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检索条件"任意字段=13th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2024"

共 716 条记录，以下是231-240 订阅

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A data-driven Based Blind Path Recognizing and Tracking control Strategy for a Guided Quadruped Robot 13

A Data-Driven Based Blind Path Recognizing and Tracking Cont...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Liu, Shida Sun, Yunlong Ji, Honghai Wang, Li School of Electrical and Control Engineering North China University of Technology Beijing100000 China Ministry of Education Key Laboratory of Marine Intelligent Unmanned China

ISBN: (纸本)9798350361674

this study addresses the motion control issues of a guiding quadruped robot and proposes a novel data-driven approach for blind path recognition and tracking. the proposed approach consists of two parts, including blind path recognition and robot tracking control. In terms of visual principles, the guiding quadruped robot identifies blind paths based on color using the Otsu threshold segmentation algorithm, combined with Canny edge detection and Hough transform for precise positioning of the blind path. Next, this study presents a model-free adaptive control method utilizing a dynamic linearization technique to follow the identified blind path. the controller is configured with a pseudo partial derivative (PPD) parameter. the proposed method enables accurate recognition and tracking of blind paths by the robot, thereby achieving precise following of blind paths by the guiding quadruped robot. the control aspect of the proposed method relies on a model-free strategy, eliminating the requirement to establish an exact mathematical model of the guiding robot during the controller design process. Instead, the controller can be achieved solely using input and output data of the robot. the proposed method was applied to a real guiding quadruped robot experimental platform, and the experimental results demonstrated a 96.24% accuracy in blind path recognition and an average deviation angle of 0.17 degree in tracking control. the effectiveness of this approach has been validated. © 2024 ieee.

关键词： Multipurpose robots

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On Prescribed Performance ADRC for a Class of Nonlinear systems with Uncertain control Input Gain 13

On Prescribed Performance ADRC for a Class of Nonlinear Syst...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Chen, Zhixiang Xue, Wenchao Yao, Ruiqiao Chen, Sen Song, Xiaojing Qingzhou High-tech Institute Weifang262500 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematics and Statistics Shaanxi Normal University Xi'an710119 China Beijing Institute of Control and Electronic Technology Beijing100089 China

ISBN: (纸本)9798350361674

this paper considers the prescribed performance tracking problem for nonlinear systems with uncertain control input gain. A novel prescribed performance active disturbance rejection control design featured with low computational complexity and large feasible range of the nominal control input gain is proposed. To deal with the tracking error constraint, an output error transformation is introduced to transform the constrained variable into an unconstrained one. A high-gain observer and sliding surface technique are combined to stabilize the converted unconstrained control system. To reduce the computational complexity, a reduced-order extended state observer is designed to estimate the system uncertainties and the high-order derivatives terms of error transformation, which arise from the 'explosion of terms'. Moreover, compared with the existing prescribed performance ADRC, the proposed ADRC method needs only the control direction, relaxing the strong assumption on the nominal control input gain. It can be proved that the resulting closed-loop system is semi-globally uniformly ultimately bounded (SGUUB), which ensures the prescribed performance of the tracking error. Finally, simulation results demonstrate the effectiveness of the proposed control scheme. © 2024 ieee.

关键词： Disturbance rejection

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Force control Method for the Variable Robot Payload in Metal Slag Removal Operation 13

Force Control Method for the Variable Robot Payload in Metal...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Liu, Junhan Xu, Degang Guo, Yuqian School of Automation Central South University Changsha410083 China

ISBN: (纸本)9798350361674

To achieve accurate force control during slag removal operations in the metallurgical industry, the impedance control strategy is commonly employed. A robot designed for slag removal operation has been developed to handle oxidized slag suspended on the surface of molten metal. However, the oxidized slag typically adheres to the end-effector over time, altering the end-effector's weight and impacting the force control's precision. this paper proposes a novel force control strategy to realize the re-identification of variable parameters of the end-effector without stopping the operation of the robot. First, a six-dimensional force sensor is installed between the robot flange and the end-effector. the paper calibrates and calculates the end-effector's parameters, reducing the influence of the end-effector's gravity on force perception. Secondly, a real-time parameter updating algorithm, termed MRLS (Modified Recursive Least Squares Method), is designed specifically for parameter re-identification of variable robot payload. Finally, experimental results demonstrate that the error of the measured weight of the tool to the true value is 1.64%. When the robot is in the slag removal movement process, the error of the contact force estimated is within 0.13N. © 2024 ieee.

