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Search Results (19)
  • Open Access

    ARTICLE

    Improved Particle Swarm Optimization for Parameter Identification of Permanent Magnet Synchronous Motor

    Shuai Zhou1, Dazhi Wang1,*, Yongliang Ni2, Keling Song2, Yanming Li2

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2187-2207, 2024, DOI:10.32604/cmc.2024.048859 - 15 May 2024

    Abstract In the process of identifying parameters for a permanent magnet synchronous motor, the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration, resulting in low parameter accuracy. This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function. This approach addresses the topic of particle swarm optimization in parameter identification from two perspectives. Firstly, the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness… More >

  • Open Access

    ARTICLE

    Parameters Identification for Extended Debye Model of XLPE Cables Based on Sparsity-Promoting Dynamic Mode Decomposition Method

    Weijun Wang1,*, Min Chen1, Hui Yin1, Yuan Li2

    Energy Engineering, Vol.120, No.10, pp. 2433-2448, 2023, DOI:10.32604/ee.2023.028620 - 28 September 2023

    Abstract To identify the parameters of the extended Debye model of XLPE cables, and therefore evaluate the insulation performance of the samples, the sparsity-promoting dynamic mode decomposition (SPDMD) method was introduced, as well the basics and processes of its application were explained. The amplitude vector based on polarization current was first calculated. Based on the non-zero elements of the vector, the number of branches and parameters including the coefficients and time constants of each branch of the extended Debye model were derived. Further research on parameter identification of XLPE cables at different aging stages based on… More >

  • Open Access

    ARTICLE

    STPGTN–A Multi-Branch Parameters Identification Method Considering Spatial Constraints and Transient Measurement Data

    Shuai Zhang, Liguo Weng*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2635-2654, 2023, DOI:10.32604/cmes.2023.025405 - 09 March 2023

    Abstract Transmission line (TL) Parameter Identification (PI) method plays an essential role in the transmission system. The existing PI methods usually have two limitations: (1) These methods only model for single TL, and can not consider the topology connection of multiple branches for simultaneous identification. (2) Transient bad data is ignored by methods, and the random selection of terminal section data may cause the distortion of PI and have serious consequences. Therefore, a multi-task PI model considering multiple TLs’ spatial constraints and massive electrical section data is proposed in this paper. The Graph Attention Network module More > Graphic Abstract

    STPGTN–A Multi-Branch Parameters Identification Method Considering Spatial Constraints and Transient Measurement Data

  • Open Access

    ARTICLE

    Double Update Intelligent Strategy for Permanent Magnet Synchronous Motor Parameter Identification

    Shuai Zhou1, Dazhi Wang1,*, Mingtian Du2, Ye Li1, Shuo Cao3

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3391-3404, 2023, DOI:10.32604/cmc.2023.033397 - 31 October 2022

    Abstract The parameters of permanent magnet synchronous motor (PMSM) affect the performance of vector control servo system. Because of the complexity of nonlinear model of PMSM, it is very difficult to identify the parameters of PMSM. Aiming at the problems of large amount of data calculation, low identification accuracy and poor robustness in the process of multi parameter identification of permanent magnet synchronous motor, this paper proposes a weighted differential evolutionary particle swarm optimization algorithm based on double update strategy. By introducing adaptive judgment factor to control the proportion of weighted difference evolution (WDE) algorithm and… More >

  • Open Access

    ARTICLE

    Robot Zero-Moment Control Algorithm Based on Parameter Identification of Low-Speed Dynamic Balance

    Saixuan Chen1, Jie Yang1,*, Guohua Cui1, Fuzhou Niu2, Baiqiang Yao1, Yu Zhang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 2021-2039, 2023, DOI:10.32604/cmes.2022.022669 - 20 September 2022

    Abstract This paper proposes a zero-moment control torque compensation technique. After compensating the gravity and friction of the robot, it must overcome a small inertial force to move in compliance with the external force. The principle of torque balance was used to realise the zero-moment dragging and teaching function of the lightweight collaborative robot. The robot parameter identification based on the least square method was used to accurately identify the robot torque sensitivity and friction parameters. When the robot joint rotates at a low speed, it can approximately satisfy the torque balance equation. The experiment uses More >

