing in the localization. Those emulations are then included in each iteration of a two-objective evolutionary algorithm minimizing the number of node-pairs with violated connectivity, as well as the value quantitating how worse of the violations. Simulation results show that the proposed algorithm can greatly decrease the reach high-accurate positions within limited iterations.

关键词： Wireless sensor network,Localization,Local movement,Evolutionary algorithm,Non-convex,Connectivity

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The paralleleye dataset: Constructing large-scale artificial scenes for traffic vision research

arXiv

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arXiv 2017年

作者： Li, Xuan Wang, Kunfeng Tian, Yonglin Yan, Lan Wang, Fei-Yue School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266000 China Department of Automation University of Science and Technology of China Hefei230027 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

Video image datasets are playing an essential role in design and evaluation of traffic vision algorithms. Nevertheless, a longstanding inconvenience concerning image datasets is that manually collecting and annotating large-scale diversified datasets from real scenes is time-consuming and prone to error. For that virtual datasets have begun to function as a proxy of real datasets. In this paper, we propose to construct large-scale artificial scenes for traffic vision research and generate a new virtual dataset called "ParallelEye". First of all, the street map data is used to build 3D scene model of Zhongguancun Area, Beijing. Then, the computer graphics, virtual reality, and rule modeling technologies are utilized to synthesize large-scale, realistic virtual urban traffic scenes, in which the fidelity and geography match the real world well. Furthermore, the Unity3D platform is used to render the artificial scenes and generate accurate ground-truth labels, e.g., semantic/instance segmentation, object bounding box, object tracking, optical flow, and depth. The environmental conditions in artificial scenes can be controlled completely. As a result, we present a viable implementation pipeline for constructing large-scale artificial scenes for traffic vision research. The experimental results demonstrate that this pipeline is able to generate photorealistic virtual datasets with low modeling time and high accuracy labeling. Copyright © 2017, The Authors. All rights reserved.

关键词： Pipelines

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An overview of recent progress in high-order nonholonomic chained system control and distributed coordination

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Journal of control and decision 2015年第1期2卷 64-85页

作者： Jie Huang Jie Chen Hao Fang Lihua Dou School of Automation Beijing Institute of TechnologyBeijingChina State Key Laboratory of Intelligent Control and Decision of Complex Systems BeijingChina Fujian Institute of Education FuzhouChina

This paper reviews some main results and progress concerning with nonholonomic system control,especially focusing on the networked chained system *** controllability of nonholonomic system,the control method of nonholonomic system,the chained form transformation,the basic graph theory for multi-agent systems are recalled,*** important definitions,lemmas,theorems and dynamics are *** the consensus and formation control problems for networked nonholonomic chained systems are ***,some open questions are proposed.

关键词： distributed coordination multi-agent system nonholonomic system chained system high-order

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