关键词： Slags

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AMING:Adaptive-learning Mechanism Based Missing-Value Imputation Networks Using GAN in Industrial Processes 13

AMING:Adaptive-Learning Mechanism Based Missing-Value Imputa...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Zhang, Jiale Yuan, Xiaofeng Wang, Kai Wang, Yalin Yang, Chunhua Gui, Weihua School of Automation Central South University Changsha410083 China

ISBN: (纸本)9798350361674

In industrial production, uncontrollable factors can lead to the inability to collect or transmit data, resulting in the widespread presence of missing values in industrial datasets. these missing data may contain crucial information for production and serve as a vital source for diagnosing equipment malfunctions or issues. Incomplete datasets directly impact subsequent modeling, prediction, and optimization tasks. However, traditional imputation methods struggle to capture complex data distributions and structures, making them unsuitable for production tasks that require high imputation accuracy. Due to its proficiency in simulating data distributions, generative networks have emerged as effective tools for handling missing or corrupted data. the classic GAIN model introduces a prompting mechanism, providing fixed prompts to the discriminator, but this may lead to issues such as model degradation, pattern collapse, and convergence difficulties. In this paper, we propose a novel unsupervised adaptive imputation framework based on GANs, referred to as AMING. It aims to impute missing data in industrial production processes in an unsupervised adaptive manner. Furthermore, we introduce an adaptive learning mechanism framework that dynamically provides learning information to the discriminator during the training process. Finally, we conduct experimental validation on a hydrocracking dataset, demonstrating the superior performance of the AMING method. © 2024 ieee.

关键词： data handling

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Escape with Self-adaptive Decision Radius based on Deep Deterministic Policy Gradient in Pursuit Games 13

Escape with Self-adaptive Decision Radius based on Deep Dete...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Zhou, Xiaojie Yang, Chunxi Wang, Wenbo Sun, Pengqi Kunming University of Science and Technology Faculty of Mechanical and Electrical Engineering Kunming650500 China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming650500 China

ISBN: (纸本)9798350361674

the Pursuit-Evasion (PE) game of Unmanned Surface Vehicles (USVs) is a classic antagonistic problem for the intelligent agent system. To enhance the escaping success rate of evaders with better effort, this paper proposes an escape strategy based on the geometrical characteristics of Apollonius circles. An improved self-adaptive escaping strategy for the evader utilizing the deep deterministic policy gradient algorithm is proposed. then, the criteria for successful encirclement by pursuer are given. A DDPG algorithm-based framework is proposed on the basis of markov decision process formulation. Specifically, an action space based on adaptive decision radius of evader is designed. Our simulation shows the proposed method has more advantages in terms of escape distance and escape time. © 2024 ieee.

关键词： Unmanned surface vehicles

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Adaptive Depth Estimation of Homography-Based Visual Servo with Finite-time Convergence 13

Adaptive Depth Estimation of Homography-Based Visual Servo w...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Fang, Qiwen Wang, Xian Huangl, Yingbo He, Haoran Kunming University of Science and Technology Faculty of Mechanical and Electrical Engineering Kunming650500 China Kunming University of Science and Technology Yunnan Key Laboratory of Intelligent Control and Application Kunming650500 China

ISBN: (纸本)9798350361674

Although the homography-based visual servo (HBVS) has been studied for many decades, how to obtain the depth information with fast and accurate convergence performance has not been fully studied. In this paper, a finite-time (FT) adaptive depth estimation method is suggested for the manipulator regulation of the eye-in-hand (EIH) visual servo system. To realize this objective, a linearized camera model including depth information is first established. To obtain the depth, a set of auxiliary variables are constructed to extract the depth estimation error with a series of simple algebraic calculation. then, inspired by the sliding mode control, a FT adaptive depth estimation algorithm is developed, in which the predictor and/or observer error are not required, but the depth estimation error is employed to drive the estimation toward to its true value within finite time. With the estimated depth, the HBVS controller of the EIH system can regulate the robot arm to the desired position with fast response. Finally, comparative simulation results are given to show the efficiency of the proposed method. © 2024 ieee.

关键词： Sliding mode control

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UGV 3D Scene Mapping and Real-Time Target Detection in Underground Space 13

UGV 3D Scene Mapping and Real-Time Target Detection in Under...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Duan, Shuai Xu, Jingbang Huang, Zhixin Wang, Jing Zhou, Meng School of Electrical and Control Engineering North China University of Technology Beijing100144 China

ISBN: (纸本)9798350361674

this paper focuses on 3D scene mapping and real-time target detection techniques for underground space based on small UGV. Both techniques are essential for small UGV to accomplish tasks in underground spaces. Complex environment and insufficiently light make some techniques inapplicable in underground space. the limited calculation power of small UGV leads to complex technique that cannot satisfy real-time requirements. In this paper, LiDAR is chosen as the sensor for mapping and target detection to enable small UGV accomplish real-time tasks in underground space. Considering factors such as calculation power and accuracy, this paper applies the LeGO-LOAM algorithm for localization and mapping, and the PointPillars algorithm for target detection. the experimental environments in this paper are chosen in an underground garage and NCUT campus to verify the algorithm deployed in small UGV. the experimental results show that the deployed algorithm has good robustness to build accurate maps and target detection in real time. In summary, the work in this paper provides important technical support for underground space mapping and target detection based on small UGV. © 2024 ieee.

