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第42届中国控制会议

作者： Dapeng Xu Xiaobo Lu Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University

Fall events have unique dynamic features,which are not fully utilized by existing fall detection *** on video understanding,we propose Fall-LSTM to learn such features pertinently without additional ***-LSTM is composed of CNN-LSTM framework and two excitation modules i.e.,Spatial Attention Module(SAM) and Temporal Location Module(TLM).SAM provides spatial constraints on motion for feature layers through foreground extraction and spatial *** emphasizes frames with high probability of fall events to LSTM by inferring the rate and trend of motion in *** results show that our proposed modules significantly improve the performance of LSTM model,outperforming the state-of-theart methods on two public Fall Detection Datasets i.e.,Le2 i and UR.

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Composite Single-Loop Model Predictive control Design for PMSM Servo system Speed Regulation Based on Disturbance Observer

Composite Single-Loop Model Predictive Control Design for PM...

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第32届中国控制与决策会议

作者： Mengdi Zhou Xiangyang Liu Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

In order to optimize the control performance of the permanent magnet synchronous motor（PMSM） in the presence of strong disturbances and model uncertainty,a composite single-loop model predictive control（MPC） based on disturbance observer（DOB） is studied in this ***,a DOB is employed to estimate the lumped disturbance including the uncertain parameters and the external disturbance in real ***,benefitting from model-based design,estimations are introduced into the prediction model of the PMSM,then a composite single-loop MPC is designed based on this ***,the optimal control input is obtained,by introducing Lagrange vector and solving the quadratic programming problem with *** results show that the proposed composite control method has a faster transient response and a better disturbance rejection *** addition,compared with the generally cascade structure,only the predictive horizon and the observer poles are needed to be adjusted,so it provides a more practical optimization algorithm for the engineering application.

关键词： Composite Single-Loop Model Predictive control Disturbance Observer Quadratic Programming Problem PMSM Servo system

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A two-column Convolutional Neural Network for Facial Point Detection

A two-column Convolutional Neural Network for Facial Point D...

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2016 IEEE International Conference on Progress in Informatics and Computing

作者： Wei Wang Xiaobo Lu Jiaji Song Cong Chen School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

This paper proposes a two-column convolutional neural network algorithm for face point detection, which proves better performance than single-column. Because of the deep level structure, global texture features are extracted at higher layers of the network, and the results of keypoint location remains high accuracy. In the first column, we take the channel component of original image as input to train the neural network respectively and calculate the average location results. In the second one, we use Sobel operator to extract first-order derivative feature of original image and regard it as the input to train another convolutional network. The location results of two columns above are fused with appropriate proportion to ensure better results. Experimental result on LFW dataset shows the performance of the proposed parallel structure better than single convolutional network, and it stays robust due to occlusions, large pose variations and extreme lighting.

关键词： facial point detection convolutional neural network Sobel information fusion

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Modified Deep Deterministic Policy Gradient Based Optimal Speed Tracking Strategy for PMSMs 13

Modified Deep Deterministic Policy Gradient Based Optimal Sp...

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13th IEEE Data Driven control and Learning systems Conference, DDCLS 2024

作者： Fan, Zhong-Xin Tang, Lintao Li, Shihua Liu, Rongjie School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Florida State University Department of Statistics TallahasseeFL32304 United States

ISBN: (纸本)9798350361674

Achieving optimal speed regulation for permanent magnet synchronous motors (PMSMs) remains a challenging task, particularly in selecting the most suitable controller to meet desired objectives. This paper considers the optimal speed tracking problem of PMSMs. We employ a reinforcement learning algorithm to obtain optimal controller with a linear form. The reinforcement learning approach incorporates a critic-actor network structure, which approximates the value function and optimal control, respectively. Specifically, a weight updating method for the critic network is introduced, where the update of the actor network is guided by the critic network. Through data collection and neural network training, dynamic acquisition of the optimal controller gain is achieved. In addition, a novel activation function is implemented in the network, leading to improved control performance concerning dataset size and reduced training time. At final, a real-world PMSM application is presented along with comparisons to demonstrate effectiveness. The desire idea of resulting optimal controllers is not only applicable to linear systems but also capable of approximating arbitrary nonlinear optimal controllers, thus offering practical engineering versatility. © 2024 IEEE.

关键词： Reinforcement learning

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An Improved Frequency Hopping Algorithm Based on Transmission Scheduling against Jamming Attacks 36

An Improved Frequency Hopping Algorithm Based on Transmissio...

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36th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2021

作者： Wang, Chenyuan Kong, Xiangying Chen, Xuebing Cao, Xianghui Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing210096 China Jiangsu Automation Research Institute Jiangsu China Southeast University School of Cyber Science and Engineering Nanjing China

ISBN: (纸本)9781665437127

In wireless networked systems, jamming attacks are destructive and easy to be launched. To mitigate the jamming attack impact, frequency hopping is an effective way, in which a defender side can switch channels to avoid using the ones under jamming attack. However, the resilient ability of anti-jamming of traditional frequency hopping algorithm can't meet the requirement of communication without channel strategy and jamming detection under the circumstance of various forms of jamming attacks. In this paper, an improved frequency hopping algorithm with higher transmit success rate (TSR) has been proposed based on channel selection and adjustment of transmission time to defend different kinds of attacks such as reactive jamming, static jamming and scanning jamming. Our algorithm judges whether to adjust data transmission time according to the result of transmit success rate and use channel selection strategy to avoid most of interfered channels. Finally, our proposed algorithm is evaluated as a resilient scheme under different forms of jamming attacks through simulations. © 2021 IEEE.

