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Operations Research, Systems Engineering and Industrial Engineering

China Simulation Federation

Parameter identification

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Articles 1 - 14 of 14

Full-Text Articles in Engineering

Prediction Of Energy Efficiency Of Nc Machine Tools Based On Recursive Method With Discounted Measurements, Cai Lei, Wang Yan, Zhicheng Ji Aug 2020

Prediction Of Energy Efficiency Of Nc Machine Tools Based On Recursive Method With Discounted Measurements, Cai Lei, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the problem that the energy efficiency of numerical control machine tool is difficult to obtain directly, a new method combined with the recursive method with discounted measurements was presented to predict the energy efficiency of machine tool. The estimation model of the cutting power was given in view of the power balance equation of the machine tool main drive system and the additional load loss function, further taking into account the additional load loss coefficients in model could not be directly measured, the recursive method with discounted measurements was adopted to identify the additional load loss coefficients …


Grey Wolf Optimizer For Parameters Identification Of Induction Motor With Improved Model, Xiaoyi Lü, Huang Song, Wang Yan, Zhicheng Ji Aug 2020

Grey Wolf Optimizer For Parameters Identification Of Induction Motor With Improved Model, Xiaoyi Lü, Huang Song, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: According to the problems of inaccurate parameters estimation of the induction motor in high-performance control, a grey wolf optimizer was used to identify the parameters of the induction motor. Grey wolf optimizer is a new meta-heuristic. It is simple and flexible to implement, and has fewer parameters to tune. Considering that two typical dynamic mathematical models have different identification precision on different parameters, the improved identification model of the induction motor was proposed. Compared with typical model, simulation results show that the proposed model obviously improves the identification performance of resistances especially stator resistance, verifying the validity …


Novel Method To Identify Pmsm Parameters Based On Multiple Linear Regressive Models, Zhenwei Shi, Zhicheng Ji Aug 2020

Novel Method To Identify Pmsm Parameters Based On Multiple Linear Regressive Models, Zhenwei Shi, Zhicheng Ji

Journal of System Simulation

Abstract: A New Coupled Recursive Least Squares (C-FF-RLS) Algorithm with a forgetting factor was proposed for the Parameters Identification of Permanent Magnet Synchronous Motors (PMSMs). The deduced multiple linear regressive models of PMSM were proposed that were simple and appropriate for parameter identification. The C-FF-RLS identification algorithm had a high computational efficiency and a fast convergence speed because which Avoided the Matrix Inversion Operation in the Gain Matrix Compared with the Traditional Multivariable Recursive Least Squares (M-FF-RLS) Algorithm with a Forgetting Factor. The Proposed Identification Algorithm was applied on a simulation system of PMSM. The identification results achieved by …


Hybrid Quantum-Behaved Particle Swarm Optimization For Parameter Identification Of Dfig, Yingying Jiang, Zhicheng Ji Jul 2020

Hybrid Quantum-Behaved Particle Swarm Optimization For Parameter Identification Of Dfig, Yingying Jiang, Zhicheng Ji

Journal of System Simulation

Abstract: In order to ensure the accuracy of the doubly-fed wind power generator (DFIG) and improve the control performance of the generator, a hybrid quantum-behaved particle swarm optimization for parameter identification was proposed. A parameter identification model of DFIG at coordinate was established. Quantum-behaved particle swarm optimization (QPSO) was improved and then mixed with simulated annealing (SA) algorithm. The proposed algorithm was compared with particle swarm optimization (PSO), QPSO and improved QPSO, which were applied to parameter identification of DFIG in Matlab/Simulink. Simulation results show that the proposed algorithm can improve the identification accuracy of …


Integrated Dynamic Equivalent Model Of Super Capacitor Energy Storage System, Xinran Li, Tingting Xu, Shaojie Tan, Xingting Cheng, Xiaojun Zeng Jul 2020

Integrated Dynamic Equivalent Model Of Super Capacitor Energy Storage System, Xinran Li, Tingting Xu, Shaojie Tan, Xingting Cheng, Xiaojun Zeng

