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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Xiao, Feng Zhang, Feilong Han, Bing Zhang, Hualiang Shenyang University of Technology School of Information Science and Engineering Shenyang110870 China University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China School of Mechanical Engineering Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou310027 China

ISBN: (纸本)9798350325706

The performance of dynamic control is intimately tied to modeling accuracy. However, traditional estimation methods and friction models, such as the least squares method and the Coulomb plus viscous model, fail to reflect the actual characteristics accurately. Particularly, the linear nature of the Coulomb plus viscous model overlooks the nonlinear static features of joint friction at slower velocities. To improve the rationality of the model structure, we integrate the Stribeck friction model into the Coulomb plus viscous model. However, introducing such nonlinearities compromises the applicability of the least squares method. As a countermeasure, we propose a new strategy that combines the least square method and the Quasi-Newton iterative method to identify the parameters of the modified nonlinear model. Additionally, the design of the excitation trajectory is critical to achieve high identification accuracy. We utilized the inverse of the smallest singular value of the observation matrix as the objective function. By minimizing it with the interior point method, we generate the excitation trajectory well-suited to stimulate dynamic characteristics. Then we leverage the discrepancies between the measured and estimated torques to assess the precision of the dynamic parameters of the manipulator. Remarkably, our proposed algorithm reduces the mean absolute error of the estimated torque by over 20.40%. Finally, an experiment of the industrial manipulator by hand guiding grab and drag is performed and shows that the proposed approach can provide the manipulator with comprehensive torque compensation. © 2023 IEEE.

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Paper-Based Microfluidic Chips for Wide Time Range Fluid control Based on Knife Crafting and Laser Cutting

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SSRN 2024年

作者： Zhong, Songyi Xue, Liqian Wang, Yue Liu, Na Li, Long Zhang, Quan Yue, Tao School of Mechatronics Engineering and Automation Shanghai University Shanghai200444 China School of Future Technology Shanghai University Shanghai200444 China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai200444 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province Hangzhou310058 China

In recent years, paper-based microfluidic chips have emerged as a promising microfluidic platform due to their simplicity, low cost, portability, and ease of fabrication. They have been applied in various fields such as biological analysis, environmental monitoring, and medical diagnostics. However, the current paper-based chips made of nitrocellulose membrane still can be improved in liquid flow rate control. To address these issues, a novel paper-based microfluidic chip is designed to control liquid in a wide time range, and the liquid delay and acceleration control are realized by laser cutting and knife crafting respectively. Microfluidic chip’s hydrophobic boundaries can be manufactured in a one-step process using laser cutting, taking less than 10 seconds. Additionally, the structural parameters of microgrooves, which have a significant impact on flow rate, can be precisely controlled using a scalpel-based cutting platform. This enables efficient and consistent microgroove processing. Furthermore, experimental optimization of laser cutting and knife crafting parameters is performed, along with an exploration of factors influencing the delay and acceleration effects in the chip structures. The effectiveness of these processing methods is validated through practical applications. In summary, this study realizes a wide time range fluid control in paper-based microfluidic chips, which can achieve delay and acceleration in the range of −57.8% to +828.3%, thus expanding the application range of paper-based microfluidic chips. © 2024, The Authors. All rights reserved.

关键词： Microfluidic chips

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Hierarchical Whole-body control of the cable-Suspended Aerial Manipulator endowed with Winch-based Actuation

Hierarchical Whole-body Control of the cable-Suspended Aeria...

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IEEE International Conference on robotics and automation (ICRA)

作者： Yuri S. Sarkisov Andre Coelho Maihara G. Santos Min Jun Kim Dzmitry Tsetserukou Christian Ott Konstantin Kondak Institute of Robotics and Mechatronics German Aerospace Center (DLR) Wessling Germany Robotics and Mechatronics Group University of Twente Enschede The Netherlands Dextrous Robotics Inc. Memphis United States Instituto Tecnológico de Aeronáutica São José dos Campos Brazil Intelligent Robotic Systems Lab Korea Advanced Institute of Science and Technology (KAIST) Daejeon Korea Automation and Control Institute TU Wien Vienna Austria

During operation, aerial manipulation systems are affected by various disturbances. Among them is a gravitational torque caused by the weight of the robotic arm. Common propeller-based actuation is ineffective against such disturbances because of possible overheating and high power consumption. To overcome this issue, in this paper we propose a winch-based actuation for the crane-stationed cable-suspended aerial manipulator. Three winch-controlled suspension rigging cables produce a desired cable tension distribution to generate a wrench that reduces the effect of gravitational torque. In order to coordinate the robotic arm and the winch-based actuation, a model-based hierarchical whole-body controller is adapted. It resolves two tasks: keeping the robotic arm end-effector at the desired pose and shifting the system center of mass in the location with zero gravitational torque. The performance of the introduced actuation system as well as control strategy is validated through experimental studies.