  • Open Access

    ARTICLE

    Pattern-Moving-Based Parameter Identification of Output Error Models with Multi-Threshold Quantized Observations

    Xiangquan Li1,2, Zhengguang Xu1,*, Cheng Han1, Ning Li1

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1807-1825, 2022, DOI:10.32604/cmes.2022.017799 - 30 December 2021

    Abstract This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm (M-AM-SGRPIA) for a class of single input single output (SISO) linear output error models with multi-threshold quantized observations. It proves the convergence of the designed algorithm. A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output (SIMO) or SISO nonlinear systems, and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system. The system input design is accomplished using the measurement technology of random repeatability More >

  • Open Access

    ARTICLE

    Parameters Identification of Tunnel Jointed Surrounding Rock Based on Gaussian Process Regression Optimized by Difference Evolution Algorithm

    Annan Jiang*, Xinping Guo, Shuai Zheng, Mengfei Xu

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 1177-1199, 2021, DOI:10.32604/cmes.2021.014199 - 24 May 2021

    Abstract Due to the geological body uncertainty, the identification of the surrounding rock parameters in the tunnel construction process is of great significance to the calculation of tunnel stability. The ubiquitous-joint model and three-dimensional numerical simulation have advantages in the parameter identification of surrounding rock with weak planes, but conventional methods have certain problems, such as a large number of parameters and large time consumption. To solve the problems, this study combines the orthogonal design, Gaussian process (GP) regression, and difference evolution (DE) optimization, and it constructs the parameters identification method of the jointed surrounding rock.… More >

  • Open Access

    ARTICLE

    Kinematic Calibration of a Parallel Manipulator for a Semi-physical Simulation System

    Dayong Yu

    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 571-580, 2018, DOI:10.31209/2018.100000024

    Abstract In the application of a semi-physical simulation system of a space docking mechanism, the simulation precision is determined by pose accuracy of the parallel manipulator. In order to improve pose accuracy, an effective kinematic calibration method is presented to enable the full set of kinematic parameter errors to be estimated by measuring the docking mechanism’s poses. A new calibration model that takes into account geometrical parameter errors and coordinates transformation errors is derived by using a differential geometry method. Based on the calibration model, an iterative least square algorithm is utilized to calculate the above More >

  • Open Access

    ARTICLE

    A Piecewise Linear Isotropic-Kinematic Hardening Model with Semi-Implicit Rules for Cyclic Loading and Its Parameter Identification

    M. Ohsaki1, T. Miyamura2, J. Y. Zhang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.111, No.4, pp. 303-333, 2016, DOI:10.3970/cmes.2016.111.303

    Abstract A simple constitutive model, called semi-implicit model, for cyclic loading is proposed for steel materials used for structures such as building frames in civil engineering. The constitutive model is implemented in the E-Simulator, which is a software package for large-scale seismic response analysis. The constitutive relation is defined in an algorithmic manner based on the piecewise linear combined isotropic-kinematic hardening. Different rules are used for the first and subsequent loading states to incorporate characteristics such as yield plateau and Bauschinger effect of rolled mild steel materials. An optimization method is also presented for parameter identification More >

  • Open Access

    ABSTRACT

    Parameter identification method of large macro-micro coupled constitutive models based on identifiability analysis

    Jie Qu, Bingye Xu, Quanlin Jin

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.16, No.1, pp. 21-22, 2011, DOI:10.3970/icces.2011.016.021

    Abstract Large macro-micro coupled constitutive models, which describe metal flow and microstructure evolution during metal forming, are sometimes overparameterized with respect to given sets of experimental datum. This results in poorly identifiable or nonidentifiable model parameters. In this paper, a systemic parameter identification method for the large macro-micro coupled constitutive models is proposed. This method is based on the global and local identifiability analysis, in which two identifiability measures are adopted. The first accounts for the sensitivity of model results to single parameters, and the second accounts for the degree of near-linear dependence of sensitivity functions… More >

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