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3D Multi-Constraint Route Planning for UAV Low-altitude Penetration Based on Multi-Agent Genetic Algorithm

IFAC Proceedings Volumes 2011年第1期44卷 11821-11826页

作者： Jin-Ping Wu Zhi-Hong Peng Jie Chen School of Automation Beijing Institute of Technology Beijing 100081 Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education P. R. China

Abstract Low-altitude penetration is one of the most important military applications of Unmanned Aerial Vehicles (UAVs). 3D route planning, which is a complex multi-objective optimization problem with multiple constraints, is the key technology of UAV low altitude-penetration. A 3D route planning method based on Multi-Agent Genetic Algorithm (MAGA) is proposed in this paper. Specifically, a dynamic route representation form is proposed to improve the flight route accuracy. An efficient constraint handling method is used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation. More importantly, details are presented to show how to apply MAGA to 3D route planning while some necessary improvements of MAGA are proposed to make it more efficient. Simulation and analysis illustrate the effectiveness of this method.

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Medical Image Segmentation Using Mean Shift Algorithm and General Edge Detection

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IFAC Proceedings Volumes 2011年第1期44卷 9656-9661页

作者： Jinghua Lu Jie Chen Juan Zhang Lihui Zou School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China (Tel: 86-010-68913795)

Abstract The segmentation of the medical image faces the challenges of the existence of large number of diverse structures of human anatomy and inevitable artifacts induced from the imaging procedure. In this paper we treat some structures and artifacts as general edge features, and introduce the edge information into the mean shift segmentation algorithm in both clustering and the fusion steps. Considering the medical images as two dimensional signals, the general edge can be detected and described with its local spatial frequency properties. The segmentation results show the improvement in preserving the completeness of details while sketching the overall structures.

关键词： image segmentation signal processing medical application

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Online Path Planning for UAV Using an Improved Differential Evolution Algorithm

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IFAC Proceedings Volumes 2011年第1期44卷 6349-6354页

作者： Xing Zhang Jie Chen Bin Xin Hao Fang School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China Tel: 86-10-68912464-22

Abstract This paper presents a 3D online path planning algorithm for unmanned aerial vehicle (UAV) flying in partially known hostile environment. In order to provide a smooth fight route for UAV, the algorithm adopts B-Spline curve to describe UAV's path whose control points are optimized by an improved differential evolution algorithm. The planner gradually produces a smooth path for UAV from starting location to its target. Regarding path planning performance, the proposed improved diferential evolution based planner is compared with its three competitors which are based on classical differential evolution, genetic algorithm and particle swarm optimization, respectively. Numerical simulation demonstrates that the proposed UAV path planner not only produces high-quality feasible flight routes for UAV, but also obviously outperforms its competitors.

关键词： UAV online path planning differential evolution B-Spline

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Differential evolution with adaptive population size combining lifetime and extinction mechanisms

Differential evolution with adaptive population size combini...

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作者： Zhang, Chunmei Chen, Jie Xin, Bin Cai, Tao Chen, Chen School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing China School of Electronic Information Engineering Taiyuan University of Science and Technology Shanxi China Department of Automation Tsinghua University Beijing China

ISBN: (纸本)9788995605646

Differential Evolution (DE) is a simple and efficient numerical optimization method. Most DE variants in the literature adopt fixed population size. This paper incorporates into DE the mechanisms of lifetime and extinction which regulate DE's population size in an adaptive manner. The population size is adjusted according to the online progress of fitness improvement. Two schemes of inserting new individuals are proposed to match different mechanisms respectively. The performance of these innovations is examined through the optimization of benchmark problems. The results show that the proposed adaptive population sizing strategy is efficient for improving the convergence and efficiency of the DE. © 2011 Asian control Association.

关键词： Optimization

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Multi-group consensus via pinning control with non-linear heterogeneous agents

Multi-group consensus via pinning control with non-linear he...

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Asian control Conference

作者： Wei Sun YongQiang Bai Rui Jia Rui Xiong Jie Chen Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China Beijing Institute of Technology Beijing Beijing CN

The agents connected by networks are capable to reach a prescribed state if only a small fraction of them are controlled with feedback information. The present work tries to stabilize groups of non-linear agents in a directed network onto a stable state with several equilibriums. The agent dynamics can be identical or heterogeneous. But the agents in the same group share a same non-linear model. The conditions to reach multiple consensus states are provided under both non-switching and switching topologies. The maximum number of heterogeneous equilibriums is discussed. It is proved theoretically and by simulations that under certain conditions, pinning control can lead a multi-group network to reach a multi-valued consensus state.

关键词： Topology Network topology Switches Eigenvalues and eigenfunctions Convergence Laplace equations

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Cooperative Pollution Supervising and Neutralization with Multi-actuator-sensor Network

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Acta Automatica Sinica 2011年第1期37卷 107-113页

作者： Wei SUN Li-Hua DOU Hao FANG School of Automation Beijing Institute of Technology Beijing 100081 P.R. China Key Laboratory of Complex System Intelligent Control and Decision (Beijing Institute of Technology) Ministry of Education Beijing 100081 P.R. China

The present work considers a scenario that a multi-actuator-sensor network neutralizes poisonous gas and tracks the pollution sources in a bounded area. A novel algorithm is proposed to minimize the system information uncertainty while reaching balance on the workload of actuators. The method combines the centroidal Voronoi tessellations (CVT) with a consensus strategy. The CVT of the region insures a local optimal position configuration of the actuators, thus the sensing uncertainty can be minimized. The consensus algorithm utilizes the connection information among actuators, and helps them to reach a common workload. The consensus component will be terminated or suppressed when the workload is averaged. The consensus component may postpone the realization of CVT configuration. But it could be viewed as a perturbation that helps the actuators jump out of the local optimal CVT configuration. As a result, the information uncertainty may be further reduced. Comparison is drawn between the pure CVT algorithm and the method with consensus strategy. Simulations validated the proposed approach.