Journal of System Simulation

Abstract: As a high-power energy storage device, super capacitor (SC) is applied in micro-grid energy storage, secondary frequency regulation and peak load shifting in power system, and the research of which has become a hotspot. A second-order model of SC monomer suitable for the grid simulation was established, and the parameter identification using the charge and discharge experiment data under constant current and constant power modes was conducted based on genetic algorithm. A SC energy storage system has been set up in Simulink/Matlab based on the established second-order model of SC. The integrated dynamic equivalent model of SC energy storage …


Coral Reefs Optimization For Solving Parameter Identification In Permanent Magnet Synchronous Motor, Yawei Quan, Tian Na, Zhicheng Ji, Wang Yan Jul 2020

Coral Reefs Optimization For Solving Parameter Identification In Permanent Magnet Synchronous Motor, Yawei Quan, Tian Na, Zhicheng Ji, Wang Yan

Journal of System Simulation

Abstract: High accuracy identification of parameters in permanent magnet synchronous motor (PMSM) is the basis of controller design. According to the drawbacks of slow speed, big error, and small number of parameters in classical particle swarm optimization (PSO) and least square method, Coral Reefs Optimization (CRO) was proposed to solve the parameter identification problem in PMSM. In order to improve the identification accuracy, the parameter setting in CRO was adjusted. The mathematical model of PMSM in coordinate system was established, CRO, PSO and RLS were applied to identify parameters in PMSM, and were verified in Matlab/Simulink for comparison. The simulation …


Parameter Identification Method Based On Lagrangemultiplier And Measuring Residual Error, He Zhi, Zhicheng Nie, Yining Qin, Youping Fan Jun 2020

Parameter Identification Method Based On Lagrangemultiplier And Measuring Residual Error, He Zhi, Zhicheng Nie, Yining Qin, Youping Fan

Journal of System Simulation

Abstract: To satisfy the security and stability control, transient and steady state analysis of power system, it is necessary to ensure the accuracy of the estimated parameters. A method of parameter identification in power system based on Lagrange multiplier and measurement method of residualis proposed through analysis of measurement residuals. A two-step approach for parameter identification is introduced. Based on Lagrange multiplier method, using thestandardized Lagrange multiplier corresponding to the parameter error the parameters with errors can be judged by the size relative to the threshold and can bedetected and identified automatically. The residual vector of measurement redundancy is …


Study Of Im Parameter Identification Using Multi-Objective Particle Swarm Optimization With Proportional Guided Strategy, Huang Song, Tian Na, Wang Yan, Zhicheng Ji Jun 2020

Study Of Im Parameter Identification Using Multi-Objective Particle Swarm Optimization With Proportional Guided Strategy, Huang Song, Tian Na, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: A multi-parameter and multi-objective identification model of induction motor was established, and a multi-objective particle swarm optimization based on Pareto set and all personal-best positions guided strategy was proposed and applied to the identification model. Not considerring the weighted coefficient of each objective, Pareto set is able to avoid subjective choice of the coefficients of multi-objective identification and proportion strategy with all personal-best positions guided could balance the learning ability from personal-best positions and global-best position. Having verified the performance on Matlab/Simulink, the results show that the proposed algorithm is able to improve parameter identification accuracy, and has …


Permanent Magnet Synchronous Motor Parameter Identification Based On Improved Teaching-Learning-Based Optimization, Li Jie, Wang Yan, Zhicheng Ji Jun 2020

Permanent Magnet Synchronous Motor Parameter Identification Based On Improved Teaching-Learning-Based Optimization, Li Jie, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: High accuracy identification of parameters in permanent magnet synchronous motor (PMSM) is the basis of controller design. In order to overcome the shortages of traditional identification methods such as slow speed and low identification accuracy, an improved teaching-learning-based optimization algorithm (ITLBO) was proposed to identify the permanent magnet synchronous motor parameters. In the teaching phrase, tutorial teaching mechanism was introduced to strengthen teacher's capacity and improved the convergence rate of algorithm, in the learning phrase, the course stepwise learning was used to improve learners' learning efficiency. Besides, opposition-based-learning was introduced for small probability mutation, which enhanced the possibility out …


Direct Parameter Identification Method For Steam Turbine And Its Governing System, Jingliang Zhong, Xiaolong Gou, Tongtian Deng Jan 2019

Direct Parameter Identification Method For Steam Turbine And Its Governing System, Jingliang Zhong, Xiaolong Gou, Tongtian Deng

