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Adaptive thermal error prediction for CNC machine tool spindle using online measurement and an improved recursive least square algorithm

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CASE STUDIES IN THERMAL ENGINEERING 2024年 56卷

作者： Wei, Xinyuan Ye, Honghan Wang, Gao Hu, Weidong Anhui Univ Technol Sch Elect & Informat Engn Maanshan 230009 Peoples R China Univ Wisconsin Coll Letters & Sci Sch Comp Data & Informat Dept Stat Madison WI 53705 USA Anhui Prov Key Lab Special Heavy Load Robot Maanshan 243032 Peoples R China

Establishing models for predicting and compensating for spindle thermal errors is cost-effective and necessary to improve the accuracy of machine tools for smart manufacturing. However, the prediction performance of existing methods deteriorates significantly with dynamic working conditions of machine tools because training from static conditions leads to the inability to adapt to dynamic conditions. Therefore, an adaptive thermal error modeling method using online measurement and an improved recursive least square algorithm is proposed to fill this research gap, which updates the thermal error model adaptively to ensure that dynamic working conditions are learned in real time. Particularly, Spearman's rank correlation coefficient method is first adopted for temperature -sensitive point selection to capture the nonlinear relationship between temperature and thermal error variables. Furthermore, a variable -forgetting factor -based recursive least square (VFF-RLS) algorithm is proposed to improve the prediction performance, in which the proposed variable forgetting factor is adaptively updated according to real-time thermal error data collected by online measurement. The experimental results showed that the proposed VFFRLS method can maintain a high prediction accuracy of 1.75 mu m and robustness of 0.16 mu m on both constant and dynamic working conditions. The effectiveness of the VFF-RLS method is validated by verification experiments.

关键词： CNC machine tools Thermal error modeling Adaptability recursive least square algorithm Variable forgetting factor

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Computation of the largest positive Lyapunov exponent using rounding mode and recursive least square algorithm

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CHAOS SOLITONS & FRACTALS 2018年 112卷 36-43页

作者： Peixoto, Marcia L. C. Nepomuceno, Erivelton G. Martins, Samir A. M. Lacerda, Marcio J. Univ Fed Sao Joao del Rei Dept Elect Engn Control & Modelling Grp GCOM Praca Frei Orlando 170 BR-36307352 Joao Del Rei MG Brazil

It has been shown that natural interval extensions (NIE) can be used to calculate the largest positive Lyapunov exponent (LLE). However, the elaboration of NIE are not always possible for some dynamical systems, such as those modelled by simple equations or by Simulink-type blocks. In this paper, we use rounding mode of floating-point numbers to compute the LLE. We have exhibited how to produce two pseudo-orbits by means of different rounding modes;these pseudo-orbits are used to calculate the Lower Bound Error (LBE). The LLE is the slope of the line gotten from the logarithm of the LBE, which is estimated by means of a recursive least square algorithm (RLS). The main contribution of this paper is to develop a procedure to compute the LLE based on the LBE without using the NIE. Additionally, with the aid of RLS the number of required points has been decreased. Eight numerical examples are given to show the effectiveness of the proposed technique. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Dynamical systems Lyapunov exponent Rounding mode Lower bound error Chaos recursive least square algorithm

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TRAJECTORY TRACKING CONTROL OF EMERGENCY SUPPLIES TRANSPORT ROBOTS BASED ON FUZZY MPC

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2023年第10期19卷 7616-7639页

作者： Tang, M. I. N. A. N. Zhang, Y. A. Q., I Yan, Y. A. G. U. A. N. G. Wang, W. E. N. J. U. A. N. An, Bo Elect Engn Lanzhou Jiaotong Univ Sch Automation Lanzhou 730070 Peoples R China Power Engn Lanzhou Jiaotong Univ Sch New Energy Lanzhou 730070 Peoples R China

"Contactless" distribution plays an important role in emergency supplies transportation, and the trajectory tracking control of emergency supplies transport robots is the key technology to achieving "contactless" distribution precision. In this paper, a trajectory tracking control method for emergency supplies transport robots was proposed based on fuzzy MPC. Firstly, a kinematic model of the emergency supplies transport robots was established, and the motion parameters were identified by the recursive least square algorithm. Secondly, aiming at the velocity problem of trajectory tracking of emergency supplies transport robots, a fuzzy control method was proposed to optimize the velocity error dynamically. Thirdly, the model predictive control theory was introduced, and an expanded state observer was designed for the total disturbances to optimize the control of the tracking trajectory of the emergency supplies transport robots. Finally, a simulation model was built in Simulink, and the performance of the trajectory tracking controller was verified by co-simulation using CarSim/ Simulink. The simulation results show that, compared with the classical MPC trajectory tracking controller, the optimized velocity error MPC trajectory tracking controller improves the operational stability of the robots and the trajectory tracking accuracy by 13.18%.

