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检索条件"机构=Key Laboratory of Measurement and Control for Complex Systems of Engineering"

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A Trajectory Tracking Algorithm Based on Interior Point Method for A Class of Mobile Manipulators

A Trajectory Tracking Algorithm Based on Interior Point Meth...

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Chinese Automation Congress (CAC)

作者： Xuechen Rao Yahui Gan Xiaoteng Wang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education NanJing China

At present, due to the high redundancy and strong coupling characteristics of mobile manipulator systems, there are few and in-depth studies on coordinated motion planning. Aiming at the above problems, this paper proposes a coordinated control algorithm that can track the desired trajectory of the end-effector based on a class of 5-DOF mobile manipulators. The algorithm takes the power consumption and trajectory stability of the entire system as the optimization objectives, and sets the function of the selected optimization objective on the desired trajectory, and performs optimization based on the interior point method of convex optimization to converge to the optimal solution faster. Finally, the system is simulated to verify the correctness and effectiveness of the control algorithm.

关键词： Smoothing methods Trajectory tracking Simulation Robot kinematics Redundancy Mathematical models End effectors

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Missing Small Bolt Detection on High-speed Train Using Improved Yolov5

Missing Small Bolt Detection on High-speed Train Using Impro...

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International Conference on systems and Informatics (ICSAI)

作者： Yiming Wei Xiaobo Lu School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781665474498

Tiny bolts are widely used on high-speed trains, playing an important role in fixing train components. However, because of the complex running environment of trains, missing bolts occur from time to time and may cause traffic accidents, resulting in property damage and, in serious cases, endangering the lives of the occupants. Therefore, it is essential to detect missing bolts on high-speed trains. The bolts discussed in this paper are generally located on the underside of high-speed trains and their small size makes detection more difficult. In this paper, we first expand the dataset, and then add the Attention module and Transformer based on YOLOv5, and change the FPN of YOLOv5 to BiFPN, fuse the features of different layers using different weights, and crop the high-resolution original image during training and testing, and finally return to the original image. Our method eventually achieves 95.3% AP, effectively improving the detection accuracy.

关键词： Training Fuses Training data Object detection Fasteners Transformers Data models

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Maximum power point tracking of photovoltaic array in partial shading condition based on improved Gray Wolf optimization algorithm

Maximum power point tracking of photovoltaic array in partia...

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Chinese control and Decision Conference, CCDC

作者： Chuang Kou Chenxi Li Kanjian Zhang Jinxia Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China

ISBN: (纸本)9781665478977

The partial shading condition (PSC) makes it challenging for the PV system to find the maximum power point. In this paper, an improved gray wolf algorithm (GWO) is proposed by introducing elimination mechanism, greedy mechanism and adjusting the convergence factor which overcomes the contradiction between global exploration ability and convergence time. Under fast varying irradiance and PSC, IGWO has been compared with GWO, particle swarm optimization (PSO), and adaptive particle swarm optimization (APSO), the results shows the superiority of IGWO in the MPPTs of the PV system.

关键词： Photovoltaic systems Maximum power point trackers Adaptive systems Heuristic algorithms Particle swarm optimization Oscillators Optimization

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Double wavelet threshold filter design for real-time adaptive denoising in OA-ICOS

Double wavelet threshold filter design for real-time adaptiv...

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Jiangsu Annual Conference on Automation (JACA 2024)

作者： Yixin Deng Zairan Wang Yang-Yang Chen Qin Liu Xiangyu Wang School of Automation and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing People's Republic of China School of Cyber Science and Engineering Southeast University Nanjing People's Republic of China

ISBN: (数字)9781837242719

In the Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) technique, single-stage filters are commonly used to reduce noise and improve the signal-to-noise ratio, enabling more precise CO2 concentration detection. However, these filters often underperform under real-time conditions. To enhance real-time performance, this paper proposes a novel framework based on Double Wavelet Threshold Filter (DWTF) that adaptively suppresses noise while preserving key features of CO2 concentration signal. Firstly, one wavelet threshold filter (WT) is introduced to calculate the mean of the current sequence, providing an initial denoising step. Secondly, another WT is employed to extract features from a longer sequence for adaptive computation of the discount factor. Finally, an exponential moving average filter (EMA) is applied to combine both current and historical data to produce a smoother aggregated output. To validate the effectiveness, DWTF was compared with other conventional algorithms for a CO2 dataset with three distinct states: smooth, ship and mutant, obtained by OA-ICOS. The experimental results demonstrate that DWTF performs effectively in all three states.

