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Dynamic Modeling and Vibration Mode Analysis for an Industrial Robot with Rigid Links and Flexible Joints

Dynamic Modeling and Vibration Mode Analysis for an Industri...

引用

The 24th Chinese control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Yanhui Qiang Fengshui Jing Junfang Zeng Zengguang Hou State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Beijing Sciample Technology CO.LTDBeijing 100190 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese

Nowadays, most industrial robots have been designed to be mechanically stiff with rigid link. When a robot with heavy payload is running in fast motions, the residual vibrations of the end-effector are primary caused by joint flexibility. Therefore, the flexibility of joint cannot be neglected. This paper presents a systematic approach to dynamic modeling and residual vibration mode analysis for an industrial robot with rigid links and flexible joints (RLFJ). First, the flexibility of the joint is modeled as a torsional spring and the dynamic equations for this robot are derived by using Lagrange’s method. Then, to examine residual vibration properties of the system, numerical simulation is carried out. The following important conclusions are drawn from simulation results: (1) the proposed dynamic model can represent joint flexibility of industrial robot and the joint flexibility causes the residual vibration of the end-effector;(2) for a given RLFJ model, the residual vibration is mainly affected by the payload mass, path of the task and joint stiffness.

关键词： Dynamic Model Flexible Joint Residual Vibration Industrial Robot

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Adaptive Dynamic Programming with Stable Value Iteration Algorithm for Discrete-Time Nonlinear systems

Adaptive Dynamic Programming with Stable Value Iteration Alg...

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International Joint Conference on Neural Networks

作者： Qinglai Wei Derong Liu State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467314886

In this paper, a new stable value iteration adaptive dynamic programming (ADP) algorithm, named "θ-ADP" algorithm, is proposed for solving the optimal control problems of infinite horizon discrete-time nonlinear systems. By introducing a parameter θ in the iterative ADP algorithm, it is proved that any of iterative control obtained in the proposed algorithm can stabilize the nonlinear system which overcomes the disadvantage of traditional value iteration algorithms. Neural networks are used to approximate the performance index function and compute the optimal control policy, respectively, for facilitating the implementation of the iterative θ-ADP algorithm. Finally, a simulation example is given to illustrate the performance of the proposed method.

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H_∞ control of Unknown Discrete-Time Nonlinear systems with control Constraints Using Adaptive Dynamic Programming

H_∞ Control of Unknown Discrete-Time Nonlinear Systems with...

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International Joint Conference on Neural Networks

作者： Derong Liu Hongliang Li Ding Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467314886

In this paper, we solve the H_∞ robust optimal control problem for discrete-time nonlinear systems with control saturation constraints using the iterative adaptive dynamic programming algorithm. First, a heuristic dynamic programming algorithm is derived to solve the Hamilton-Jacobi-Isaacs equation associated with the H_∞ control problem, and a convergence analysis is provided. Then, a dual heuristic dynamic programming algorithm with nonquadratic performance functional is developed to overcome the control saturation constraints. Finally, to facilitate the implementation of the algorithm, four neural networks are used to approximate the unknown nonlinear system, the control policy, the disturbance policy, and the value function.

关键词： Standing Orders dynamic programming dynamic programming algorithm Nonlinear systems discrete-time control strategy Unknown Robust optimal control Self tuning

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Traffic signal controller based on mobile agent

Traffic signal controller based on mobile agent

引用

2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Chen, Cheng Li, Zhenjiang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan China

ISBN: (纸本)9781467324007

With mobile agent technology, multi-agent traffic management system is one effective approach to realize the demand-based control. Traffic signal controller is the base of traffic management system. Hence, the realization of traffic signal controller based on mobile agent is indispensable. In this paper, we detailed the traffic signal controller based on Mobile agent in CASIA. Meanwhile, test data about its performance is given. © 2012 IEEE.

关键词： controllers

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Artificial power system based on ACP approach

Artificial power system based on ACP approach

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Dong, Xisong Xiong, Gang Hou, Jiachen Fan, Dong State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan China

ISBN: (纸本)9781467324007

Modern power system is a typical multi-level complex giant system consisting of physical infrastructures, human operators, and social resources, etc. The conventional analytical methods and simulation systems can't provide sufficient guidance for its operation and management, because they are mainly based on physical models, natural phenomenon, or other existing control methods which are based on reductionism. ACP approach, mainly consisting of artificial systems (A), computational experiments (C) and parallel execution (P), which is based on holism and complex system theory, has its specific advantages in the research on power systems. In this article, ACP approach is applied to build up artificial power system (APS) by using multi-agent complex networks. With the help of APS, actual power system's control, scheduling, optimization and management can be improved further via providing theoretical guidance and technical support for the rolling optimizations in normal situations and emergency management in abnormal situations. As a case study, an APS constructed with actual data from North China power grid is constructed and its vulnerability is simulated and analyzed under random, dynamic and static attacks. © 2012 IEEE.

