2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)最新文献_第3页

Hybrid Event-Triggered Adaptive Control for Nonlinear Systems with Dynamic Uncertainties and Unknown disturbances 具有动态不确定性和未知扰动的非线性系统的混合事件触发自适应控制

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023818

N. Pang, Xin Wang

引用次数: 0

Research on the latest calibration technology of vector Network Analyzer 矢量网络分析仪最新标定技术研究

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023671

Yongrui Guo, Shubiao Li, Zhiyuan Zhuang

{"title":"Research on the latest calibration technology of vector Network Analyzer","authors":"Yongrui Guo, Shubiao Li, Zhiyuan Zhuang","doi":"10.1109/YAC57282.2022.10023671","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023671","url":null,"abstract":"Calibration and error correction technology, as one of the key technologies for vector network analyzer to achieve high precision measurement, has always been the focus of researchers’ continuous efforts to explore and innovate. With the development of microwave network analysis theory and technology, vector network analyzer calibration and error correction technology in the measurement speed, accuracy, usability, adaptability and other aspects have undergone fundamental changes. In this paper, the latest development of vector network analyzer calibration and error correction technology is described in detail. New calibration technology not only enhances vector network analyzer error correction function, and expands the vector network analyzer applications - including not only multiport devices, some special test environment and test problems of traditional S parameter linear test areas, including chip, fixture and on-wafer such as microelectronic test in field, It also includes mixer and power amplifier gain compression, intermodulation and other nonlinear characteristics testing fields. At the same time, the intelligent and automatic calibration mode represented by electronic calibration technology pushes the vector network analyzer calibration and error correction technology to another height","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130270370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Neural Network Fixed-Time Control for Robotic Manipulators with Input Quantization 输入量化的机械臂自适应神经网络定时控制

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023889

Donghao Zhang, Wenkai Niu, Linghuan Kong, Shuang Zhang, Xinbo Yu

引用次数: 0

Improved Attention-based AE-LSTM for Short-term Power Load Forecasting 改进的基于注意力的AE-LSTM短期电力负荷预测

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023759

Li Qian, Zhao Yuelei, Zheng Haiqing, Sun Xiaoyun, Han Guang, Zhang Jun, Liu Baoan, Guo Kang

{"title":"Improved Attention-based AE-LSTM for Short-term Power Load Forecasting","authors":"Li Qian, Zhao Yuelei, Zheng Haiqing, Sun Xiaoyun, Han Guang, Zhang Jun, Liu Baoan, Guo Kang","doi":"10.1109/YAC57282.2022.10023759","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023759","url":null,"abstract":"Power load forecasting, which can increase system stability, is a more crucial link in the planning of the power system and the construction of sectors associated to power. Random feature changes in short-term load forecasting make the forecasting process more difficult. A more advanced attention-based AE-LSTM (Auto Encoder-Long Short-Term Memory) is a multivariate prediction model that aims to address the drawbacks of feature extraction of various information in numerous time steps and the substantial amount of computing in the training process. AE can obtain different kinds of temporal features to obtain related feature vectors. Since AE-LSTM has limitations in paying dynamic degrees of attention to sub-window characteristics over multi-time step. Through the idea of competitive random search, an improved attention learning algorithm is introduced to optimize AE-LSTM. Using attention sampling to mine relevant information in temporal features, and striving for random search, the model can reduce the phenomenon of local optimization. The experimental results verified the effectiveness of the proposed prediction model.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130469364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Path Planning of Six-wheel-drive Rescue Robot Based on A* Algorithm and Artificial Potential Field Method 基于A*算法和人工势场法的六轮驱动救援机器人路径规划

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023654

Hongqian Zhao, Zhanshun Cheng

{"title":"Path Planning of Six-wheel-drive Rescue Robot Based on A* Algorithm and Artificial Potential Field Method","authors":"Hongqian Zhao, Zhanshun Cheng","doi":"10.1109/YAC57282.2022.10023654","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023654","url":null,"abstract":"In view of the rescue robot path planning under complicated environment and unknown disturbance failure problem, path planning of complex environment for rescue robot based on the improved Hybrid algorithm is proposed in this paperThe hybrid algorithm improves the traditional A* and introduces artificial potential field into A*. More and more reliable path planning algorithms need to be studied to ensure that the rescue robot can reach the rescue scene quickly, including the heuristic function H(n) is dynamically weighted, and redundant nodes in the path are removed. In my paper, the search speed of A* algorithm is improved by dynamically changing the weight size, the redundant nodes are eliminated to reduce the path length, and the APF is introduced to avoid obstacles to make the rescue robot reach the end point successfully and efficiently. We can see from the simulation results-the hybrid algorithm has better performance, the Search time reduced by 34.09%, the length is shortened by 5.75%, and the turning points are shortened by 36.28%. The results show that this method has obvious optimization effect and certain feasibility.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134115230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Active control for a flexible aircraft wing in the presence of external disturbances 存在外部扰动时柔性机翼的主动控制

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023596

Yun Fu, Yunpeng Liu, Zuoxuan Gan

引用次数: 0

Research on global energy optimization of central air conditioning system based on particle swarm optimizer with penalty functions 基于惩罚函数粒子群优化器的中央空调系统全局能量优化研究

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023675

Qi Li, Y. Su, Danhong Zhang, Chenyu Liu, Huajun Zhang, Z. Yan

引用次数: 0

BEBLID-SLAM: An Efficient Feature-Based Monocular SLAM System 盲眼SLAM:一种高效的基于特征的单目SLAM系统

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023629

Feng Yang, Baibing Jie, Hongxuan Song, Haotian Li

引用次数: 0

ERT image reconstruction based on DPSO-ATikhonov regularization algorithm 基于DPSO-ATikhonov正则化算法的ERT图像重建

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023683

Xingkun Dong, Hongwei Ren, Qian Lu, Zheng Zhuang, Xin Cheng, L. Qin

引用次数: 0

Neural network based control for UUV with deployment on the High-level Synthesis 基于神经网络的UUV高级综合部署控制

2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC) Pub Date : 2022-11-19 DOI: 10.1109/YAC57282.2022.10023703

Zehua Peng, Xiaobo Lin, Kejian Guo, C. Hao

{"title":"Neural network based control for UUV with deployment on the High-level Synthesis","authors":"Zehua Peng, Xiaobo Lin, Kejian Guo, C. Hao","doi":"10.1109/YAC57282.2022.10023703","DOIUrl":"https://doi.org/10.1109/YAC57282.2022.10023703","url":null,"abstract":"With the improvement of marine technology, unmanned underwater vehicle (UUV) plays an important role in marine survey operations, environment monitoring and so on. In practical applications, the neural network (NN) based controller is able to compensate for the uncertain and nonlinear disturbance caused by UUV dynamic model. However, due to the performance limitation of embedded hardware, it is still a challenge to deploy the NN based controller. In this paper, Field Programmable Gate Array (FPGA) with parallel computing ability is used to realize the deployment of NN based controller. The High-level Synthesis (HLS) technology is utilized to accelerate the computation of the NN. The hardware in loop simulations show that the longest computing time on FPGA platform is about 6.51us, which is far less than the maximum 1400us computing time on raspberry pi platform. The average relative error of the controller output deployed on FPGA and Raspberry pi is less than 0.5%. The design method not only improves the calculation speed, but also guarantee high real-time response in the UUV control task.","PeriodicalId":272227,"journal":{"name":"2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132819632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0