关键词： Emergency supplies transport robots model predictive control fuzzy control recursive least square algorithm extended state observer

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Extracting Fetal ECG Signals Through a Hybrid Technique Utilizing Two Wavelet-Based Denoising algorithms

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IEEE ACCESS 2023年 11卷 91696-91708页

作者： Darsana, P. Kumar, Vaegae Naveen Vellore Inst Technol Sch Elect Engn Vellore 632014 Tamil Nadu India

Developing an intelligent technique for fetal heartbeat detection to monitor the cardiac function of the fetus in the initial stages of pregnancy is crucial. In this research work, two hybrid algorithms are proposed that use a combination of recursive least square algorithm (RLS) and stationary wavelet transform (SWT) for fetal ECG extraction. The goal of this research is to enhance the fetal ECG signal, reduce noise and artifact, and accurately detect the R-peaks by employing improved spatially selective noise filtration (ISSNF) method or threshold-based denoising approach in the wavelet domain. Accurate fetal R-peak detection can provide important clinical information and aid in the diagnosis and treatment of fetal heart conditions. The primary aim is to extract a clear fetal ECG signal from the mixed abdominal signal. The abdominal signal is divided into multiscale components using SWT, with different levels of noise determining the scale of wavelet decomposition. The RLS algorithm is then utilized for removing maternal ECG components, and either ISSNF or threshold-based algorithms are employed for denoising in the wavelet domain. We evaluate the effectiveness of our proposed method using both synthetic and clinical data. Our analysis involves qualitative and quantitative measures, including visual inspection, signal-to-noise ratio (SNR) computation, and QRS complex recognition. Our findings reveal that the proposed system exhibits superior performance when compared to conventional adaptive filtering techniques. The experimental results suggest that the proposed system has the potential to extract fetal ECG signals that are clear, with good SNR results and minimal disturbances.

关键词： ECG extraction fetal ECG improved spatially selective noise filtration recursive least square algorithm stationary wavelet transforms threshold-based algorithm

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Identification of linear time-varying fractional order systems using block pulse functions based on repetitive principle

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ISA TRANSACTIONS 2022年 123卷 218-229页

作者： Zhang, Bo Tang, Yinggan Lu, Yao Yanshan Univ Inst Elect Engn Qinhuangdao 066004 Hebei Peoples R China Yanshan Univ LiRen Coll Qinhuangdao 066004 Hebei Peoples R China

A novel method for identifying linear time-varying fractional order systems based on a repetitive principle is proposed in this study. According to the repetitive principle, the system operates repetitively for several times, so the time-varying parameters are invariant on the fixed time for different operations. In the identification process, the time-varying parameters, independent from the input/output signals, are expanded onto some block pulse functions. The system is then converted to an algebraic system via the fractional differential operational matrix of the block pulse functions. Finally, recursive least square and instrumental variable recursive least square algorithms along the iteration axis are designed to identify the time-varying parameters without and with noise. Simulation results demonstrate that our proposed method is powerful in tracking time-varying parameters. (C) 2021 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Identification Fractional order system Repetitive principle Time-varying parameter recursive least square algorithm

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Dynamic Forgetting Factor Based Bias-Compensated RLS Model Free Predictive Current Control for Voltage Source Inverter 17

Dynamic Forgetting Factor Based Bias-Compensated RLS Model F...

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17th Conference on Industrial Electronics and Applications (ICIEA)

作者： Li, Zhipeng Wang, Benfei Wang, Ping Han, Yu Garcia, Cristian Rodriguez, Jose Sun Yat Sen Univ Sch Intelligent Syst Engn Shenzhen Campus Shenzhen 518107 Peoples R China Guangdong Prov Key Lab Fire Sci & Intelligent Eme Guangzhou 510006 Peoples R China Univ Talca Dept Elect Engn Curico 3340000 Chile Univ San Sebastian Santiago Fac Engn Santiago 8420524 Chile

ISBN: (纸本)9781665409841

Recently, recursive least square (RLS) based model free predictive control (MF-PC) has been widely applied to model estimation for superior performance to model-based method. In most previous researches the forgetting factor which is a tradeoff between the convergence speed and the steady-state tracking error is usually neglected, thus selected as a constant to ensure robustness. In this paper, a dynamic forgetting factor based bias compensated RLS (DFF-BCRLS) is proposed for model free predictive current control of a voltage source inverter. The dynamic forgetting factor is calculated by local optimal forgetting factor (LOFF) algorithm to improve data convergency and steady-state robustness. A bias compensation (BC) scheme is presented to further increase the accuracy of parameter estimation and immune input noise. The simulation results show that the proposed strategy has smaller tracking error in steady-state and better performance against model or parameter mismatches compared to the conventional RLS.