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Design and implementation of FPGA-based hardware acceleration system for target detection

Design and implementation of FPGA-based hardware acceleratio...

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2022 Chinese automation Congress, CAC 2022

作者： Zhan, Canyu Zhao, Bingjie Zhang, Huangliang Yan, Zhongpeng Wu, Jie Yuan, Da Shenyang University of Chemical Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Shenyang University of Technology Shenyang China

ISBN: (纸本)9781665465335

Since the application of target detection in convolutional neural networks is becoming more and more widespread, and the computational volume is increasing, the complexity of the network hierarchy and the memory requirements are gradually increasing, so according to the Field Programmable Gate Array (FPGA) parallel computing characteristics, using FPGA to accelerate the convolutional neural network hardware, can design a CPU+FPGA target detection hardware acceleration system. The system adopts the YOLOv2 target detection algorithm and divides the tasks according to the network structure of the algorithm, and at the same time, it quantifies the 32-bit floating-point numbers of the algorithm with 16-bit fixed points, optimizes the convolutional, pooling, and reordering layers of the algorithm, and finally designs the algorithm by using the HLS high-level synthesis. The system uses PYNQ-Z2 platform to implement the convolutional neural network YOLOv2, and the final system performance reaches 27.06GOPs (Giga Operations Per Second, 1 billion operations/s), and the power consumption is only 2.609W, compared to CPU (E5-2620V4), its performance is 6.58 times that of CPU, and the power consumption is only 3% of the CPU, which has certain advantages compared with current target detection systems. © 2022 IEEE.

关键词： Convolution

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Weld Defects Detection by Neural Networks Based on Attention Mechanism

Weld Defects Detection by Neural Networks Based on Attention...

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IEEE Information Technology and mechatronics Engineering Conference (ITOEC)

作者： Guang Yang Zhifeng Liu Jianjun Wang Shuping Cui State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

Welding technology plays an indispensable role in ship construction, and its maturity has a direct impact on the quality of shipbuilding. The weld seam, being the weakest part of a welded structure, significantly affects the structural strength, service life, and safety reliability of ships. However, the current identification of weld defects in the ship industry relies on manual methods, which are subjective and prone to error. To address this issue, this paper presents a novel approach by collecting weld images from actual ship scenes, preprocessing them to eliminate noise and highlight defect features, and proposing a Transformer-based improved target detection model (T-OBJDETC) to enhance the recognition accuracy of the model.

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A Novel Hybrid Method for Fault Diagnosis of Industrial Equipment Based on Vibration Signals 14

A Novel Hybrid Method for Fault Diagnosis of Industrial Equi...

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14th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Hangzhou 2023

作者： Tao, Sen Wang, Kai Zeng, Peng Yu, Tianda Wu, Hao Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110169 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110169 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Nuclear Power Institute of China Chengdu610213 China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing400044 China

ISBN: (纸本)9798350301359

Industrial equipment reliability is a critical issue that smart manufacturing systems must address. Implementation of online fault diagnosis for industrial equipment is a promising technology that can improve equipment reliability. Vibration analysis is a popular technique for equipment condition monitoring. For the non-linear and non-stationary features of industrial vibration signals, a hybrid model based on wavelet transform (WT), support vector machine (SVM), and grey wolf optimization algorithm (GWO) is proposed. The time-frequency domain features of fault signals are extracted by wavelet transform to solve the non-linearity of signals, and the obtained feature vectors are input into SVM for classification. Aiming at the problem of setting penalty coefficient and kernel function parameters, GWO is introduced to seek hyperparameters by using the hunting principle of wolves. In the experimental part, firstly, the comparison of the GWO-WT-SVM, GWO-SVM and SVM models was carried out. Secondly, Comparison with classical classification algorithms is made. Apparently, the GWO-WT-SVM model achieves higher accuracy than other models in bearing fault diagnosis. © 2023 IEEE.