关键词： Mapping

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A Velocity Tracking Method for Quadruped Robot with Rhythm controller 13

A Velocity Tracking Method for Quadruped Robot with Rhythm C...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Zhang, Xiaoping Wu, Yitong Xiu, Zhongchen School of Electrical and Control Engineering North China University of Technology Beijing100144 China University of Cambridge Department of Engineering CambridgeCB2 1PZ United Kingdom

ISBN: (纸本)9798350361674

In the motion performance of quadruped robots, the velocity is a very important item. It is hoped that a quadruped robot can move stably in accordance with the expected velocity. In this work, a velocity autonomous tracking method is proposed to realize real-time velocity tracking during the movement of quadruped robots. Firstly, the gait learning process of a quadruped robot is completed based on deep reinforcement learning, and the velocity adaptation ranges of different gaits are obtained. After that, the gait selection and velocity tracking controller selects the gait according to the desired velocity firstly, and makes periodic dynamic adjustment according to the velocity error signal after, thus completing the velocity tacking of the robot. the effectiveness of the method is verified by simulation experiments. the quadruped robot can well complete the velocity tracking task under different gaits, and the movement is relatively stable. © 2024 ieee.

关键词： Multipurpose robots

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Distributed control of Heterogeneous Modular Flight Arrays under the Limited Space Constraints 13

Distributed Control of Heterogeneous Modular Flight Arrays u...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Liu, Jianhui Yang, Chunxi Zhang, Xiufeng Li, Yiming Kunming University of Science and Technology Faculty of Mechanical and Electrical Engineering Yunnan650500 China

ISBN: (纸本)9798350361674

Modularized aerial vehicles are now receiving more and more attention for its flexibility and scalability. How to achieve fast and safe traversal among modular unmanned aerial vehicle (UAV) swarms in the limited space is a critical issue for them to accomplish complex missions. Motivated by cooperative control method of UAV swarms in structured airspace, this paper takes the modular flight array platform developed by our research team as an object. And then an advection model is established to discuss the dynamic process of multiple modular flight arrays. By designing two regions, a type of collision avoidance schedule is proposed. Moreover, a distributed controller based on the group of heterogeneous modular flight arrays is developed to solve air traffic problem among them under limited space constraints. Formal analyses are made to show that all modular flight arrays can reach their respective destination lines and avoid collisions. In order to make the modular flight arrays complete their respective missions quickly, a collision avoidance strategy is proposed, which shorten the convergence time and effectively avoids the oscillation phenomenon. Finally, simulation example is given to verify the effectiveness of the proposed method. © 2024 ieee.

关键词： Unmanned aerial vehicles (UAV)

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Design and Stability Analysis of Vehicle Platooning control in Zero-Trust Environment 13

Design and Stability Analysis of Vehicle Platooning Control ...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Zhu, Ling Huang, Darong Na, Yuhong Li, Xinrong Institute of Information Science and Engineering Chongqing Jiao Tong University Chongqing400074 China School of Artificial Intelligence Anhui University Hefei230001 China

ISBN: (纸本)9798350361674

Vehicle platoon control constitutes a pivotal aspect of intelligent transportation system development, most of the previous research on vehicle platoon control is carried out under mutual default trust, without considering the trust factor between interconnected vehicles, the trust factor between vehicles has a significant influence on the cooperative behavior of the vehicles, the way of information sharing, and the security of the vehicles, etc. In the actual traffic scenario, vehicle cooperative process is often In real transportation scenarios, the process of vehicle collaboration is often subject to various network attacks, so vehicle collaboration is always facing security threats. Zero-trust network is a kind of de-boundary network, which requires individuals in the network to 'never trust and verify in real-time', and vehicle platoon control can be placed in the zero-trust environment to avoid these problems. Firstly, we employ the C-F uncertainty inference method to assess the trust of nodes of interconnected vehicles. Secondly, we constructed a vehicle platoon dynamics model containing node trust, and based on this, we constructed a vehicle platoon dynamics model containing node trust, and designed a distributed controller. Finally, the effectiveness of the method proposed in this paper is verified by numerical simulation experiments. © 2024 ieee.

关键词： Maneuverability

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