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Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 957-968页

作者： Jinhua She Kou Miyamoto Qing-Long Han Min Wu Hiroshi Hashimoto Qing-Guo Wang School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan K.Miyamoto is with the Institute of Technology Shimizu CorporationKotoTokyo 135-0044Japan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China School of Industrial Technology Advanced Institute of Industrial TechnologyTokyo 140-0011Japan Institute of Artificial Intelligence and Future Networks Beijing Normal UniversityZhuhai 519087 Guangdong Key Lab of AI and Multi-Modal Data Processing Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNUHKBU United International College Zhuhai 519087China

Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state *** paper presents a deep observation on and a comparison between two of those methods:the generalized extended-state observer(GESO)and the equivalent input disturbance(EID)from assumptions,system configurations,stability conditions,system design,disturbance-rejection performance,and extensibility.A time-domain index is introduced to assess the disturbance-rejection performance.A detailed observation of disturbance-suppression mechanisms reveals the superiority of the EID approach over the GESO method.A comparison between these two methods shows that assumptions on disturbances are more practical and the adjustment of disturbance-rejection performance is easier for the EID approach than for the GESO method.

关键词： Active disturbance-rejection control(ADRC) disturbance observer(DOB) equivalent input disturbance(EID) extendedstate observer(ESO) generalized extended-state observer(GESO)

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Multi-UAV Coverage Path Planning Method Based on Improved Particle Swarm Optimization

Multi-UAV Coverage Path Planning Method Based on Improved Pa...

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Chinese Automation Congress (CAC)

作者： Yan Zhou Yonghua Xiong 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 Automation China University of Geosciences Wuhan China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

The widespread application of unmanned aerial vehicle (UAV) has made the coverage path planning problem for multiple UAV systems a research hotspot. In this paper, we propose a multi-UAV solution to achieve complete coverage of multi-region. Based on this solution, we present an improved particle swarm optimization (PSO) algorithm that combines PSO algorithm, greedy strategy, and back-and-forth (BAF) algorithm. Its purpose is to plan the optimal paths for multi-UAV while achieving the shortest total distance and the highest UAV cooperation efficiency with the minimum number of UAVs, thereby enhancing the multi-UAV coverage cooperation and path optimization capabilities. Simulation results demonstrate the feasibility and superiority of this algorithm.

关键词： Automation Simulation Autonomous aerial vehicles Path planning Particle swarm optimization Collision avoidance Optimization

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An Error Correcting Output Code Algorithm Based on Hierarchical Clustering for Lithology Identification

An Error Correcting Output Code Algorithm Based on Hierarchi...

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第43届中国控制会议

作者： Ao Li Xi Chen School of Rail Transit Hunan University of Technology Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems.Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Lithology identification serves as a crucial foundation for the precise exploration and safe exploitation of geological resources. However, challenges arise from the inherent imbalance and overlap present in logging data, making the accurate identification of lithology a complex task. Addressing these challenges effectively, this paper introduces a novel algorithm,the Error Correcting Output Code algorithm based on Hierarchical Clustering(HC-ECOC). The proposed algorithm initially formulates a coding matrix using distance and overlap measures between class clusters. Subsequently, it extends the length of the coding matrix by considering both the accuracy of the integrated classifier and the diversity among base classifiers. To evaluate the efficacy of the proposed method, comparisons were conducted with alternative algorithms using UCI datasets and an authentic lithology dataset. The results unequivocally demonstrate the superior performance of our algorithm.

关键词： Lithology Identification Error Correcting Output Code Hierarchical Clustering

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Norm-Integrated Softmax Loss For Deep Face Recognition

Norm-Integrated Softmax Loss For Deep Face Recognition

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IEEE International Conference on Image Processing

作者： Jun Chen Yiwei Wang Haiyan Zhang School of Automation China University of Geosciences Wuhan 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

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

The key to face recognition lies in how to improve the model’s ability to extract facial features. To this end, numerous loss functions based on different metrics have been proposed to increase the margin of feature distinction between different classes. Methods based on Cosine distance significantly enhance face recognition performance by focusing on angular constraints between samples and classes, demonstrating their superiority over those based on Euclidean distance. However, a significant oversight in these methods is the neglect of feature magnitude’s importance in representing facial features. To address this gap, our study introduces the NormIntegrated Softmax loss (NIface loss), a novel loss function that amalgamates feature norms with angular information. This integration offers a comprehensive perspective for feature classification, augmenting the compactness of intra-class features. Extensive evaluations on large-scale public datasets have demonstrated the efficacy of NIface loss in enhancing recognition accuracy and stability.

