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International Workshop on Variable Structure systems, VSS

作者： Jianliang Mao Shihua Li Qi Li Jun Yang Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China

This paper develops a continuous second-order sliding mode control based on finite-time disturbance observer for light of sight (LOS) stabilized loop of inertial stabilized platform. The main purpose of an inertial stabilized platform is to eliminate the various disturbances to make the LOS keep steady in an inertial space. To accomplish the controller design, the equations of motion for a 2-DOF gimbal system driven by permanent synchronous motors are established and the cross coupling torque, mass unbalance torque, uncertain load torque are treated as the lumped disturbances. And to improve the tracking accuracy, a new continuous sliding mode control approach is employed to control the rate loop of the system. The proposed method confirms that the tracking error of LOS rate converges to zero in finite time even in the presence of the disturbances. By using the Lyapunov function technique, a rigorous finite-time convergence proof is given. The comparison simulation results show that the proposed method for LOS stabilized system exhibits a promising control performance in practical engineering.

关键词： Torque Couplings Sliding mode control DC motors Tracking Observers Aerospace electronics

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Spatial-Temporal Fusion Convolutional Neural Network for Simulated Driving Behavior Recognition

Spatial-Temporal Fusion Convolutional Neural Network for Sim...

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International Conference on control, Automation, Robotics and Vision

作者： Yaocong Hu MingQi Lu Xiaobo Lu Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China

Abnormal driving behaviour is one of the leading cause of terrible traffic accidents endangering human life. Therefore, study on driving behaviour surveillance has become essential to traffic security and public management. In this paper, we conduct this promising research and employ a two stream CNN framework for video-based driving behaviour recognition, in which spatial stream CNN captures appearance information from still frames, whilst temporal stream CNN captures motion information with pre-computed optical flow displacement between a few adjacent video frames. We investigate different spatial-temporal fusion strategies to combine the intra frame static clues and inter frame dynamic clues for final behaviour recognition. So as to validate the effectiveness of the designed spatial-temporal deep learning based model, we create a simulated driving behaviour dataset, containing 1237 videos with 6 different driving behavior for recognition. Experiment result shows that our proposed method obtains noticeable performance improvements compared to the existing methods.

关键词： driving behaviour convolutional neural networks spatial-temporal deep learning fusion

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Wind Speed Data Repairing Method Based on Bidirectional Prediction

Wind Speed Data Repairing Method Based on Bidirectional Pred...

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2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021

作者： Shen, Xincheng Qu, Yi Huang, Shaoxiong Li, Zhi Zhang, Kaifeng Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China State Grid Anhui Electric Power Co. Ltd Department of Dispatch Center Hefei China

ISBN: (纸本)9781728190037

In order to repair the lost data in distributed wind power system, this paper puts forward a wind speed data repairing model based on a new bidirectional prediction method. This model consists of two one-way prediction models. In each prediction model, the original wind speed data are decomposed into several intrinsic mode functions (IMFs) and a residue signal by ensemble empirical mode decomposition (EEMD) method. Then the Savitzky-Golay (SG) filter is used to reduce noise for high-frequency IMFs. Next the long short-term memory (LSTM) model and autoregressive integrated moving average (ARIMA) model are combined to predict low-frequency IMFs and the noise reduction results respectively. At the end, all those forecast results are added and form a one-way result. By weighted average of two one -way results, the repairing result is calculated. The experimental results from multiple prediction cases show that this method can get more accurate results. © 2021 IEEE.

关键词： Empirical mode decomposition

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Consensus-based distributed estimation in homogeneous sensor networks

Consensus-based distributed estimation in homogeneous sensor...

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International Conference on control and Automation (ICCA)

作者： Ya Zhang Yu-Ping Tian Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China

This paper studies distributed estimation of linear dynamical target in homogeneous sensor networks. Just some sensors can get observations of the target. A distributed estimator composing of Luenberger observers and consensus strategy is applied. Based on spectral radius analysis and algebraic graph theory, necessary conditions of distributed detectability are given for time-invariant and randomly switching networks, respectively. By applying Lyapunov functional analysis and solving a special LQR problem, sufficient detectability conditions are proposed for both networks. The sufficient conditions are composed of an explicit inequality concerning weights, topology switching probabilities and the eigenvalues of the target's system matrix. Simulation examples are given to illustrate the results.

关键词： Topology Network topology Sensors Switches Estimation Noise Loss measurement

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Data-free point cloud network for 3d face recognition

arXiv

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arXiv 2019年

作者： Zhang, Ziyu Da, Feipeng Yu, Yi School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering

Point clouds-based Networks have achieved great attention in 3D object classification, segmentation and indoor scene semantic parsing. In terms of face recognition, 3D face recognition method which directly consume point clouds as input is still under study. Two main factors account for this: One is how to get discriminative face representations from 3D point clouds using deep network;the other is the lack of large 3D training dataset. To address these problems, a data-free 3D face recognition method is proposed only using synthesized unreal data from statistical 3D Morphable Model to train a deep point cloud network. To ease the inconsistent distribution between model data and real faces, different point sampling methods are used in train and test phase. In this paper, we propose a curvatureaware point sampling(CPS) strategy replacing the original furthest point sampling(FPS) to hierarchically downsample feature-sensitive points which are crucial to pass and aggregate features deeply. A PointNet++ like Network is used to extract face features directly from point clouds. The experimental results show that the network trained on generated data generalizes well for real 3D faces. Fine tuning on a small part of FRGCv2.0 and Bosphorus, which include real faces in different poses and expressions, further improves recognition accuracy. Copyright © 2019, The Authors. All rights reserved.

