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第三十二届中国控制会议

作者： Ma Li Li Xuebing Ding Shihong Zhang Jun School of Electrical and Information Engineering Jiangsu University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast University

ISBN: (纸本)9781479900305

The local/global Lipschitz continuity is always required when considering the stability of the cascaded systems. Different from the exiting methods proposed in the literature,this paper gives a method to deal with non-smooth cascaded *** using iISS property,some sufficient conditions for global asymptotic stability of the cascaded systems are derived. Then,based upon this,an interesting result of finite-time stability for cascaded systems is further *** proposed methods are verified by some academic examples.

关键词： Cascaded systems Stability Finite-time control

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Research on multi-dimensional data visualization analysis of large enterprise's purchasing fund

Research on multi-dimensional data visualization analysis of...

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

作者： Minhui Lv Hongxia Zhao Department of Equipment Economics and Management Naval University of Engineering Wuhan China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479960590

With the continuous development of data storage technology, the complexity, category and size of data increase sharply; on the other hand, the wide expansion of its application domain brings great challenges on the traditional data processing and analysis technology. In this paper, the data analysis and processing technology and its development status are introduced and by multi-dimensional data visualization analysis method and combining the knowledge of domain experts, the equipment purchasing fund data of a large enterprise is analyzed to provide reliable management decision to the investment and investment volume of business fund.

关键词： Investment Visualization Data mining

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Topological mapping and navigation based on visual sensor network

Topological mapping and navigation based on visual sensor ne...

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IEEE International Conference on Mechatronics and Automation

作者： Wenbo Yuan Zhiqiang Cao Min Tan Jingyu Liu State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China School of Electrical and Information Engineering Beijing jiaotong University Beijing China

ISBN: (纸本)9781479939800

In this paper, a novel topological mapping approach applied to the navigation mission is proposed based on visual sensor network. Firstly, the natural objects in the scene monitored by visual sensor network are recognized through the inference model based on structural features. Then, topological nodes are designed according to the recognized objects and their spatial structure information, and topological mapping will be fulfilled. On this basis, global localization for mobile robot in camera view can be implemented with HOG feature based detection and tracking. Finally, the robot can make motion decisions for navigation. Our approach does not rely on artificial landmarks and is tested in large-scale office scene. The effectiveness of the proposed approach is verified.

关键词： Visualization Robot sensing systems Navigation Cameras Image segmentation Feature extraction

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Computational experiments based on competitive influence diffusion model

Computational experiments based on competitive influence dif...

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

作者： Kainan Cui Xiaolong Zheng The School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479960590

Understanding the strategies to optimize/suppress information spreads under intense competition could provide important insights in a broad range of settings including viral marketing, emergency response and information system design. However, most of existing studies about competitive influence diffusion mainly focus on two-information competition mechanism. To date, the competitive influence maximization problem considering the mechanism of multi-information competition is still not well studied. In this paper, we conducted computational experiments to study the competitive influence maximization with multi-information competition mechanism. By applying an information diffusion model called limited attention model (LAM), we carried on two computational experiments to validate the model and investigate the relation between seed selection methods and the properties of information cascades. Our experimental results show that 1) the LAM model could reproduce the features of empirical distribution in Chinese social media; 2) the eigenvector centrality-based heuristic is a reasonable seed selection method for competitive influence maximization problem. The results of this paper can provide significant potential implications for information system design and management.

关键词： Computational modeling Media Blogs

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Interventions of traffic flow for intersection based on interval type-2 fuzzy sets

Interventions of traffic flow for intersection based on inte...

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International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Xuan Li Hong Mo FengHua Zhu College Of Electrical And Information Engineering Changsha University Of Science And Technology Changsha China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479947515

Assessment and analysis of the intersection status can help to make the right choice of interventions, it's can bring convenience to solve the traffic congestion. In this paper, interval type-2 fuzzy sets is applied in the analysis of the intersection state and congestion intervention, dynamic fuzzy comprehensive evaluation and footprint of uncertainty are used to assess the intersection condition. Combined with the example of intersection congestion, through corresponding intervention measures to improve the intersections crowded conditions. Thus the linguistic dynamic orbits of road status figured out.

关键词： Fuzzy sets Pragmatics Extraterrestrial measurements Manganese Orbits Uncertainty Vehicle dynamics

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The identifier-based relative position estimation for leader-follower robotic system

The identifier-based relative position estimation for leader...

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IEEE International Conference on Mechatronics and Automation

作者： Lingyi Xu Zhiqiang Cao Peng Zhao Yixin Yin State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

ISBN: (纸本)9781479939800

A monocular vision measurement approach is presented for leader-follower robotic system to estimate the position of the leader robot relative to the follower robot. The color identifier with green and red blocks is attached on the back of the leader robot, and it may be captured by the camera mounted on the follower robot. A coarse-to-fine searching method is given to extract the center point of the identifier. The parameters of the camera with the combination of the intrinsic and extrinsic ones are calibrated via least square method with given relative positions and the corresponding image coordinates of the identifier's center. The parameters are further optimized with Levenberg-Marquardt method. Then the position of the leader robot relative to the follower robot can be estimated only with single feature point. The experimental results verify the validity of the given approach.

