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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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Optimization of Simulation Parameters of Input Shaper Based on Genetic Algorithm 2

Optimization of Simulation Parameters of Input Shaper Based ...

引用

2nd IEEE International Conference on Advanced Technologies in intelligent control, Environment, Computing and Communication Engineering, ICATIECE 2022

作者： Yi, Tao Pei, Quanshen Li, Deying Wei, Shugong Jia, Danping Zhang, Hualiang Hunan University of Information Changsha China School of Information Science and Engineering Shenyang University of Technology Shenyang China College of Physics and Electronic Engineering Guangxi Normal University for Nationalities Chongzuo China Chinese Academy of Sciences Shenyang Institute of Automation Key Laboratory of Networked Control Systems Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China

ISBN: (纸本)9781665493963

In the motion control system, input shaper is often used to suppress the residual oscillation of high-precision positioning system, but the selection of input shaper parameters is difficult. In view of the difficulty of selecting input shaper parameters, this paper proposes to use genetic algorithm to select the parameters of input shaper. Firstly, the input shaper is designed in the light of the three-loop mathematical model of motor;Secondly, because the genetic algorithm directly optimizes the output of the motor and the algorithm can reduce the influence of the deviation of generator parameters on the parameter selection of the input shaper to a certain extent, the parameters of the input shaper are selected by the genetic algorithm to optimize the output of the motor;In the finish, a comparative experiment between a system with input shaper and a system with simple PID control is carried out. The results show that the optimized system can obtain higher robustness and smaller tracking deviation. © 2022 IEEE.

关键词： Genetic algorithms

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Defect Sample Generation System Based on DCGAN for Glass Package Electrical Connectors

Defect Sample Generation System Based on DCGAN for Glass Pac...

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Chinese intelligent systems Conference, CISC 2020

作者： Liu, Qunpo Wang, Mengke Hanajima, Naohiko Department of Robotics Engineering Henan Polytechnic University 2001 Century Avenue JiaozuoHenan454003 China Henan International Joint Laboratory of Direct Drive and Control of Intelligent Equipment 2001 Century Avenue JiaozuoHenan454003 China College of Information and Systems Muroran Institute of Technology 27-1 Mizumoto-cho Muroran-shiHokkaido050-8585 Japan

ISBN: (纸本)9789811584572

Precision glass packaged electrical connectors are widely used to connect precision modular electrical appliances. Manual detection is currently used due to its small size. In order to improve the detection efficiency and accuracy, deep learning is applied to the automatic detection of the defect. In this paper, in order to solve the problem of lack of defect samples, a defect sample generation system for micro-precision glass package electrical connectors based on deep convolutional generation confrontation network (DCGAN) is constructed. A network model of defect samples based on DCGAN is constructed, and algorithm design, parameter settings, network training and experiments are performed. More than 1,500 samples were generated. Finally, the generated samples were tested for defects (including missing blocks and bubbles). The results show that the samples generated by this method can be used as real samples in defect detection training. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Defects

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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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Optimization of input shaping parameters based on genetic algorithm 4

Optimization of input shaping parameters based on genetic al...

引用

4th International Symposium on Power Electronics and control Engineering, ISPECE 2021

作者： Lu, Xu Jia, Danping Zhang, Hualiang Zhao, Bingjie Zhang, Tao Liu, Yang Yan, Hongyu School of Artificial Intelligence Shenyang University of Technology Shenyang China School of Information Science and Engineering Shenyang University of 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

ISBN: (数字)9781510650374

ISBN: (纸本)9781510650367

In view of the position control vibration problem of permanent magnet synchronous motor, the control model of permanent magnet synchronous motor is simulated by using Simulink software. At the same time, according to the structure of the system model, an input shaper is added to the input end of the system to suppress the vibration of the system. However, the input parameters of the shaper are highly dependent on the parameters of the system model, so it is usually necessary to accurately identify the system model. However, the identification of permanent magnet synchronous motor is often not accurate enough, which makes it difficult to determine the input parameters of the shaper. Aiming at the problem that the input shaper is too dependent on the system, a method of input shaper parameter optimization based on genetic algorithm is designed and verified by experiments. The results show that the parameters of the input shaper with better effect can be selected by genetic optimization, and the dependence of the input shaper on the system model is reduced. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Computer control systems

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An Improved Method for Small Target Recognition Based on Faster RCNN 17th

An Improved Method for Small Target Recognition Based on Fas...

