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An Improved-WM Method Based on Optimization of Centers of Output Fuzzy Subsets for Fuzzy Rules

IFAC-PapersOnLine 2017年第1期50卷 7369-7374页

作者： Jin Y. Cao W. Wu M. She J. Yuan Y. School of Automation China University of Geosciences Wuhan 430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan

The generation of fuzzy rules from samples is significant for fuzzy modelling. To improve the robustness of Wang-Mendel (WM) method, an improved WM method to extract fuzzy rules from all the regularized sample data was proposed. However, the accuracy of the model with this method is degraded for the conflicting rules with small difference between support degrees. And the output subsets can only be chosen from the pre-defined ones. To solve these problems, we develop an improved-WM method based on optimization of centers of output fuzzy subsets for fuzzy rules (COiWM). This method adopts the fuzzy c-means (FCM) clustering algorithm to divide the input and output spaces, and the improved WM method which replaces the original data by regularized data is used to calculate the support degrees. Then the support degrees are used as weights to optimize the centers of output fuzzy subsets with a method of weighted averages, so as to enhance the accuracy of a fuzzy model. Experimental results of a case study on short term daily maximum electric load forecasting prove that our proposed method enhances the accuracy of a fuzzy model. © 2017

关键词： Accuracy Conflicting rules Fuzzy c-means clustering algorithm Fuzzy rules Wang-Mendel method

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An improved tiny SLAM method for simultaneous localization and mapping 5

An improved tiny SLAM method for simultaneous localization a...

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5th International Workshop on Advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Li, Dan-Yun Liu, Cong-Jun Liu, Zhen-Tao Feng, Zhi-Yong School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Hubei Key Laboratory of Advanced Technology of Automotive Parts Wuhan University of Technology Wuhan430070 China

TinySLAM algorithm is a simple 2D laser SLAM algorithm. However, in practical applications, it has higher error rate of mapping because of its simple filter. In this paper, an improved TinySLAM algorithm is proposed for simultaneous location and mapping. By adding a simple filter before the Monte Carlo simulation and then fusing the information from the odometer, the error in the positioning process can be reduced. Moreover, the introduced hybrid map cell model that can be compatible with ROS system, improves the response to dynamic obstacles, and reduces the mapping error rate further. Simulation using ROS system and Stage software is performed, from which the results show that the proposal has good effects comparing with TinySLAM, and the error rate is reduced so that the map built is closer to the actual environment.

关键词： Mapping

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The effect of waist twisting on walking speed of an amphibious salamander like robot

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Acta Mechanica Sinica 2016年第3期32卷 546-550页

作者： Xin-Yan Yin Li-Chao Jia Chen Wang Guang-Ming Xie Intelligent Control Laboratory College of EngineeringPeking University Key State Laboratory for Turbulence & Complex Systems College of Engineering Peking University

Amphibious salamanders often swing their waist to coordinate quadruped walking in order to improve their crawling speed. A robot with a swing waist joint, like an amphibious salamander, is used to mimic this locomotion.A control method is designed to allow the robot to maintain the rotational speed of its legs continuous and avoid impact between its legs and the ground. An analytical expression is established between the amplitude of the waist joint and the step length. Further, an optimization amplitude is obtained corresponding to the maximum stride. The simulation results based on automatic dynamic analysis of mechanical systems（ADAMS） and physical experiments verify the rationality and validity of this expression.