关键词： component Fault diagnosis GWO PHM SVM

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Actor-Based Learning Framework for the Co-Optimization of Modular Cpps Scheduling and control with Stochastic Processing Times

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SSRN 2023年

作者： Wan, Guangxi Dong, Xiaoting Dong, Qingwei He, Yunpeng Zeng, Peng State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

Scheduling with stochastic processing times is a kind of dynamic scheduling in production systems. The current scheduling optimization problem is formulated in the scheduling domain, which ignores the underlying synergies for optimization objectives between scheduling and control. To address this problem, we propose and formulate the problem of the co-optimization of scheduling and control with stochastic processing times (COSC-SPT) with a system respective view. To solve the COSC-SPT, we model the decision-making process as a Markov decision process and propose an actor-based learning framework to facilitate problem solving. To verify the feasibility of the proposed framework and the effectiveness of the formulated COSC-SPT, a real reducer assembly system is taken as a use case. The results of experiments demonstrate that the COSC-SPT provides better solutions than conventional scheduling problems. Keywords: Actor, cyber-physical production systems, optimization, scheduling, stochastic processing time. © 2023, The Authors. All rights reserved.

关键词： Markov processes

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A Robust Surveillance System for AGV Using Forward-Downward Visual Measurements

A Robust Surveillance System for AGV Using Forward-Downward ...

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第35届中国控制与决策会议

作者： Sichao Zhang Wei Liang Xudong Yuan Haibo An Meng Zheng Yinlong Zhang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences Science and Technology on Information Systems Engineering Laboratory the 28th Research Institute of CETC

Automatic Guided Vehicle(AGV) has been widely used in the warehouse for transporting the bulky and heavy ***,the AGV may deviate the regular trajectories in presence of incorrect or untimely commands sent form the server due to,e.g.,cyber attacks,unexpected blocks of the wireless *** order to ensure AGV running safely,this paper presents a visual surveillance system by making full use of the measurements from the forward and downward ***,the forward camera estimates the AGV positions and attitudes by tracking the surrounding landmarks detected from the forward image ***,the downward camera is used to detect the QR codes fixed on the floor and estimate the AGV poses in the absolute reference *** from that,the AGV poses from the downward camera could correct scale and poses estimated the forward *** proposed method has been extensively performed on the developed *** results proves the effectiveness in using the complementary forwarddownward visual measurements for AGV security surveillance.

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Active model-based nonlinear system identification of quad tilt-rotor UAV with flight experiments

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Science China(Information Sciences) 2022年第8期65卷 105-119页

作者： Zhong LIU Didier THEILLIOL Yuqing HE Feng GU Liying YANG Jianda HAN Xi'an Modern Control Technology Research Institute Faculte des Sciences et Techniques CRAN UMR 7039CNRSUniversity of Lorraine State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences College of Artificial Intelligence Nankai University

To propose an accurate and less complex model of a special unmanned aerial vehicle(UAV),namely tilt-rotor UAV(TRUAV), this study identifies the active model-based nonlinear system of a quadTRUAV. First, a nominal nonlinear model of the vehicle is formulated. Some unstructured nonlinearities are ignored to reduce the complexity of the model. Then, due to the unstable dynamics of the open-loop system,the format of this nominal model is considered to design an innovative smooth-switch attitude control via interconnection and damping assignment passivity-based control(IDA-PBC). Active model-based nonlinear system identification is studied for the vehicle with the designed control method and flight *** model error vector is defined and estimated by the unscented Kalman filter(UKF) to improve the accuracy of the model. The main contribution of this paper is to identify the nominal nonlinear model and to develop an active model method of the quad-TRUAV. The attitude control method with an innovative smooth-switch structure is another contribution to flight experiments. Numerical results are displayed to present the experimental results and effectiveness of the proposed nonlinear models.

关键词： tilt-rotor unmanned aerial vehicle flight control nonlinear system identification active model method unscented Kalman filter

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A Weighting Factors Autotuning Strategy for Model Predictive Torque control of Permanent Magnet Synchronous Motor Based on Adaptive Multi-Objective Black Hole Algorithm

A Weighting Factors Autotuning Strategy for Model Predictive...

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Chinese control Conference (CCC)

作者： Zixiang Zhou Tao Wu School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China System Integration and Industrial Robotics Laboratory Wuhan P. R. China

The rational design of weighting factors in the cost function for finite control set model predictive torque control (FCS-MPTC) has been a matter of great interest in power electronics and electrical drives. In order to solve this problem, a weighting factors autotuning strategy for FCS-MPTC of permanent magnet synchronous motor (PMSM) based on the adaptive multi-objective black hole algorithm (AMOBH) is proposed. In this paper, the design process of the FCS-MPTC algorithm is first analyzed in detail. Then, an AMOBH algorithm that can take into account both population convergence and population diversity is introduced, and based on this algorithm, the design problem of the weighting factors is successfully transformed into a multi-objective optimization problem by means of reconstructing the cost function and designing the motor operation information collected in real time as the objective functions of the multi-objective optimization algorithm. Simulation results show that the proposed method can find a set of weighting factor combinations suitable for different working condition requirements, and these weighting factors can effectively improve the operation performance of the PMSM system.

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