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42nd Chinese control Conference, CCC 2023

作者： Shan, Xiyuan Cai, Tao School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9789887581543

This paper is concerned with the controller design and the theoretical analysis for time-delay systems, a two degree of freedom (feedforward and feedback) control method is proposed, which combines advantages of the Smith predictor and the active disturbance rejection control (ADRC). The feedforward part of controller is used to track the set point, the feedback part of controller (ADRC) is used to suppress interferences and the Smith predictor is used to correct time delay. The proposed control design is easy to tune parameters and has been proved to effectively control systems with large time delay. The bounded input bounded output (BIBO) stability of closed-loop system is verified. Finally, numerical simulations show the effectiveness and practicality of the proposed design. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Time delay

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Theoretical characterization of the temperature-dependent saturation magnetization of magnetic metallic materials

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Chinese Physics B 2024年第7期33卷 577-585页

作者：吴金龙董攀贺屹马艳丽李梓源姚沁远邱俊麻建坐李卫国 State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing UniversityChongqing 400044China College of Aerospace Engineering Chongqing UniversityChongqing 400044China College of Intelligent Systems Science and Engineering Hubei Minzu UniversityEnshi 445000China College of Mechanical Engineering and Automation Chongqing Industry Polytechnic CollegChongqing 401120China

Based on the force-heat equivalence energy density principle,a theoretical model for magnetic metallic materials is developed,which characterizes the temperature-dependent magnetic anisotropy energy by considering the equivalent relationship between magnetic anisotropy energy and heat energy;then the relationship between the magnetic anisotropy constant and saturation magnetization is ***,we formulate a temperature-dependent model for saturation magnetization,revealing the inherent relationship between temperature and saturation *** model predicts the saturation magnetization for nine different magnetic metallic materials at different temperatures,exhibiting satisfactory agreement with experimental ***,the experimental data used as reference points are at or near room *** to other phenomenological theoretical models,this model is considerably more accessible than the data required at 0 *** index included in our model is set to a constant value,which is equal to 10/3 for materials other than Fe,Co,and *** transition metals(Fe,Co,and Ni in this paper),the index is 6 in the range of 0 K to 0.65T_(cr)(T_(cr) is the critical temperature),and 3 in the range of 0.65T_(cr) to T_(cr),unlike other models where the adjustable parameters vary according to each *** addition,our model provides a new way to design and evaluate magnetic metallic materials with superior magnetic properties over a wide range of temperatures.

关键词： magnetic metallic materials temperature dependent saturation magnetization modeling

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Detection and Positioning of Workpiece Grinding Area in Dark Scenes with Large Exposure 1

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16th International Conference on intelligent Robotics and Applications, ICIRA 2023

作者： Guo, Zhentao Zhao, Guiyu Bian, Jinyue Ma, Hongbin School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

Workpiece grinding is a crucial process in the smart manufacturing chain. In order to meet the requirements of industrial precision and relieve heavy work, researchers have developed a vision-based grinding robot. However, the problem of workpiece grinding area detection and positioning is difficult to be solved in dark scenes with large exposure. This paper proposes a method that fuses technologies such as processing of the image, coordinate and point cloud, which can accurately detect and locate the workpiece grinding area. Firstly, A method based on YOLOv7 and improved image preprocessing is used to detect labels of the grinding area. Secondly, A model for the prediction of the coordinates based on multiple linear regression was used to predict the coordinates of missing labels for the same grinding area. Finally, Data processing of the point cloud and transformation of the system of coordinates are used to achieve the acquisition of the coordinates of positioning vertices in the grinding area and conversion from the camera coordinate system to the world coordinate system. We used several sets of data for evaluation in our experiments, and the experimental results show that our proposed method can effectively detect the workpiece grinding area. At the same time, our method can also predict the coordinates of missing labels, which provides a more stable and reliable guarantee for industrial production. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Multiple linear regression

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CFSeRec: A Contrastive Framework for Sequential Recommendation 42