关键词： Terrestrial locomotion Step length Waist twisting Walking speed

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An Online Modeling Method for Formation Drillability Based on OS-Nadaboost-ELM Algorithm in Deep Drilling Process

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IFAC-PapersOnLine 2017年第1期50卷 12886-12891页

作者： Gan, Chao Cao, Weihua Wu, Min Chen, Xin Hu, Yule Wen, Guojun Gao, Hui Ning, Fulong Ding, Huafeng School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Adavanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Faculty of Engineering China University of Geosciences Wuhan430074 China School of Mechanical Engineering & Electronic Information China University of Geosciences Wuhan430074 China

To achieve safety, high quality, and efficiency in deep drilling, it is necessary to get formation drillability around the borehole during drilling-trajectory planning and intelligent drilling control. Since the drilling data have the characteristics of low value density and noise in the process of deep drilling, it is difficult to model formation drillability in deep drilling. In this paper, a new online modeling method for formation drillability based on online sequential nadaboost extreme learning machine (OS-Nadaboost-ELM) algorithm has been proposed. Firstly, the well logging parameters are chosen as the inputs of the model, whose output is formation drillability. Then, several ELM models are established and the outputs of these models are as weak learners. Then the weak learners are combined by Nadaboost algorithm in order to get a strong learner. Finally, the recursive least squares algorithm is used to adjust the model. The numerical test results show that, in both prediction accuracy and training efficiency aspects, the proposed method is better than other prediction methods such as multiple regression, gray method, back-propagation neural networks, Nadaboost extreme learning machine and online sequential extreme learning machine. Thus the prediction model serves as the online geological model to develop intelligent drilling systems. © 2017

关键词： E-learning

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Analysis of security in cyber-physical systems

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Science China. Technological Sciences 2017年第12期60卷 1975-1977页

作者： Chen Jie Zhang Fan Sun Jian School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081

In recent years, cyber-physical systems (CPSs) have received much attention from both the academic world and the industrial world, which refer to a deep integration and coordination of physical and computational resources [1,2]. Typical examples of CPSs can be found in smart grids, smart transportation systems, industrial control systems, water supply systems, and so on. Furthermore, many military systems are also CPSs. The key characteristic of CPSs is the integration of computing, control and communication. The increased interconnection between the cyber and physical spaces make CPSs vulnerable to various malicious attacks. A well-known example of an attack of CPSs is the Stuxnet which infected the control system of nuclear-fuel centrifuges of Bushehr nuclear power plant in Iran. Stuxnet makes people beware of the grave consequences of a cyber-attack on a CPS. Since many national critical infrastructures are applications of CPS, ensuring security and safety of such systems is of great importance.

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Stable walking of quadruped robot on unknown rough terrain

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Journal of Beijing Institute of Technology 2016年第4期25卷 463-472页

作者：何玉东王军政柯贤锋汪首坤 Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Quadruped robot is considered to be the most practical locomotion machine to negotiate uneven terrain, and shows superb stability during static walking. To improve the ability to go over rough terrain, this paper is focused on the stable walking and balance control of quadruped robots. 24 kinds of walking gaits are analyzed in order to derive the most stable and smoothest walking gait. Considering the inefficiency to model a terrain by its specified appearance, a uniform terrain model is established and by means of kinematic analysis, a method to adjust the body posture and center of gravity （COG） height is presented. Simulations demonstrate the effectiveness of the proposed meth- od and the improvement of the adaptation of quadruped robots on rough terrain.

关键词： quadruped robot unknown rough terrain walking gait body posture body center ofgravity （COG）

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Torque Ripple Reduction of a Modular-Stator Outer-Rotor Flux-Switching Permanent-Magnet Motor

Torque Ripple Reduction of a Modular-Stator Outer-Rotor Flux...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Jing Zhao Yun Zheng Congcong Zhu Hao Chen Liu Yang Key laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology Beijing China

In order to reduce the permanent magnet (PM) volume and combine the advantages of in-wheel motor, a novel modular-stator outer-rotor flux-switching permanent-magnet motor (MSOR-FSPM) whose PM volume is half of that in conventional outer-rotor flux-switching permanent-magnet (COR-FSPM) motor is proposed. However, cogging torque and torque ripple of MSOR-FSPM motor are especially worse due to the inherent double salient effect and the back-EMF harmonics caused by module stator structure. In this paper, structure and operation principle of MSOR-FSPM motor are described simply. Secondly, cogging torque and torque ripple are reduced by using traditional rotor two-step skewing method, but the result is unsatisfactory. Thirdly, a new rotor two-step skewing method is adopted since the ratio of back-EMF period to cogging torque period is the odd. Compared with traditional rotor step skewing method, the new method eliminates the even harmonics of back-EMF and remains the amplitude of fundamental waveform;the odd harmonics of cogging torque and electromagnetic torque are eliminated. Finally, the results of the new rotor step skewing method is verified by 3D finite element method (FEM) and further improved by embedding non-magnetic blocks in the middle of the stator and rotor.

