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检索条件"机构=LABoratory of Intelligent Robotics Automation and Systems - LABIRAS"

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Identification of PMSM Moment of Inertia based on Model Reference Adaptive Algorithm 4

Identification of PMSM Moment of Inertia based on Model Refe...

引用

4th IEEE International Conference on Power, intelligent Computing and systems, ICPICS 2022

作者： Ding, Fan Zhang, Tao Jia, Danping Zhang, Hualiang Pei, Quanshen Huang, Haoran School of Information Science and Engineering Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Dalian University of Technology Dalian China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

A method that can identify the rotational inertia in a timely manner is proposed because the performance of a permanent magnet synchronous motor servo system is easily affected by the rotational inertia. Firstly, principles of model-referenced adaptive recognition algorithm is introduced, and the influence of the adaptive gain on the identification results is analyzed. Then, design a suitable range of adaptive gain value, use the set error value to compare the identification error with the set value, and then select the appropriate gain for identification. Finally, through simulation verification, this method has fast identification convergence speed, high precision and strong anti-disturbance. © 2022 IEEE.

关键词： Adaptive algorithms

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Design of magnetorheological brake with adjustable interdigitated comb for lower limb prostheses and exoskeletons

Design of magnetorheological brake with adjustable interdigi...

引用

2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Shi, Qiuyu Zhao, Xuan Liao, Haisu Lin, Yongji Huang, Ruisen Wu, Xinyu Gao, Fei Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Shatin 999077 Hong Kong

ISBN: (纸本)9798350325706

Magnetorheological (MR) fluids-based devices such as MR dampers and brakes can output a continuously controllable damping force via modulating the magnitude of the applied magnetic field. Owing to low energy consumption and fast response, recently vast MR dampers and brakes are widely studied and explored for lower limb prostheses and exoskeletons. This paper proposed a novel MR brake with adjustable interdigitated comb for lower limb prostheses. Through actively adjusting the area the of the comb engagement, the maximum viscous and field-induced damping torque can be increased or decreased. Because of that, the dynamic adjustment interval of the output damping torque can be increased to meet the function requirements of the prosthetic knee in different walking modes. Magnetic analysis via ANSYS is performed to check the magnetic density of the MR fluid under different excitations. Mathematical models of the damping torque are built. Finally, a prototype of the novel MR brake is fabricated. © 2023 IEEE.

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RESIDUAL LIFE PREDICTION OF LITHIUM BATTERY BASED ON IMPROVED MULTI-OPTIMIZATION ALGORITHM AND SUPPORT VECTOR REGRESSION 14

RESIDUAL LIFE PREDICTION OF LITHIUM BATTERY BASED ON IMPROVE...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2024

作者： Tao, Yulong Wang, Jun Wang, Kai School of Computer Science and Technology Shenyang University of Chemical Technology Shenyang China Key Laboratory of Intelligent Technology for Chemical Process Industry Liaoning Province Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Robotics and Artificial Intelligence Manufacturing Innovation Institute Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781837242672

The lithium-ion battery is increasingly critical in the fields of electric vehicles and sustainable energy. Accurate prediction of the Remaining Useful Life (RUL) of lithium-ion batteries is essential to mitigate risks and minimize potential losses. This paper introduces a novel fusion algorithm, FPSOGWO, which combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) with an enhanced Circle chaos strategy and a random adaptive weighting strategy. The FPSOGWO algorithm, integrated with Support Vector Regression (FPSOGWO-SVR), was utilized to predict the RUL of health factors in lithium batteries. Compared to other optimization algorithms, FPSOGWO exhibits superior optimization speed and value, effectively overcoming issues of local optimality. Specifically, when benchmarked against the Whale Optimization Algorithm-SVR (WOA-SVR), the R-Square values of FPSOGWO-SVR showed improvements of 15.62%, 1.28%, 5.67%, and 10.65% across four different types of batteries. Experimental results demonstrate that FPSOGWO-SVR provides more accurate RUL predictions for lithium batteries, highlighting its potential for broader application in battery health management systems. © The Institution of Engineering & Technology 2024.

关键词： Support vector regression

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intelligent electricity consumption forecasting and electricity-theft analysis method based on deep learning 2

Intelligent electricity consumption forecasting and electric...

