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Iterative Parameter Estimation for Photovoltaic Cell Models by Using the Hierarchical Principle
Xiangxiang Meng,Yan Ji,Junwei Wang 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.8
This paper considers the parameter estimation problems of photovoltaic cell models. In order to overcome the complexity of the model structure, through applying the hierarchical identification principle and decomposing the photovoltaic cell model into two sub-models with a smaller number of parameters. The nonlinear identification model becomes a combination of a linear sub-model and a nonlinear sub-model. A two-stage gradient-based iterative and a two-stage Newton iterative algorithms are proposed to estimate the parameters of photovoltaic cell models by using the negative gradient search and the Newton method. The performance of the proposed algorithms is assessed by using the simulation from the experimental data, and the evaluation results test the effectiveness of the proposed algorithms. In particular, the model built by using the obtained parameter estimates can fit the I-V curve, the P-V curve and the maximum power point well.
Haibo Liu,Junwei Wang,Yan Ji 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.8
Maximum likelihood methods have wide applications in system modeling and parameter estimation. For the purpose of improving the precision of parameter estimation, this paper presents a maximum likelihood recursive generalized extended least squares (ML-RLS) algorithm for a bilinear-parameter system with autoregressive moving average noise based on the over-parameterization identification model. An over-parameterization-based recursive generalized extended least squares algorithm is presented to show the effectiveness of the proposed ML-RLS algorithm for comparison. The simulation test shows that the proposed algorithm has a higher estimation accuracy than the recursive least squares algorithm.
Evaluation of energy correction algorithm for signals of PET in heavy-ion cancer therapy device
Niu, Xiaoyang,Yan, Junwei,Wang, Xiaohui,Yang, Haibo,Ke, Lingyun,Chen, Jinda,Du, Chengming,Zhang, Xiuling,Zhao, Chengxin,Kong, Jie,Su, Hong Korean Nuclear Society 2020 Nuclear Engineering and Technology Vol.52 No.1
In order to solve the contradiction between requirements of high sampling rate for acquiring accurate energy information of pulses and large amount of data to be processed timely, the method with an algorithm to correct errors caused by reducing the sampling rate is normally used in front-end read-out system, which is conductive to extract accurate energy information from digitized waveform of pulse. The functions and effects of algorithms, which mainly include polynomial fitting with different fitting times, double exponential function fitting under different sampling modes, and integral area algorithm, are analyzed and evaluated, and some meaningful results is presented in this paper. The algorithm described in the paper has been used preliminarily in a prototype system of Positron Emission Tomography (PET) for heavy-ion cancer therapy facility.
A real-time sorting algorithm for in-beam PET of heavy-ion cancer therapy device
Ke, Lingyun,Yan, Junwei,Chen, Jinda,Wang, Changxin,Zhang, Xiuling,Du, Chengming,Hu, Minchi,Yang, Zuoqiao,Xu, Jiapeng,Qian, Yi,She, Qianshun,Yang, Haibo,Zhao, Hongyun,Pu, Tianlei,Pei, Changxu,Su, Hong Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.10
A real-time digital time-stamp sorting algorithm used in the In-Beam positron emission tomography (In-Beam PET) is presented. The algorithm is operated in the field programmable gate array (FPGA) and a small amount of registers, MUX and memory cells are used. It is developed for sorting the data of annihilation event from front-end circuits, so as to identify the coincidence events efficiently in a large amount of data. In the In-Beam PET, each annihilation event is detected by the detector array and digitized by the analog to digital converter (ADC) in Data Acquisition Unit (DAQU), with a resolution of 14 bits and sampling rate of 50 MS/s. Test and preliminary operation have been implemented, it can perform a sorting operation under the event count rate up to 1 MHz per channel, and support four channels in total, count rate up to 4 MHz. The performance of this algorithm has been verified by pulse generator and <sup>22</sup>Na radiation source, which can sort the events with chaotic order into chronological order completely. The application of this algorithm provides not only an efficient solution for selection of coincidence events, but also a design of electronic circuit with a small-scale structure.
Qijun Peng,Junwei Zhang,Yan Wang 한국화학공학회 2013 Korean Journal of Chemical Engineering Vol.30 No.6
Phase behavior of aqueous two-phase systems (ATPS) containing cationic (SDS) and anionic (CTAB) surfactants and its application to theanine extraction was studied. Results indicated the ATPS could form under the certain SDS/CTAB molar ratio; there was a reasonable consistency between the conductivity and the formation region of ATPS,and the viscosity was higher in the formation region of ATPS. Additionally, the phase ratio increased with increase of CATB concentration, and the interfacial film between the top phase and the bottom phase was resilient. Moreover,the theanine extraction with ATPS was realized in the waste liquid of tea polyphenol production (WLTPP), and the partition coefficient of theanine decreased with increase of WLTPP concentration, whereas the extraction rate of theanine increased. The partition coefficient decreased with increasing SDS/CTAB molar ratio, and the extraction rate of theanine increased with increase of SDS/CTAB molar ratio.
Cutting Parameter Optimization for Reducing Carbon Emissions Using Digital Twin
Lili Zhao,Yilin Fang,Ping Lou,Junwei Yan,Angran Xiao 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.22 No.5
With the exacerbation of global environmental concerns, manufacturing industries need to consider the impact of carbon emissions from manufacturing processes. The selection of the parameters in the machining process greatly influences on carbon emissions and machining efficiency. Hence dynamically optimizing the machining process parameters is a significant means to reduce carbon emissions according to the real-time perception of the machining conditions. In the paper, a method of cutting parameter optimization is presented on basis of the construction the digital twin of a CNC machine tool. In this method, an ontology on CNC machining process is established to be used as a communication bridge for understanding the semantic of the real-time interaction between the physical machine and the virtual twin. And a dynamic optimization method on cutting parameters is presented according to the simulation and optimization of the virtual twin with the dynamic perception of the machining conditions of the physical machine. At last, a case study is presented to validate this method for effectively optimizing the cutting parameters and decreasing carbon emissions.