Journal of System Simulation

Abstract: Since most of the traditional parameter identification methods used in the steam turbine and its governing system have the shortages of poor fitness, complicated identification process and long period, a novel identification method based on least square theory, called direct identification method, is proposed in this paper. Parameter to be identified can be obtained quickly and accurately through direct identification method if the identification process is transferred to solve nonlinear equation which represents the minimal error between simulated data and measured data. The identification results show that during identification process the proposed method has high identification efficiency, accurate identification …


Permanent Magnet Synchronous Motor Fuzzy Forgetting Factor Recursive Least Squares Parameter Identification, Yanxia Shen, Baolong Jin Jan 2019

Permanent Magnet Synchronous Motor Fuzzy Forgetting Factor Recursive Least Squares Parameter Identification, Yanxia Shen, Baolong Jin

Journal of System Simulation

Abstract: In order to improve the stability and convergence rate of permanent magnet synchronous motor (PMSM) on-line identification, this paper proposes a fuzzy forgetting factor least squares algorithm based on the least squares algorithm with forgetting factor. The linear regression model of permanent magnet synchronous motor is established by using the linearization technique of Pade approximation method. A fuzzy controller is designed by using the current error and the forgetting factor can be adjusted adaptively. The proposed method is applied to the field of on-line identification of permanent magnet synchronous motor stator resistance, which solves the contradiction between the result …


Parameter Identification Of Permanent Magnet Synchronous Motor Based On Mutation Coral Reef Algorithm, Dinghui Wu, Huang Xu, Yawei Quan, Zhicheng Ji Jan 2019

Parameter Identification Of Permanent Magnet Synchronous Motor Based On Mutation Coral Reef Algorithm, Dinghui Wu, Huang Xu, Yawei Quan, Zhicheng Ji

Journal of System Simulation

Abstract: High accuracy identification of parameters in Permanent magnet synchronous motor (PMSM) is the basis of controller design. According to the drawbacks of slow speed, big error, and small number of parameters in particle swarm optimization (PSO), least square method, and classical coral reefs optimization (CRO), an improved CRO with Cauchy and Gaussian mutation is proposed to solve the parameter identification problem in PMSM. The mathematical model of PMSM in dq coordinate system is established. The Cauchy and Gaussian mutation operator is introduced to CRO. Both of the two versions are applied for identifying parameters in PMSM, and are …


Pmsm Parameter Identification Using Teaching-Learning-Based Optimization With Levy Flight, Jinbao Chen, Li Jie, Wang Yan, Zhicheng Ji Jan 2019

Pmsm Parameter Identification Using Teaching-Learning-Based Optimization With Levy Flight, Jinbao Chen, Li Jie, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: High precision parameters are the key for permanent magnet synchronous motor to realize high performance control. To overcome the shortages of slow speed and low identification accuracy in traditional identification methods, a novel teaching-learning-based optimization algorithm with Levy flight is proposed to identify the PMSM parameters. The algorithm introduces adaptive teaching factor and self-learning strategy to improve the convergence speed. As for learning phase, a Levy flight stochastic process is introduced to improve the optimization strategy so that the algorithm can enhance the ability to keep the balance between exploration and exploitation. The simulation results show that the novel …


Parameter Identification For Pmsm Based On Multi-Innovation Approximate Least Absolute Deviation Identification Algorithm, Dinghui Wu, Jianyu Zhang, Yanxia Shen, Zhicheng Ji Jan 2019

Parameter Identification For Pmsm Based On Multi-Innovation Approximate Least Absolute Deviation Identification Algorithm, Dinghui Wu, Jianyu Zhang, Yanxia Shen, Zhicheng Ji

Journal of System Simulation

Abstract: In view of the problem that the results of traditional identification algorithm are not accurate caused by the peak noise signal in the environment, a new algorithm based on the forgetting factor multi-innovation approximate least absolute deviation (MIALAD) identification algorithm is proposed. Combined with the system voltage equation of permanent magnet synchronous motor (PMSM), a discrete identification model is constructed. By using vector control method, the input and output data of the identification model are obtained to identify the rotor resistance and inductance. The simulation results show that this identification algorithm can obtain the accurate parameters of the PMSM …