关键词： Dynamic forgetting factor bias compensation voltage source inverter recursive least square algorithm

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Technique to Adjust Adaptive Digital Filter Coefficients in Residue Number System Based Filters

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IEEE ACCESS 2021年 9卷 82402-82416页

作者： Kaplun, Dmitrii Voznesensky, Alexander Veligosha, Alexander V. Kalmykov, Igor A. Sarma, Kandarpa Kumar St Petersburg Electrotech Univ LETI Dept Automat & Control Proc St Petersburg 197376 Russia Mil Acad Strateg Missile Forces Dept 52 Serpukhov 142210 Russia North Caucasus Fed Univ Dept Informat Secur Automated Syst Stavropol 355009 Russia Gauhati Univ Dept Elect & Commun Engn Gauhati 781014 India

The paper discusses adaptive filtering using least Mean square (LMS) and recursive least square (RLS) algorithms. An algorithm for adjusting the coefficients of an adaptive digital filter in the Residue Number System and a procedure of developed algorithm applying depending on filter length and signal length are proposed. Mathematical modeling of the considered algorithms is performed. Examples are presented to demonstrate how the proposed technique can help the designer in the adjustment of the filter coefficients without the need for extensive trial-and-error procedures. The analysis of the denoising quality and computational complexity is made. Synthetic and real data (earthquake recording) were used while testing. The proposed algorithm surpasses the existing ones like LMS and RLS, and their modifications in a number of parameters: adaptation (denoising) quality, ease of implementation, execution time. The main difference between the developed algorithm is the sequential adaptation of each coefficient with zero error. In the known algorithms, the entire vector of coefficients is iteratively adapted, with some specified accuracy. The iterations (steps) number is determined by the input signal length for all algorithms.

关键词： Digital filters Signal processing algorithms Filtering algorithms Wiener filters Finite impulse response filters Electronic mail Approximation algorithms Adaptive digital filter residue number system least mean square algorithm recursive least square algorithm denoising quality computational complexity

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Online Inductance Identification of Permanent Magnet Synchronous Motors Independent of Rotor Position Information

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WORLD ELECTRIC VEHICLE JOURNAL 2024年第1期15卷 35页

作者： Xing, Jilei Zhang, Junzhi Zhuang, Xingming Xu, Yao Tsinghua Univ Sch Vehicle & Mobil Beijing 100084 Peoples R China BIT HuaChuang Elect Vehicle Technol Co Ltd Beijing 100081 Peoples R China Beijing Inst Technol Sch Mech Engn Beijing 100081 Peoples R China

Sensorless control of permanent magnet synchronous motors is preferable in some applications due to cost and mounting space concerns. The performance of most existing position estimation methods greatly depends on the accuracy of the motor inductance. As the estimated position should not be involved in the parameter identification process in a sensorless control system, an online inductance identification method independent of the rotor position information is developed in this paper. The proposed method utilizes the recursive least square algorithm and the particle swarm optimization algorithm to realize real-time identification of the inductance along the direct axis and the quadrature axis, respectively, based on the deduced parametric equations without position information. The proposed method is efficient enough to be implemented within 0.2 ms and does not introduce any additional signal injection. A test bench is built to validate the characteristics of the method, and the experimental results show that the identified inductance can converge to the actual value rapidly and is robust to changes in the initial values and stator current. With the proposed method, accurate estimation of the rotor position and speed can be obtained using traditional model-based position estimators, and the stability of the sensorless control system can be improved significantly.

关键词： permanent magnet synchronous motors online inductance identification sensorless control recursive least square algorithm particle swarm optimization

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An on-line capacitor state identification method based on improved RLS

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Transportation Safety and Environment 2021年第3期3卷 231-243页

作者： Shu Cheng Chang Liu Shengxian Xue Maoyu Wang Xun Wu Yu Luo School of Traffic and Transportation Engineering Central South UniversityChangsha 410075China CRRC Changchun Rail Car Co. LtdChangchun 130062China Shenyang Bullet Train Section of China Railway Shenyang Bureau Group Co.Ltd Shenyang 110021China

As an essential part of DC-Link in the power converter,capacitor plays a crucial role in absorbing ripple current and suppressing ripple *** health and residual service life of the DC-Link capacitor is one of the decisive factors for the safety,stability,and efficiency of the system in which it is *** at the shortcomings of existing methods,such as low dynamic sensitivity of data update and fluctuation of identification results,a capacitor state identification method based on improved RLS is proposed in this *** proposed method is optimized by introducing the forgetting factor algorithm and root means square algorithm to modify the iterative formula and final identification *** with existing methods,this method can identify the capacitor’s current state in real time and ***,we successfully verified the accuracy,robustness,and adaptability of the proposed method by a series of experimental tests on a dSPACE platform.

关键词： DC-Link capacitor state identification recursive least square algorithm

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Integration of optimized feedrate into an online adaptive force controller for robot milling

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2020年第3-4期106卷 1533-1542页

作者： Xiong, Gang Li, Zhou-Long Ding, Ye Zhu, LiMin Shanghai Jiao Tong Univ Sch Mech Engn State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China

Maximum resultant cutting force control provides a great benefit of improving productivity in machining tasks. This paper presents a new force control method for robot milling that can prevent force overshoots during abrupt part geometry changes. Firstly, the feedrates of the robot at critical cutter locations are optimized offline according to the cutting force model and the part geometry. Secondly, an online parameter self-adaptive proportional-integral (PI) controller is designed in consideration of the robot feed-direction dynamics and the time-varying first-order model of the cutting process. Finally, the offline scheduled feedrates are integrated into the online adaptive controller via a feedforward-like strategy. Experiments demonstrate the effectiveness and advantages of the proposed force control method.

关键词： Robot machining Force control Feedrate scheduling Parameter self-adaptive PI controller recursive least square algorithm

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