关键词： Face recognition

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An Incentive-based Supplier Selection Mechanism to Support Green Supply Chains

An Incentive-based Supplier Selection Mechanism to Support G...

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World Congress on Intelligent control and Automation

作者： Fang Yu Lei Xue Changyin Sun Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

ISBN: (纸本)9781467384155

Supplier selection is an important decision for an enterprise to realize a sustainable production. However, almost all works, which concerned the environmental issues, focused on the supplier selection or evaluation methods, rather than the incentive mechanism urging the participants to improve their decisions (reduce the harm to the environment). In this paper, not only are the commercial factors (price, quantity, and lead time), but also the environment factors (green factors and carbon dioxide emissions) of the suppliers are considered during the selection. The determinations of the green factors and the total carbon dioxide emissions depend on the analysis of the history trade data. An incentive supplier selection mechanism, which urges the agents to improve their decisions to reduce the harm to the environment, is proposed. Numerical calculations are provided to verify the feasibility and the superiority of the proposed model.

关键词： degradation of the environment carbon dioxide emission green LEAD TIME evaluation method numerical calculation Environmental issues HARM Environmental factors incentives

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Path planning of robotic fish based on genetic algorithm and modified dynamic programming

Path planning of robotic fish based on genetic algorithm and...

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2011 International Conference on Advanced Mechatronic systems, ICAMechS 2011

作者： Yang, Qian Yu, Mei Liu, Shu Chai, Zhong-Ming School of Control and Computer Engineering North China Electric Power University Beijing 102206 China Key Laboratory of Measurement and Control New Technology and System for Industrial Process North China Electric Power University Beijing 102206 China

ISBN: (纸本)9780955529375

In this paper, genetic algorithm and modified dynamic programming are applied to path planning of robotic fish for the first time. Using grid method to the environment modeling and applying genetic algorithm to the path planning, an optimal or sub-optimal robot path can be obtained. Since the robotic fish can't track linear motion, the robot path can be seen as several circular arc. Based on the optimal path obtained via genetic algorithm, modified dynamic programming algorithm is proposed to calculate the shortest circular arc path, fish velocity and direction in every step. Finally the experiment on the robotic fish control software shows the effectiveness of the proposed method. © 2011 Intl Journal of Adv Mechatr.

关键词： Motion planning

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Multi-Dimensional Taylor Network (MTN)-Based Adaptive Tracking control for a Class of Nonlinear systems with Input Constraints

Multi-Dimensional Taylor Network (MTN)-Based Adaptive Tracki...

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Chinese control Conference (CCC)

作者： Yu-Qun Han Hong-Sen Yan Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China

This paper focuses on the problem of multi-dimensional Taylor network (MTN)-based adaptive tracking control for a class of nonlinear systems with input constraints. As preliminaries, the saturation is first presented by a smooth function, and then a novel MTN-backstepping-based adaptive control method is designed on the basis of the Lyapunov stability theory. It is shown that the proposed control method can guarantee that all the signals in the closed-loop system are bounded and the tracking error converges to an arbitrarily small neighborhood around the origin. Finally, one example is given to illustrate the effectiveness of the proposed design approach.

关键词： Nonlinear systems Adaptive control Lyapunov methods Backstepping Closed loop systems

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Cooperative control Based on Distributed Attack Identification and Isolation

Cooperative Control Based on Distributed Attack Identificati...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Hailing Liu Dalin Huang Ya Zhang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

This paper studies the secure consensus control of multi-agent systems where some agents are injected into malicious attacks and compromised. We focus on the distributed detection and identification of attacks on agents and the realization of consensus of agents against attacks. Firstly, we design monitors that can perform precise distributed attack detection. Then, we propose a distributed attack identification algorithm by constructing distributed observers. After that, a cooperative controller is proposed which ensures the normal control of systems by means of isolating the agents which are attacked. Finally, we validate our results through simulation examples.

关键词： Multi-agent systems Monitoring Sensors Sensor systems Security Observers Data models

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Study on short periodic solutions of a discretized second-order sliding-mode control system

Study on short periodic solutions of a discretized second-or...

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International Workshop on Variable Structure systems, VSS

作者： Xiangyu Wang Shihua Li Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China

In this paper, short periodic solutions of a discretized second-order sliding-mode control system are investigated. Specifically, the existence and stability of short periodic solutions are analyzed. Moreover, the exp... 详细信息

关键词： Orbits Manifolds Stability analysis Educational institutions Sliding mode control Trajectory Switches

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