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An Obstacle Avoidance Path Planning Algorithm for Manipulator in Deep Crate Grasping

An Obstacle Avoidance Path Planning Algorithm for Manipulato...

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2023 China Automation Congress, CAC 2023

作者： Yao, Zhuobin Gan, Yahui Han, Zao Gao, Huan Li, Ang School of Automation Southeast University Key Laboratory of Measurement and Control of Systems of Engineering Ministry of Education NanJing China Intel Joint Research Institute on Intelligent Edge Computing Nanjing YingQi Intelligent Technology Co. Ltd. NanJing China

ISBN: (纸本)9798350303759

The deep crate grasping problem is a major challenge for manipulator in industrial applications. In order to solve the issue of deep crate grasping and ensure the path quality of the algorithm, this paper proposes a new hybrid obstacle avoidance planning algorithm based on goal-biased rapidly exploring random tree and improved artificial potential field (RRT-APF). Initially, the algorithm strategizes an efficient trajectory for the working element within the operational area. Subsequently, it dissects this trajectory through sampling, creating a sequence of sub-target points. These points serve as the basis for obstacle avoidance planning within the manipulator's configuration space, mitigating planning complexities. Moreover, the RRT algorithm is employed to address the challenge of local optima within the artificial potential field method. The stochastic nature of the RRT algorithm plays a crucial role in enabling the APF algorithm to break free from local optima. Ultimately, the efficacy of the algorithm is demonstrated through the planning of a path for obstacle avoidance on the DOBOT CR5 manipulator using MATLAB. © 2023 IEEE.

关键词： Trees (mathematics)

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Chaos Suppression of Power System Based on Finite-time Adaptive Sliding Mode control 20

Chaos Suppression of Power System Based on Finite-time Adapt...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Wang, Hongjun Li, Shuyi Zhao, Hui Yue, Youjun Tianjin University of Technology Key Laboratory of Control Theory and Application for Complex Systems in Tianjin Binshui Xidao Extension 391 Tianjin300384 China Tianjin Agricultural University College of Engineering and Technology 22 Jinjing Road Tianjin300384 China

ISBN: (纸本)9798350320831

Under certain conditions, the power system will produce chaotic oscillation, which may impact the safety and stability of the power grid. Under the action of inductive load, the power system will generate a certain amount of reactive power. Excessive reactive power will lead to the deviation of the voltage phase angle of the power system. Usually, reactive compensation equipment is used to absorb the reactive power in the power system and adjust the voltage phase angle. In this article, the dynamics analysis of chaotic oscillation of the second-order power system model (SOPSM) is firstly carried out, and a global adaptive sliding mode controller based on finite time is designed by comprehensively using backstepping, fixed-time controller and adaptive sliding mode control methods (ASM), which not only realizes the suppression of chaotic oscillation of the power system, but also reduces the computational burden and improves the convergence speed of the system, Finally, MATLAB/Simulink numerical simulation shows that the designed controller can quickly restore the power system from chaotic state to equilibrium state, thus verifying the effectiveness and efficiency of the controller. © 2023 IEEE.

关键词： Sliding mode control

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Online Estimation of State of Healh for Lithium-ion Batteries Based on Attention-LSTM Netwrok Using Partial Charging Features

Online Estimation of State of Healh for Lithium-ion Batterie...