关键词： Rotors Torque Forging Harmonic analysis Brushless motors Torque measurement AC motors

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design and analysis of a novel double-sided five-phase modular linear permanent magnet machine

Design and analysis of a novel double-sided five-phase modul...

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Annual Conference of Industrial Electronics Society

作者： keyu Guo Jing Zhao Xiangdong Liu Liu Yang Hao Chen Key laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology Beijing China

In this paper, in order to replace a conventional electric linear actuator which is consist of rotary PM machine and ball screw, a novel double-sided five-phase modular linear permanent magnet synchronous machine (MLPMSM) is proposed and designed with the same volume. The basic structure of the machine is firstly described and the major dimensions of one module are then optimized to acquire the largest thrust force. Through these methods, the average force of the MLPMSM reaches 206N, which is 58.4% larger than the conventional linear actuator. After that, the 5 th order harmonic in thrust ripple is analyzed and diminished by adjusting the distance between slot openings of the module. As the result the 5 th order harmonic is diminished greatly by 57%.

关键词： Force Optimization Stator cores Actuators Harmonic analysis Iron

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M4CD: A robust change detection method for intelligent visual surveillance

arXiv

引用

arXiv 2018年

作者： Wang, Kunfeng Gou, Chao Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Innovation Center for Parallel Vision Qingdao Academy of Intelligent Industries Qingdao266000 China Research Center for Computational Experiments Parallel Systems Technology National University of Defense Technology Changsha410073 China

In this paper, we propose a robust change detection method for intelligent visual surveillance. This method, named M4CD, includes three major steps. Firstly, a sample-based background model that integrates color and texture cues is built and updated over time. Secondly, multiple heterogeneous features (including brightness variation, chromaticity variation, and texture variation) are extracted by comparing the input frame with the background model, and a multi-source learning strategy is designed to online estimate the probability distributions for both foreground and background. The three features are approximately conditionally independent, making multi-source learning feasible. Pixel-wise foreground posteriors are then estimated with Bayes rule. Finally, the Markov random field (MRF) optimization and heuristic post-processing techniques are used sequentially to improve accuracy. In particular, a two-layer MRF model is constructed to represent pixel-based and superpixel-based contextual constraints compactly. Experimental results on the CDnet dataset indicate that M4CD is robust under complex environments and ranks among the top methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Pixels

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Adaptive optimal control for a class of uncertain systems with saturating actuators and external disturbance using integral reinforcement learning

Adaptive optimal control for a class of uncertain systems wi...

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Asian control Conference

作者： Jingang Zhao Minggang Gan Jie Chen Dongyang Hou Meng Zhang Yongqiang Bai State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing

ISBN: (纸本)9781509015740;9781509015733

The problem of adaptive optimal control for a class of nonlinear uncertain systems with saturating actuators and external disturbance is investigated in this paper. Considering the saturating actuators, a non-quadratic cost function is adopted. The key of this optimal control problem is to find the solution to the Hamilton Jacobi Bellman equation (HJB). An online intergral reinforcement learning (IRL) algorithm based-Neural Network (NN) is given to approximate the solution. Unlike traditional integral reinforcement learning algorithms, data onto a period of time stored together with current data are used to update the neural network weights in place of persistence of excitation (PE) condition. This method overcomes the shortcomings of the PE condition which is not easy to be checked online. Finally, numerical examples are given to show the effectiveness of the proposed methods.

关键词： Optimal control Actuators Nonlinear systems Approximation algorithms Artificial neural networks System dynamics

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