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2nd International Conference on Electronic Information Engineering and Computer Technology, EIECT 2022

作者： Yu, Shimao Song, Chunhe Gao, Pengpei Zheng, Haiyang Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350399561

Residential electricity consumption data have great mining value for electricity-theft analysis and electricity consumption forecasting. This paper designs an intelligent electricity consumption forecasting and electricity-theft analysis method based on deep learning. Firstly, the power consumption data of a single user is converted into multi-period data through preprocessing, and the data forecasting is realized by designing a deep neural network model. The electricity-theft data are first amplified through user's power data and electricity-theft labels. And then the time series are converted into two-dimensional tensors for classification and recognition by deep CNN. The classification accuracy of electricity-theft reaches 92.2% compared with RNN method. © 2022 IEEE.

关键词： Forecasting

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Research and Implementation of Industrial Real-Time Ethernet Scheduling Method Based on Time Slot Reuse

Research and Implementation of Industrial Real-Time Ethernet...

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Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Mingxu Gang Bingjun Yan Bo Hu Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

To improve the operation efficiency and real-time scheduling capability of existing industrial control network systems, based on the existing industrial real-time Ethernet communication protocol technology, an industrial real-time Ethernet scheduling method based on time slot reuse is proposed. This method adopts the time-division multiplexing strategy, decomposes the continuous time into different time slots, configures the data of different types of nodes to be transmitted in their respective time slots, uses the peak shift clock synchronization method and timer trigger task mechanism to improve the real-time communication, and uses the time slot multiplexing mechanism to improve the data transmission efficiency; Finally, a test platform is built to verify the proposed method. The experimental results show that the proposed method has high clock synchronization accuracy and real-time scheduling capability.

关键词： Multiplexing Job shop scheduling Protocols Accuracy Industrial control Ethernet Real-time systems

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MADDPG Based Radar Interference Resource Allocation Decision

MADDPG Based Radar Interference Resource Allocation Decision

引用

Chinese automation Congress (CAC)

作者： Sen Jiang Bo Wang Center for Intelligent Systems and Robotics School of HDU-ITMO Research Hangzhou Dianzi University Hangzhou China International Joint Research Laboratory for Autonomous Robotic Systems School of Automation Hangzhou Dianzi University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

For the problem of jamming penetration under the one-to-many scenario with jammer, a real-time radar interference resource allocation method based on the Multi-agent deep deterministic policy gradient (MADDPG) algorithm is proposed. This method describes the interference resource allocation model as a Markov Decision Process (MDP), and designed the state space, action space and reward function for interference resource allocation problem. The jammer is divided into three heterogeneous agents, each responsible for selecting jamming targets, jamming patterns, and jamming power, respectively. These three agents coordinate to enhance the convergence ability of the high-dimensional action space algorithm. Simulation results indicate that the jamming resource allocation method designed in this paper provides better jamming effects on radar positions, higher stability, and effectively improves the operational performance of the jammer.

关键词： Markov decision processes Simulation Radar Interference Stability analysis Sensors Resource management Jamming Thermal stability Convergence

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Motion Capture and Gait Analysis of Ants with Leg Injuries

Motion Capture and Gait Analysis of Ants with Leg Injuries

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Chinese Control Conference (CCC)

作者： Ming Zeng Yuanhao Li Chang Meng Shutong Zhong Zhijing Wang Feng Zhao Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Institute of Robotics and Automation Systems School of Electrical and Information Engineering Tianjin University Tianjin

Many insects in nature, such as ants, recover quickly after sustaining leg injuries. If this capability could be imparted to multi-legged robots, it would drastically enhance their ability to resist destruction and adapt to the environment. In this paper, the Camponotus Japonicus is used as the research object, and its locomotive patterns are studied under different leg-loss conditions. To facilitate this, a high-speed acquisition system, with a dual-view (bottom view and side view) setup, is designed to analyze the ant's linear gaits. Subsequently, the pivotal gait characteristics of the injured ants are extracted by keyframe annotation technology, including the gait phase diagram, duty factor, angle before support, angle before swing, and leg swing range. Lastly, according to the obtained gait characteristics, the general and specific laws of gait adjustment in the absence of one or two legs are systematically analyzed, which provides the basis for parametric settings and strategy optimization of robotic injured gait self-adjustment.