关键词： Measurement Technological innovation Image recognition Accuracy Face recognition Focusing Euclidean distance

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Design of Load Frequency controller for Power System Based on Equivalent Input Disturbance Method

Design of Load Frequency Controller for Power System Based o...

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New Energy and Energy Storage System control Summit Forum (NEESSC)

作者： Jianrong Zhang Hang Xu Hongzhang Wang Chuanke Zhang 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: (数字)9798350389012

ISBN: (纸本)9798350389029

In the power system, due to the instability of the external environment, safe and stable operation cannot always be guaranteed, as it frequently encounters varying degrees of external disturbances. In order to mitigate the effects of these disturbances on the system, the power system can operate safely and stably, In this paper, a power system load frequency control (LFC) based on Equivalent Input Disturbance (EID) method is proposed from the perspective of active disturbance suppression. Firstly, the disturbances present in the environment are unified as external disturbances, and then a single area the electric power system model with external disturbance was constructed. Then, a controller algorithm based on EID was designed using EID equivalent processing method and linear matrix inequality method to address the issue of external interference in the power system. Finally, a numerical example is used to validate the effectiveness and accuracy of the controller by simulating with two aspects, fixed perturbation and random perturbation, respectively.

关键词： Perturbation methods Process control Interference Power system stability control systems Linear matrix inequalities Numerical models Frequency control Load modeling Energy storage

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PATH OPTIMIZATION FOR DYNAMIC OBSTACLE AVOIDANCE OF PIONEER ROBOT BASED ON DDPG SMART AGENT

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UPB Scientific Bulletin, Series D: Mechanical Engineering 2023年第2期85卷 29-42页

作者： Zheng, Qingchun Peng, Zhi Zhu, Peihao Zhao, Yangyang Ma, Wenpeng Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China China School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

To improve the path efficiency for dynamic obstacle avoidance algorithms of Pioneer robots, this paper proposes an approach to create deep deterministic policy gradient (DDPG) smart agents with recurrent neural networks (RNN) to optimize the path strategy. This approach is realized by training RNN with the backpropagation (BP) algorithm to train the agent. First, the SolidWorks model and obstacle avoidance model of the Pioneer robot is established. The LIDAR sensor is used to obtain environmental information. Further, deep reinforcement learning obstacle avoidance algorithm based on RNN is presented. The dynamic obstacle avoidance path of the Pioneer robot is further simulated in two different virtual robot experiment platform (V-REP) scenarios. The simulation results show that the proposed algorithm shortens the training time by 26.3% compared with the DDPG algorithm. Our proposed scheme can improve the path efficiency for dynamic obstacle avoidance of the Pioneer robot. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Reinforcement learning

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Cross-user Gesture Recognition Based on Deep Domain Adaptation Networks

Cross-user Gesture Recognition Based on Deep Domain Adaptati...

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第43届中国控制会议

作者： Zhongzheng Fu Xinrun He Haoyuan Wang Xingjian Chen Yixuan Li Jian Huang Ministry of Education Key Laboratory of Image Processing and Intelligent Control Hubei Key Laboratory of Brain-inspired Intelligent Systems School of Artificial Intelligence and Automation Huazhong University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This study introduces an innovative approach for gesture recognition in smart wearable devices using a deep domain adaptation model, focusing on the challenges posed by heterogeneous user environments and the need for precise, adaptable, and personalized gesture recognition systems. Traditional methods based on machine learning and deep learning techniques, while effective, struggle with the variance in data distribution among different users, leading to accuracy challenges. To address this,the study proposes the Domain Kernel-Alignment Adaptation Network(DKAN) model, utilizing a new Kernel-Aligned Multi-kernel Maximum Mean Discrepancy(KAMMD) method within deep networks. By calculating kernel alignments between source and target domains and adjusting weights of Gaussian kernels accordingly, DKAN emphasizes features conducive to transfer learning, enabling more accurate cross-user gesture recognition. The model achieves a significant average accuracy of 97.3% across 21 gestures, highlighting its potential in practical applications. This advancement addresses challenges in traditional gesture recognition methods and sets a new direction for future research in smart wearable technology.