CFSeRec: A Contrastive Framework for Sequential Recommendati...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Tong Dai, Yaping Shao, Shuai School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9789887581543

In sequential recommender systems, the main problems are the long-tailed distribution of data and noise interference. A Contrastive Framework for Sequential Recommendation (CFSeRec) is proposed to solve these two problems respectively. Token shuffling and adversarial attack data augmentation methods are used in the framework to improve the quality and quantity of training data, so that the long-tailed problem is mitigated. Through the application of projection head method, the sequence representation becomes more general and robust, rather than just adapted to the task of contrastive learning. Therefore, the impact of noise on sequence recommender systems is effectively alleviated. Experiments on four public datasets show that CFSeRec achieves state-of-the-art performance in the metrics of hit ratio and normalized discounted cumulative gain, when comparing to the seven previous frameworks. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Recommender systems

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Reinforcement learning-enhanced dynamic multi-objective evolutionary algorithm for cooperative shovel scheduling in open-pit mining

Reinforcement learning-enhanced dynamic multi-objective evol...

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2024 China automation Congress, CAC 2024

作者： Zhang, Zihao Li, Changhe Yang, Shengxiang 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 Wuhan430074 China School of Artificial Intelligence Anhui University of Science & Technology Hefei232001 China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350368604

Aiming at the ore blending problem in the open-pit mining scenario, the optimization objective is to minimize the grade variance of the sliding window of the ore flow, and a cooperative shovel scheduling model for real-time ore blending is established. A reinforcement learning-enhanced dynamic multi- objective evolutionary algorithm is proposed, where a Q-learning operator selection mechanism is introduced to reuse the information from the previous environment for tracking the optimal solution in the dynamic environment. Experimental results show that the proposed method can effectively control the grade fluctuation of the ore flow and dynamically respond to external events, and can find a better solution in real time compared with the traditional operator selection algorithm. © 2024 IEEE.

关键词： Open pit mining

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Distributed Active Disturbance Rejection control of Multiple Mobile Robots for Online Workload Partition

Distributed Active Disturbance Rejection Control of Multiple...

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2023 China automation Congress, CAC 2023

作者： Li, Xin Zhai, Chao Zhang, Hehong China University of Geosciences School of Automation Wuhan Campus Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Computer and Data Science Fuzhou University Fuzhou China

ISBN: (纸本)9798350303759

Considering the actual multi-agent coverage process, the motion trajectories are seriously affected by disturbances and noise. In this paper, a cooperative control method based on active disturbance rejection controller (ADRC) for multiple mecanum-wheeled robots (MWMR) is proposed to improve its robustness. In particular, to suppress the total disturbances during the running of each robot and reduce large computation and observation cost of high order ADRC, a reduced-order cascaded ADRC (RC-ADRC) is proposed. Moreover, distributed controller is proposed to track the expected trajectories of multiple mecanum-wheeled robots under disturbances. Compared with the proposed RC-ADRC based cooperative control scheme and PID based cooperative control one, the favorable motion trajectory tracking performance is obtained. Simulation results verify the superiority of the method. © 2023 IEEE.

关键词： controllers

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A Reinforcement Learning Based Dynamic Multi-Objective Constrained Evolutionary Algorithm for Open-Pit Mine Truck Scheduling

A Reinforcement Learning Based Dynamic Multi-Objective Const...

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2023 China automation Congress, CAC 2023

作者： Qiu, Junxiang Li, Changhe Yang, Shengxiang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo- Exploration Ministry of Education Wuhan430074 China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350303759

Aiming at the truck scheduling problem in the open-pit mine scenario, a truck scheduling model based on real-time ore blending is established, and an adaptive evolution algorithm for truck scheduling based on DCNSGA-III is proposed. In the established scheduling model, the real-time grade variance of the crushing plant is minimized as one of the optimization objectives, and the Q-learning algorithm is introduced to adaptively select one of the most effective operators during the search process. Experiments show that the proposed method can effectively control the grade fluctuation of the ore flow and better scheduling schemes are obtained in comparison with algorithms equipped with the traditional search operator selection methods. © 2023 IEEE.