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Feature Space Augmentation and Old Class Space Preservation for Class Incremental Learning

Feature Space Augmentation and Old Class Space Preservation ...

引用

Chinese Control Conference (CCC)

作者： Ming Zeng Siying Li Jiazhe Liu Yuanhao Li Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Institute of Robotics and Automation Systems School of Electrical and Information Engineering Tianjin University Tianjin

The ability of continuously learning new knowledge without forgetting old ones is crucial to adapt to an ever-changing world. This scenario becomes more challenging when the previous data are not available. Current class incremental learning (CIL) approaches tend to incorporate new classes with backward compatibility, i.e., maintaining discriminability of old ones. By contrast, we focus on the extensibility and compatibility for future new classes in the early stage. Our proposed method achieves this by augmenting feature space. In detail, a large number of pseudo-new classes are generated via real example mixture and then train the initial spatially augmented model using pseudo-new classes and the base classes. Besides, considering the fact that it is impossible to maintain backward compatibility with only one prototype for each old class, the updated model also needs to preserve old class space in incremental stages. We employ a certain perturbation to the old class prototypes to effectively avoid old class space from being over-squeezed by the samples of new classes. The experiments on CIFAR-100 and ImageNet-Subset (100 classes) demonstrate that our method substantially reduces the overlap of old and new classes, outperforming state-of-the-art various baselines.

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Multiple Jumping and Perching of a Miniature Mobile Robot

Multiple Jumping and Perching of a Miniature Mobile Robot

引用

IEEE International Conference on robotics and Biomimetics

作者： Longlong Hu Lingqi Tang Hao Chen Yao Li Bing Li Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China Key University Laboratory of Mechanism Machine Theory and Intelligent Unmanned Systems of Guangdong Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Many insects and miniature robots can traverse through narrow spaces via jumping motion; however, successful jumping and landing remains challenging in small-scale. No jumping robot within 90 g have yet demonstrated multiple jumping and perching successfully. Here, we demonstrate continuous jumping and perching of a miniature robot. The origami-inspired structure was manufactured by smart composite microstructure technology. A novel jumping mechanism was designed to load adjustable jump energy actuated by only one motor. A perching mechanism with two adhesive pads was designed to passively couple with the jumping mechanism, achieving perching on the ground and automatically detaching before the next jump. The jumping mechanism achieved adjustable jumping energy, corresponding to jumping height from 0.7 cm to 36.4 cm. The perching mechanism provided successful landing within a wide range (when velocity angle according to vertical direction $=18^{\circ}$ , the velocity magnitude $\leq 3.4\mathrm{m}/\mathrm{s}$ , the body angle $\leq 30^{\circ}$ ). $\text{Unlike}$ typical jumping robots performing uncontrollable landing and free-rolling, our robot kept its body up-righted during the whole movement and avoided free-rolling after landing. The self-contained prototype had 18 g of mass, 6.5 cm of body height, and 36.4 cm of maximum jumping height. Finally, an eccentric motor was integrated to perform multiple omnidirectional jumping and perching movements; this represents significant improvement of motion ability for small-scale mobile robots.

关键词： Insects Biomimetics Prototypes Motors Mobile robots Microstructure

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A Battery Control Strategy for Sequential Utilization of Energy Storage systems in Power Batteries

A Battery Control Strategy for Sequential Utilization of Ene...

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IEEE Advanced Information Technology, Electronic and automation Control Conference (IAEAC)

作者： Bowen Li Shijie Cui Lizhong Zhu College of Automation and Electrical Engineering Shenyang Ligong University Liaoning China 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 Liaoning China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

With the widespread adoption of energy storage systems utilizing power batteries, battery lifespan degradation has become a primary constraint on system performance. To address this issue, this study proposes a lifespan-optimized battery control strategy. Firstly, a battery lifespan calculation model for the energy storage system is established, taking into detailed consideration key parameters such as battery State of Charge (SOC). Secondly, a control strategy based on SOC for charging and discharging is designed, aiming to minimize battery lifespan consumption to the greatest extent possible. Finally, experimental results demonstrate that the proposed control strategy significantly improves the lifespan of the energy storage system compared to existing strategies. This research provides an effective means of control for the long-term stable operation of power battery systems.

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