关键词： Robot kinematics Cameras Feature extraction Robot vision systems Position measurement Image color analysis

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The design of robust MIMO neural network disturbance observer for multi-variable system

The design of robust MIMO neural network disturbance observe...

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Chinese control Conference (CCC)

作者： Juan Li Shihua Li Shengquan Li Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing Jiangsu CN School of Automation Southeast University Nanjing Jiangsu CN Sch. of Hydraulic Energy & Power Eng. Yangzhou University Yangzhou Jiangsu CN

Multi-variable systems widely exist in the practical engineering control systems whose performances are always severely interrupted by strong disturbances including unmodeled dynamics, parameter variations, couplings and external disturbances. Disturbance observer (DOB) is known as an effective technique to estimate disturbances and has been extensively applied for feed-forward compensation design in the presence of disturbances. Yet many disturbance observer techniques in previous literature are just used for single-input-single-output (SISO) systems or the DOBs can be applied in the multi-variable systems, but the DOBs are still SISO DOBs. A decoupled robust multi-input-multi-output neural network disturbance observer (MNNDOB) is designed for the multi-input-multi-output (MIMO) systems. Simulation results on the mixing tank show that the proposed method has better disturbance estimation performance when there are severe model mismatches compared with the MIMO linear disturbance observer.

关键词： Observers Neural networks MIMO Robustness control systems Adaptation models

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An high-efficient online reinforcement learning algorithm for continuous-state systems

An high-efficient online reinforcement learning algorithm fo...

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World Congress on Intelligent control and Automation (WCICA)

作者： Yuanheng Zhu Dongbin Zhao Haibo He The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI USA

In this paper, we consider continuous-state systems and pursue a near-optimal policy through online learning. A new online reinforcement learning algorithm-MSEC (Multi-Samples in Each Cell) is proposed. The proposed algorithm combines state aggregation technique and efficient exploration principle, making high utilization of samples observed online. More concretely, we apply a grid over the continuous state space and partition it into different cells. Then, a near-upper Q iteration operator is defined to use samples in each cell and produce a near-upper Q function, whose corresponding greedy policy is efficient for exploration. MSEC is a totally model-free algorithm, which means no system dynamics is required during the implementation. It collects the system knowledge during the online learning. Based on PAC (Probability Approximately Correct) principle, MSCE can find a near-optimal policy in finite time bound online. To test the performance, an inverted pendulum is simulated and the results show the new algorithm is qualified for solving online optimal control problems.

关键词： Algorithm design and analysis Heuristic algorithms Partitioning algorithms Learning (artificial intelligence) Approximation algorithms Polynomials Upper bound

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Approximation-error-ADP-based optimal tracking control for chaotic systems with convergence proof

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Chinese Physics B 2013年第9期22卷 305-311页

作者：宋睿卓肖文栋孙长银魏庆来 School of Automation and Electrical Engineering University of Science and Technology Beijing The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

In this paper, an optimal tracking control scheme is proposed for a class of discrete-time chaotic systems using the approximation-error-based adaptive dynamic programming （ADP） algorithm. Via the system transformation, the optimal tracking problem is transformed into an optimal regulation problem, and then the novel optimal tracking control method is proposed. It is shown that for the iterative ADP algorithm with finite approximation error, the iterative performance index functions can converge to a finite neighborhood of the greatest lower bound of all performance index functions under some convergence conditions. Two examples are given to demonstrate the validity of the proposed optimal tracking control scheme for chaotic systems.

关键词： chaotic systems approximation error adaptive dynamic programming optimal tracking control

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EEG-based classification of upper-limb ADL using SNN for active robotic rehabilitation

EEG-based classification of upper-limb ADL using SNN for act...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Jin Hu Zeng-Guang Hou Yi-Xiong Chen Nikola Kasabov Nathan Scott State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland New Zealand

Repetitive activities of daily living (ADL) and robotic active training are commonly practised in the rehabilitation of paralyzed patients, both of which have been proven rather effective to recover the locomotor function of impaired limbs. ADL classification based on electroencephalogram (EEG) is of great significance to perform active robotic rehabilitation for patients with complete spinal cord injury (SCI) who lose locomotion of affected limbs absolutely, where surface electromyography (sEMG) or active force signal can hardly be detected. It is a challenge to achieve a satisfying result in neuro-rehabilitation robotics using EEG signals due to the high randomness of the EEG data. A classification method is proposed based on spiking neural networks (SNN) to identify the upper-limb ADL of three classes with 14-channel EEG data. The continuous real-number signals are firstly encoded into spike trains through Ben's Spike Algorithm (BSA). The generated spikes are then submitted into a 3-D brain-mapped SNN reservoir called NeuCube trained by Spike Timing Dependant Plasticity (STDP). Spike trains from all neurons of the trained reservoir are finally classified using one version of dynamic evolving spiking neuron networks (deSNN) - deSNNs. Classifications are presented with and without NeuCube respectively on the same EEG data set. Results indicate that using the reservoir improves identification accuracy which turns out pretty promising despite that EEG data is highly noisy, low frequently sampled, and only from 14 channels. The classification technique reveals a great potential for the further implementation of active robotic rehabilitation to the sufferers of complete SCI.

关键词： Neurons Electroencephalography Training Robot kinematics Encoding Reservoirs

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