关键词： Voronoi tessellation position configuration workload assignment multi-agent system

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Electronic compass calibration based on Adaptive Differential Evolution Algorithm-Fourier Neural Network

Electronic compass calibration based on Adaptive Differentia...

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作者： Gong, Kun Deng, Fang Chen, Jie School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

ISBN: (纸本)9789881725592

Based on the comparison of several common methods of electronic compass error compensation, this paper presents a new error compensation method based on Adaptive Differential Evolution-Fourier Neural Networks (ADE-FNN) to improve the measurement accuracy of electronic compass. This method uses Fourier neural network to model electronic compass error, and adopts Adaptive Differential Evolution to optimize the weights of neural network, and get more exact error model to compensate measured values. The compensation object is the common electronic compass composed by two-dimensional magnetic resistance sensor. Compared with the compensation effect of Least-square method, BP neural network and Fourier neural networks, It proves that the mode of this method can realize the high precision in the sample space mapping and high non-linear approximation ability, and this method has faster convergence rate, can avoid falling into local minima, reduces the training error, and improves error compensation accuracy. This method decreases the error range from 3.4° ∼ 25.2° before compensation to -0.20° ∼ 0.72°, and the average of the absolute error is 0.30°. Repeatability tests also proved the compensation plan have a good consistency. © 2011 Chinese Assoc of Automati.

关键词： Error compensation

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Adaptive sliding mode control of electromechanical actuator with improved parameter estimation

Adaptive sliding mode control of electromechanical actuator ...

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Asian control Conference

作者： Hao Li Yongqiang Bai Zhong Su School of Automation Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

An adaptive sliding mode control scheme for electromechanical actuator has been presented. The adaptive control strategy can estimate the uncertain parameters and adaptively compensate the modeled dynamical uncertainties, while the sliding mode control method overcomes the unmodelled dynamics. In the adaptive law an equivalent output injection of the sliding mode observer which contains the parameter estimation error is used, and estimates of parameters can approximate the true values without prediction-error that is typically used in compositive adaptive law. Due to the improved estimation of uncertain parameters, the sliding mode law can robustifies the design against model uncertainties with a small swithcing gain. Stability of the system with the proposed approach has been proved and it has also been shown that the system states can reach the sliding mode in finite time. Finally, the effectiveness of the proposed control scheme has been exhibited via simulation examples.

关键词： Parameter estimation Sliding mode control Actuators Aerodynamics Robustness Adaptive control Uncertainty

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Decentralized Loading Coordinations for Large-population Plug-in Electric Vehicles and a few controllable Bulk Loads

Decentralized Loading Coordinations for Large-population Plu...

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IEEE Conference on decision and control

作者： Xiaokun Yin Zhongjing Ma Lei Dong School of Automation Beijing Institute of Technology (BIT) Beijing China School of Automation BIT and the Key Laboratory of Complex System Intelligent Control and Decision (BIT) Ministry of Education Beijing China School of Automation BIT

ISBN: (纸本)9781612848006

This paper studies the loading coordinations for large-population autonomous individual (plug-in) electric vehicles (EVs) and a few controllable bulk loads, e.g. EV fleets, pumped storage hydro units, and so on. Due to the computational infeasibility of the centralized coordination methods to the underlying large-population systems, in this paper we develop a novel game-based decentralized coordination strategy. Following the proposed decentralized strategy update mechanism and under some mild conditions, the system may quickly converge to a nearly valley-fill Nash equilibrium. The results are illustrated with numerical examples.

关键词： (Plug-in) electric vehicles Loading coordination Nash equilibrium (NE) Valley-fill

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Path planning of multiple UAVs low-altitude penetration based on improved Multi-agent Coevolutionary Algorithm

Path planning of multiple UAVs low-altitude penetration base...

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作者： Peng, Zhi-Hong Sun, Lin Chen, Jie Wu, Jin-Ping School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9789881725592

In order to solve the multi-UAV cooperative path planning problem of low-altitude penetration, the paper proposes an improved Multi-agent Coevolutionary Algorithm (IMACEA), which introduces co-evolution mechanism based on Multi-agent Genetic Algorithm(MAGA) to find the optimal solution of multi-objective optimization problem by combing the agents' perception and response capabilities of environment, information sharing capacity among multi-agent systems and heuristic search ability of heuristic search. At the same time, we use absolute Cartesian coordinates and relative polar coordinates coding method to reduce the search space and speed up the convergence rate. To adapt to multi-path planning problems of UAVs, new multi-agent co-evolution operators are designed. Finally, the proposed algorithm is used for multiple UAVs offline and online route planning, simulation results show the effectiveness of the algorithm. © 2011 Chinese Assoc of Automati.

关键词： Motion planning

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