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17th Chinese intelligent systems Conference, CISC 2021

作者： Liu, Qun-po Wang, Qi-jing Hanajima, Naohiko Su, Bo Department of Robotics Engineering Henan Polytechnic University 2001 Century Avenue Jiaozuo Henan454003 China Henan International Joint Laboratory of Direct Drive and Control of Intelligent Equipment 2001 Century Avenue Jiaozuo Henan454003 China College of Information and Systems Muroran Institute of Technology 27-1 Mizumoto-cho Muroran-shi Hokkaido050-8585 Japan

ISBN: (纸本)9789811663239

As one of the most challenging tasks in the field of deep learning, target detection has achieved remarkable results. The existing algorithms have achieved excellent results in the detection of large and medium-sized targets, but the detection accuracy of small targets is not ideal because of their small size and weak features. A small target recognition method based on improved Faster_Rcnn that aims at the problem of low accuracy in small target detection is proposed in this paper. Since the ROI Pooling method in Faster Rcnn might cause quantization errors in the operation process, resulting in inaccurate positioning and other problems during detection, an improved ROI Align method is adopted to eliminate the quantization errors. The cell public data set is used for the experiment, the results show that the average recognition accuracy of the recognition model with improved algorithm is 92.11%, which is an increase of 7%. The method also obtains good effect on NWPU VHR-10 data set, which indicates that it has good universality. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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A largely model independent solution for the position control of a typical inverted pendulum system

A largely model independent solution for the position contro...

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Chinese control Conference (CCC)

作者： Qiang Gao Shasha Chen Yi Li Junfang Li Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems School of Electrical Engineering Tianjin University of Technology Tianjin CN Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin Tianjin CN

An Active Disturbance Rejection based solution is proposed for the position control of a standard inverted pendulum system, demonstrating a largely model independent design that is distinctly different from existing model-based designs from classical as well as modern control theory. The quality of the control loop is further improved with a unique double disturbance observer design, which rejects independently the disturbance and uncertainty in both the pendulum itself and the cart that carries it. This proposed approach offers a promising and practical solution because it's intuitive to understand and easy to tune, in addition to its strong performance and effectiveness shown in both simulation study and real time experimentation.

关键词： Real-time systems Mathematical model Equations control systems Estimation Educational institutions Simulation

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Curved path planning based on 3D vision water immersion ultrasonic nondestructive testing 2

Curved path planning based on 3D vision water immersion ultr...

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2nd International Conference on Computer Vision and Data Mining, ICVDM 2021

作者： Chen, Zheng Wang, Jian Zhang, Hualiang School of Information Engineering Shenyang University of Chemical Technology Liaoning Shenyang110142 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Liaoning Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110169 China

Compared with traditional 2D image processing, 3D point cloud processing has become a hot technology in the industry, but there are few researches applied to nondestructive testing of curved workpieces. This article aims at the non-destructive testing of curved workpieces, using 3D point cloud and robotic arm for water immersion ultrasonic nondestructive testing. Aiming at the 3D point cloud with many outliers, using the commonly used filter in two-dimensional images-the guide filter, the algorithm is improved and used for the filtering and downsampling of the 3D point cloud, and the adjustment of the curved surface workpiece and the robot arm's pose is introduced. Finally, the workpiece was scanned by a robotic arm with a water immersion ultrasonic nondestructive testing system to prove the feasibility of the experiment and improve the detection efficiency of traditional nondestructive testing technology. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Robotic arms

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A new SPICE modeling approach of annular MOSFET in 350 nm commercial CMOS process

A new SPICE modeling approach of annular MOSFET in 350 nm co...

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Electronic Information Engineering and Computer Technology (EIECT), International Conference on

作者： He Cheng Zhijia Yang Chao Zhang Zhipeng Zhang Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China

Annular gate MOSFETs have emerged as potential solutions for radiation-hardened electronics, demonstrating exceptional total ionizing dose tolerance. However, accurate modeling of annular MOSFETs is crucial when designing analog integrated circuits for use in radiation environments, especially when implementing commercial CMOS processes. To enable circuit simulation using tools like SPECTRE/SPICE, foundry-provided PDKs must incorporate a rigorously verified compact model of annular MOSFET behavior. TCAD simulation can then be used to numerically evaluate the current characteristics of the annular MOSFET against the refined compact model constructed from the foundry-provided PDK. In this paper, by aligning the current characteristics of a standard NMOS between TCAD and SPICE simulations, we can verify the material process conditions. Then, based on the material process parameters, the model of the annular gate MOSFET is established using the TCAD simulator. Finally, reasonable agreements are obtained between the TCAD and SPICE simulation results for the I DS -V GS and I DS -V DS characteristics.

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A novel approach to proactive human-robot cooperation

A novel approach to proactive human-robot cooperation

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： O.C. Schrempf U.D. Hanebeck A.J. Schmid H. Worn Intelligent Sensor-Actuator-Systems Laboratory Institute of Computer Science and Engineering Universität Karlsruhe Karlsruhe Germany Institute for Process Control and Robotics Universität Karlsruhe Karlsruhe Germany

This paper introduces the concept of proactive execution of robot tasks in the context of human-robot cooperation with uncertain knowledge of the human's intentions. We present a system architecture that defines the necessary modules of the robot and their interactions with each other. The two key modules are the intention recognition that determines the human user's intentions and the planner that executes the appropriate tasks based on those intentions. We show how planning conflicts due to the uncertainty of the intention information are resolved by proactive execution of the corresponding task that optimally reduces the system's uncertainly. Finally, we present an algorithm for selecting this task and suggest a benchmark scenario.

关键词： Robot sensing systems intelligent robots Uncertainty Application software Humanoid robots Human robot interaction Bayesian methods intelligent sensors Laboratories Computer science

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