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Energy, Electrical and Power engineering (CEEPE), International Conference on

作者： Yue Yao Ying Wang Jiangfeng Zhang Kaifeng Zhang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China State Grid Zhejiang Electric Power Research Institute Zhejiang China

Accurate estimation for state-of-health (SOH) of lithium-ion batteries is critical to ensure the security and durability of battery operation. Accordingly, this paper proposes a SOH estimation method based on Attention-LSTM neural network using the partial charging features. First, features are extracted from partial constant-current charging curves. Second, Pearson coefficient analysis is employed to analysis the mapping relationship between extracted features and SOH. Third, an Attention-LSTM network is utilized to realize the SOH estimation. The attention mechanism can adaptively assign weights to the input features and time steps, thereby improving the estimation accuracy. Validation experiments are conducted on public dataset from NASA Ames Prognostics Center of Excellence. The experimental results highlight that the proposed method has higher accuracy and robustness compared with other approaches.

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A repetitive-control method based on sliding-mode control for nonlinear systems with external disturbances 41

A repetitive-control method based on sliding-mode control fo...

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第41届中国控制会议

作者： Yibing Wang Min Wu Manli Zhang Luefeng Chen Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Engineering Tokyo University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents a two-dimensional(2 D) repetitive-control method based on sliding-mode control for a nonlinear system with external *** a sliding-mode controller has a powerful ability to handle nonlinearity and external disturbances during the sliding motion,the reference-tracking and disturbance-suppression problems of the original nonlinear system are decomposed into two subproblems:reference tracking for a linear system and disturbance suppression for a nonlinear modified-repetitive control system(MRCS) with external *** the first one,a repetitive controller constructed with two positive time-delay loops is employed to increase the flexibility of the system design and guarantee high accuracy reference tracking.A continuous-discrete 2 D model of the linear MRCS is established to describe continuous control and discrete learning by using the 2 D property of repetitive control.A sufficient stability condition,in which three parameters are used to adjust control and learning,is given to guarantee the stability of the linear *** design of the system is transformed into parameter *** optimization algorithm is used to yield the optimal *** the other,a sliding-mode controller is developed to eliminate the effect of both nonlinearity and external disturbances on the system.A linear-matrix-inequality(LMI)-based sufficient stability condition is derived to guarantee the stability of the sliding *** condition is used to design the sliding-mode controller,which has a simple structure and does not require any specific information of nonlinearity and external ***,a numerical example and a comparison demonstrate the validity and advantage of the presented method.

关键词： Repetitive control sliding-mode control two-dimensional model

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Hand-Motion Intention Recognition Based on One-Dimensional Convolutional Neural Network 41

Hand-Motion Intention Recognition Based on One-Dimensional C...

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第41届中国控制会议

作者： Hao Wu Feng Wang Juan Zhao Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Engineering Tokyo University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Surface electromyographic(sEMG) signals play an important role in human-computer interaction between patients and rehabilitation robots in rehabilitation *** paper shows the effectiveness of one-dimensional convolutional neural networks(1-D CNN) in estimating hand motion intentions from sEMG *** database 1 was employed to train the ***,the data from a single subject was used to train a model,and the accuracy was roughly maintained at 80%.Then,the whole dataset was used to train the network,and the recognition accuracy was improved to 84.16%.This shows that 1-D CNN effectively estimates hand movements and achieves high accuracy even for a small number of data.

关键词： Electromyographic hand motion intention Ninapro database one-dimensional convolutional neural network(1-D CNN)

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A Survey on IMU-and-Vision-based Human Pose Estimation for Rehabilitation 41

A Survey on IMU-and-Vision-based Human Pose Estimation for R...

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第41届中国控制会议

作者： Yuan Niu Jinhua She Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the rapid development of human pose estimation,the human-pose-estimation method applied in rehabilitation therapy has attracted more and more attention in today's aging *** them,inertial measurement units(IMU) and computer vision are two significant methods for human pose *** mainly pay attention to the application of these two methods in the rehabilitation therapy *** this paper,we first summarize the research status of IMU and computer vision in the field of rehabilitation ***,we find that combining the two methods can produce better ***,the main problems of the current research and possible development directions are identified.

关键词： Human Pose Estimation IMU Computer Vision Rehabilitation Therapy

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