关键词： Evolutionary algorithms

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Multi-Level Features Fusion for Zero-Shot Object Pose Estimation 26

Multi-Level Features Fusion for Zero-Shot Object Pose Estima...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Huang, Nanxin Xu, Chi 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 Wuhan China

ISBN: (纸本)9798331521950

Driven by advancements in industrial production and artificial intelligence, the need for pose estimation of new ob-jects in areas like robotic manipulation and virtual reality is increasing. We introduce a zero-shot object pose estimation approach that identifies the poses of objects excluded from the training dataset, removing the requirement for re-modeling. The method is built around a multi-level features fusion framework de-signed to enhance generalization. First, a trainable feature extraction module filters and selects multi-level features extracted by the backbone network. Unlike traditional convolutional ker-nels, we incorporate a dynamic convolution kernel to enhance the feature extraction capability. Second, in the feature fusion module, we adopt a dynamic weight generation strategy to perform weighted fusion of multi-level features. This method enhances template matching by effectively describing similarities between unseen objects (those absent from the training set) and templates, leveraging robust and adaptive feature representations to narrow the gap with seen objects. Experimental results demonstrate that our approach achieves state-of-the-art performance on two popu-lar benchmark datasets, LineMod and LineMod-Occlusion, proves that our method has better generalization than previous models. © 2025 IEEE.

关键词： Industrial robots

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A Finite-Time Posture control Strategy for the Swarm Underactuated Robots 5th

A Finite-Time Posture Control Strategy for the Swarm Under...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Huang, Zixin Qin, Xiangyu Wei, Shaoqi Wang, Lejun Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan430205 China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan430200 China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789811939976

Under the background of industrial machinery automation. The swarm robots are required to cooperate to complete complex and accurate works in finite-time and create more relative residual value. Based on the inherent advantages of underactuated robot, the research of finite time posture control strategy has higher theoretical and practical value. Firstly, the dynamic model of a single Pendubot of planar swarm underactuated robots was built. However, the robots reach to the same objective from different initial states and keep being at the same posture, so it was necessary to plan a feasible trajectory. Then, the planned trajectory parameters are optimized to make the underactuated robots relized the objectives in finite time. Finally, an unified tracking controller is designed for the underactuated robots. Simulation results of the swarm underactuated robots demonstrated the effectiveness of the proposed control strategy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Robots

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Photovoltaic Data Cleaning Method Based on DBSCAN Clustering, Quartile Algorithm and Pearson Correlation Coefficient Interpolation Method 6

Photovoltaic Data Cleaning Method Based on DBSCAN Clustering...

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6th International Conference on Energy, Electrical and Power Engineering, CEEPE 2023

作者： Wang, Biyuan Deng, Xingye Chen, Taowei Li, Yidong Huizhou Power Supply Bureau Guangdong Power Grid Co Guangdong China School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798350348279

The proportion of photovoltaic power generation in the global energy structure is increasing year by year. Because of its volatility and periodicity, grid-connected photovoltaic challenges the safe and stable operation of power grid. One of the ways to solve this problem is data mining. Data mining needs high-quality data support, and data cleaning is one of the important means to improve data quality. Aiming at the problem of poor quality of original PV data, this paper analyzes two typical outliers of PV data and proposes a PV output data cleaning method based on Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm, quartile algorithm and Pearson correlation coefficient interpolation method. Comparison of DBSCAN clustering algorithm combined with the quartile method of outlier identification with the quartile method alone outlier identification, the effectiveness of the method proposed in this paper is verified. Then using the method proposed in this paper for outlier identification based on Pearson correlation coefficient interpolation and cubic spline interpolation to verify the data filling effect, the results show that Pearson correlation coefficient interpolation is superior to cubic spline interpolation. Finally, two sets of data with different data cleaning methods are substituted into the Long short-term memory (LSTM) Model to verify accuracy of the cleaning method proposed in this paper. © 2023 IEEE.

关键词： Data mining

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