关键词： Gesture recognition Kernel-alignment Domain adaptation

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Simulation and Experiment of Planar Magnetic Sensor

Simulation and Experiment of Planar Magnetic Sensor

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China Instrument and control Society (ACCIS), Academic Conference of

作者： Jiaqi Lu Fang Jin Kaifeng Dong Junlei Song Wenqin Mo Yajuan Hui Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798350350326

ISBN: (纸本)9798350350333

In this paper, aiming at the planar magnetic sensor, the model of the planar magnetic sensor probe is constructed from the principle of magnetic line orbit transfer. The planar magnetic sensor probe is simulated and analyzed by COMSOL Multiphysics software. The influence of the horizontal width, height, length, and relative permeability parameters of the magnetic line orbit transfer structure on the orbit transfer coefficient of the magnetic line orbit transfer structure is studied. The simulation results analyze the influence of the structural parameters of the magnetic line transfer on the transfer coefficient, and the optimal parameter conditions are obtained. In order to verify the simulation results, an experimental test platform was built to test the planar magnetic sensor, and the magnetic line of force rail structure with the best experimental effect was obtained. The magnetic line of the force rail structure selects soft magnetic material with relative permeability greater than 5000, the horizontal width is 3mm, the height is 14mm, and the length of the magnetic line of the force rail structure in the experiment is determined to be 5mm according to the actual demand and the production process. Finally, the conversion efficiency of the planar magnetic sensor to the Z-axis magnetic field can reach 39.9 %. This study provides a research idea for promoting the planar design of magnetic sensors.

关键词： Rails Magnetic flux leakage Magnetic field measurement Magnetic sensors Simulation Force Orbits Permeability Soft magnetic materials Magnetic fields

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Few-shot Pose-free View Synthesis with 3D Gaussian Splatting

Few-shot Pose-free View Synthesis with 3D Gaussian Splatting

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Chinese Automation Congress (CAC)

作者： Yuan Huang Chi Xu 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 Automation China University of Geosciences Wuhan China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Recent advancements in Novel View Synthesis using neural radiance fields and 3D Gaussian splatting have demon-strated promising results. However, these methods conventionally rely on accurate initial poses and point clouds from the model of structure from motion, which poses challenges in sparse input views. To addressing these drawbacks, we introduces an novel method for view synthesis based on 3D Gaussian splatting. Our approach operates on sparse input views without the prerequisite of pose priors, achieving reconstruction and real-time rendering of novel perspectives. For the deficiency of camera poses and point cloud, we employ an end- to-end deep learning model to recover the 3D structure from a few of 2D images to initialize the 3D Gaussian point cloud. In addressing the issue with few-shot, we utilize the differentiable rasterization module to render depth map and apply regulation on it. Additionally, we incorporate supervision between input views by interpolating to generate novel perspectives during training. Experimental results demonstrate that our proposed method significantly enhances the capabilities of 3D Gaussian splatting for novel view synthesis in sparse views and without the necessity of camera pose priors.

关键词： Point cloud compression Training Solid modeling Three-dimensional displays Structure from motion Cameras Rendering (computer graphics) Regulation Real-time systems Image reconstruction

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Investigating day-to-day route choices based on multi-scenario laboratory experiments, Part Ⅱ: Route-dependent attraction-based stochastic process model

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Communications in Transportation Research 2024年第1期4卷 92-107页

作者： Hang Qi Ning Ji Xiaobo Qu Zhengbing He Institute for Advanced Studies in Finance and Economics Hubei University of EconomicsWuhan430205 China Laboratory of Computation and Analytics of Complex Management Systems Tianjin UniversityTianjin300072 China Institute of Systems Engineering College of Management and EconomicsTianjin UniversityTianjin300072 China State Key Laboratory of Intelligent Green Vehicle and Mobility School of Vehicle and MobilityTsinghua UniversityBejing100084 China Senseable City Lab Massachusetts Institute of TechnologyCambridgeMA02139USA

laboratory experiments are one of the important means used to investigate travel choice behavior under strategic *** experiment-based studies have shown that the Nash equilibrium can predict aggregated route choices,while the fluctuations,whose mechanisms are still unclear,continue to exist until the *** understand the fluctuations,this paper proposes a route-dependent attraction-based stochastic process model,which shares exactly the same behavioral foundation introduced in Part I of the study(Qi et al.,2023),i.e.,route-dependent inertia and route-dependent *** model predictions are carefully compared with the experimental observations obtained from the congestible parallel-route laboratory experiments containing 312 subjects and eight decision-making scenarios(Qi et al.,2023).The results show that the proposed stochastic process model can precisely reproduce the random oscillations both in terms of flow switching and route flow ***,an approximated model is developed to enhance the efficiency in evaluating the equilibrium distribution,providing a practical tool to evaluate the impacts of transportation policies in both long-and short-term *** the best of our knowledge,this paper is the first attempt to model and explain experimental phenomena by introducing stochastic process theories,as well as a successful example of applying experimental economics methodology to improve our understanding of human travel choice behavior.

关键词： Day-to-day dynamics Route choice behavior Markov process Stochastic process

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