关键词： Frequency hopping

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Nonsingular Terminal Sliding Mode control for Fuel Quantity Actuator system Using High-order Sliding Mode Observer

Nonsingular Terminal Sliding Mode Control for Fuel Quantity ...

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第三十八届中国控制会议

作者： Jianpei Hu Hao Sun Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

Fuel quantity actuator can directly control fuel injection quantity of the diesel engine, so it is the main component of the electronic distribution pump. In this paper, a position tracking problem for fuel quantity actuator system under the influence of disturbances and system uncertainties is studied via a high-order sliding mode observer(HOSMO) based nonsingular terminal sliding mode control(NTSMC) approach. The proposed finite-time NTSMC method integrates the lumped disturbance estimation information estimated by the HOSMO into the designed control law, and realizes the finite time tracking performance under the influence of disturbances and uncertainties. The simulation results show the effectiveness of the proposed method.

关键词： Lumped Disturbances Fuel Quantity Actuator Non-singular Terminal Sliding Mode control(NTSMC) High-order Sliding Mode Observer(HOSMO)

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The control and Application of a 2D-Motion Platform

The Control and Application of a 2D-Motion Platform

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第34届中国控制与决策会议

作者： Ziyao Wang Yiye Wang Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

Natural Locomotion interface(NLI) is critical to expanding the users' exploration of scenes in virtual reality and improving user *** on the 2D motion platform,users can achieve a natural locomotion experience in a limited physical *** a small-scale 2D motion platform,an ideal situation is that the velocity of the platform can always be synchronized with the user's actual intended velocity,so that the user's center of mass is kept at the center of the *** puts a brand new requirement on the performance of the platform *** paper designs an acceleration-level state feedback controller for the small-scale 2D motion *** the user's intended acceleration as an external disturbance,it is estimated by introducing a disturbance state observer;for the user' s velocity on the platform,a linear state observer is used to estimate it;then takes the estimated values as feedforward terms to compensate the *** with the HCMK1 2D motion platform,we implemented the controller and verified it to be *** recording the data of the user walking along the circle and the square trajectory,it was verified that the designed controller has good control performance for the user's motion and the state observers a great performance to quickly track the user's intended acceleration and the user's velocity on the platform.

关键词： Virtual Reality Nature Locomotion Interface State Observer 2D-Motion Platform

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Dynamic Multi-Person Mesh Recovery from Uncalibrated Multi-View Cameras

arXiv

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arXiv 2021年

作者： Huang, Buzhen Shu, Yuan Zhang, Tianshu Wang, Yangang Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

Dynamic multi-person mesh recovery has been a hot topic in 3D vision recently. However, few works focus on the multi-person motion capture from uncalibrated cameras, which mainly faces two challenges: the one is that inter-person interactions and occlusions introduce inherent ambiguities for both camera calibration and motion capture;The other is that a lack of dense correspondences can be used to constrain sparse camera geometries in a dynamic multi-person scene. Our key idea is incorporating motion prior knowledge into simultaneous optimization of extrinsic camera parameters and human meshes from noisy human semantics. First, we introduce a physics-geometry consistency to reduce the low and high frequency noises of the detected human semantics. Then a novel latent motion prior is proposed to simultaneously optimize extrinsic camera parameters and coherent human motions from slightly noisy inputs. Experimental results show that accurate camera parameters and human motions can be obtained through one-stage optimization. The codes will be publicly available at https://***. Copyright © 2021, The Authors. All rights reserved.

关键词： Mesh generation

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A Robust Traffic Driver Face Detection Method

A Robust Traffic Driver Face Detection Method

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2016 IEEE International Conference on Progress in Informatics and Computing

作者： Dechao Luo Xiaobo Lu Changhui Hu Xiang Peng Wei Wang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

Face detection technology is a hot topic in the past recent years. It has been maturely applied to many practical areas. However, the driver face detection is still an open problem to solve. In this paper, we proposed an improved method to promote the face detection rate and apply it to the images from the monitoring videos. The first step is to detect the car from the images according to an off-line learning method. Then the method based on additional off-line learning method is the front level for skin color feature in order to correctly detect the driver face. The proposed systems are implemented on the various complicated road environment. The results show that the proposed method improves the efficiency of the driver face detection and is of strong robustness on having glasses, driver head rotation, and lighting change.

关键词： car detection driver face detection skin color feature Haar-like feature Adaboost

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An Algorithm for Cooperative Navigation Using Neural Network to Identify Colored Noise Online

An Algorithm for Cooperative Navigation Using Neural Network...

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2024 IEEE International Conference on Unmanned systems, ICUS 2024

作者： Sheng, Danting Cheng, Jin Li, Fengyi Hao, Mingrui Beijing Electro-mechanical Engineering Institute CASIC Beijing China HIWING Technology Academy of CASIC CASIC Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation CASIC Beijing China

ISBN: (纸本)9798350384185

In practical applications of cooperative navigation algorithms based on Kalman filtering, noise is often colored noise, which does not meet the requirement of Gaussian white noise for Kalman ***, an algorithm is proposed to identify and compensate for colored noise online using a BP neural ***, a cooperative navigation model based on Kalman filtering is ***, by studying the update process of Kalman filtering, the neural network is incorporated into the prediction calculation of the observations, following the online learning and updating of the Kalman *** simulations show that under conditions of colored noise, the results of the Kalman filter ***, after correction by the BP neural network, the filtering converges, providing high reference value for improving the accuracy of cooperative navigation. © 2024 IEEE.

关键词： Wiener filtering

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