关键词： complex networks

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Learning weighted features for human action recognition

Learning weighted features for human action recognition

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International Conference on Pattern Recognition

作者： Wen Zhou Chunheng Wang Baihua Xiao Zhong Zhang Long Ma State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9781467322164

In traditional bag-of-words method, each local feature is treated evenly for representation. One disadvantage of this method is that it is not robust to noise, which makes the performance impaired. In this paper, a novel human action recognition approach which learns weights for features is proposed, where each feature is assigned a weight for human action representation. These weights are learned jointly with discriminative model. There are two advantages of our model. First, small weights are assigned to noise, which can help to reduce the effect of noise on representation of human action. Second, discriminative features, which are critical for human action recognition, are assigned large weights. Experimental results demonstrate the advantages of the proposed method.

关键词： Humans Noise Support vector machines Accuracy Kernel Feature extraction Noise measurement

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A dynamic user adaptive combination strategy for hybrid movie recommendation

A dynamic user adaptive combination strategy for hybrid movi...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Cai Chen Daniel Zeng State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

Movie recommendation is a very popular service in internet based movie related websites such as NetFlix, MovieLens. The performance of the recommendation plays the key role in the user experience. Existing works have shown that combining content based and collaborative filtering based algorithms is the best way for movie recommendation. Nevertheless, the performance of this hybrid algorithm is strongly depended on the strategy how to combine the basic pure algorithms. Existing works usually use a static combination strategy which may generate even worse performance for some users. To solve this problems, in this paper we propose a new item based hybrid algorithm that uses a dynamic user adaptive combination strategy. Besides, we also exploit the external open resources IMDB as the movie content data. Experiments on real datasets show that the dynamic user adaptive combination strategy can significantly enhance the performance of the recommendation and the external open resource IMDB is a very good information resource for recommendation.

关键词： Measurement History Algorithm design and analysis DH-HEMTs Filtering algorithms

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Artificial Transportation System constrution based on ontology-based knowledge base systems

Artificial Transportation System constrution based on ontolo...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Chen, Songhang Zhu, Fenghua State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songs han Lake Dongguan China

ISBN: (纸本)9781467324007

Artificial Transportation systems (ATS) provide a comprehensive perspective to study actual transportation systems, which are a kind of open and complex giant system referring to diverse engineering and social disciplines. To make use of achievements from related research fields, ontology for ATS is constructed in this paper. Besides conceptual model involved in modeling and applications of ATS, the compatibility with other ontology is considered. Further, an ontological knowledge base with SOA (Service-Oriented Architecture) is designed to manage information and knowledge in ATS. The architecture and interfaces of the knowledge base are presented. Benefit from this, construction and applications of ATS can be conducted on a uniform information and knowledge platform. A case study about traffic jam pattern is demonstrated. © 2012 IEEE.

关键词： Ontology

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A survey of urban traffic coordination controls in intelligent transportation systems

A survey of urban traffic coordination controls in intellige...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Li, Shuangshuang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan 523808 China

ISBN: (纸本)9781467324007

The urban traffic coordination controls (UTCCs) can make full use of the mutual advantages of intersections, which makes it can improve the traffic access capacity and decrease the possibility of traffic congestion in intersections. This paper gives an overview of UTCCs. After reviewing the concept of UTCCs, we survey the several main hot topics in UTCCs: the correlation degree analysis of intersections, the division approach of traffic control subareas and the objects of coordination. This paper provides a survey of urban traffic coordination controls with the goal of promoting research in this area and concludes with some comments on future research directions. © 2012 IEEE.

关键词： Surveys

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Human action recognition by bagging data dependent representation

Human action recognition by bagging data dependent represent...

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International Conference on Pattern Recognition

作者： Wen Zhou Chunheng Wang Baihua Xiao Zhong Zhang Long Ma State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9781467322164

Traditional methods based on bag-of-word representation are easily affected by noise, and they also cannot handle the problem when a test distribution differs from the training distribution. In this paper, we propose a novel method for human action recognition by bagging data dependent representation. Different with traditional methods, the proposed method represents each video by several histograms. These histograms are obtained by bagging according to an estimated prior several times in both training and testing. The data dependent property of our method depends on the prior which reflects the training distribution. There are two advantages of the proposed method. First, it alleviates the distribution difference between training set and test set. Second, the bagging operation reduces noise and improves the performance significantly. Experimental results show the effectiveness of the proposed method.

关键词： Data structures Boolean functions Bagging Humans Training Accuracy Noise

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