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2023 IEEE International Conference on Electrical, Automation and Computer Engineering, ICEACE 2023

作者： Song, Gaoling Wang, Xuezhi Xiao, Quanjian Zhao, Wangyang Wang, Yuanming Tianjin Navigation Instrument Research Institute Tianjin300131 China

ISBN: (纸本)9798350309614

Aiming at the problem of micro-inertial sensor alignment under high overload conditions, a new alignment method based on guidance information + spin signal decomposition is proposed in this paper. By deducing the four-element attitude theory, the attitude recursive calculation method is established to solve the problem of missile heading and initial pitch angle. In this paper, based on the phase identification and error compensation technology of double acceleration velocity measurement signal, recursive least squares algorithm, symmetrical double acceleration velocity meter configuration scheme and micro-inertial gyroscope speed signal are used to realize the rolling attitude acquisition technology based on periodic signal, and to achieve high dynamic fast alignment of guided projectile in the air. The accuracy level of horizontal alignment error less than 0.2°and heading error less than 0.5°is analyzed by simulation under the condition of high-speed rotation of the projectile body. © 2023 IEEE.

关键词： alignment micro-inertial system recursive least squares algorithm

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An algorithm for precisely estimating loop-delay in digital predistortion system

An algorithm for precisely estimating loop-delay in digital ...

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2010 International Conference on Communications, Circuits and Systems, ICCCAS 2010

作者： Kong, Xiaowei He, Zishu Xia, Wei School of Electronic Engineering University of Electronic Science and Technology of China Chengdu Sichuan China

ISBN: (纸本)9781424482238

In digital predistortion (DPD) design, loop-delay estimation for synchronization is an important work. In this paper, an algorithm for precisely estimating loop-delay in DPD system is proposed. The whole algorithm consists of integer loop-delay estimation and fractional loop-delay estimation. Amplitude-difference correlation function is used to estimate the integer loop-delay estimation. The fractional loop-delay estimation gets the estimate through recursive least squares (RLS) algorithm based on interpolation filter structure. Finally, a series of simulations prove the validity of the algorithm and the effect on the DPD system. © 2010 IEEE.

关键词： amplitude-difference correlation function delay estimation delay lock loops digital predistortion system filters integer loop-delay estimation interpolation filter structure least squares approximations loop-delay recursive least squares algorithm synchronisation

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A systolic array structure for on line system identification

A systolic array structure for on line system identification

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作者： Mumtaz Tunc NAVAL POSTGRADUATE SCHOOL

学位级别：硕士

In this study, we present an algorithm for system identification for systolic array implementation. With this schema, discrete samples of input and output data of a sys- tem with uncertain characteristics are used to determine the parameters of its model. The identification algorithm is based on recursive least squares, QR decomposition, and block processing techniques with covariance resetting. The identification process is based on the use of Givens rotation. Additionally, we want to address the following problems: how the round-off error propagates in time and the implementation in closed loop adaptive control. We will compare the implementation of fixed point arithmetic with the implementation of floating point arithmetic. This is primarily a theoretical in- vestigation to be conducted with computer simulations where numerical results will be investigated.

关键词： Systolic Arrays recursive least squares algorithm Givens Rotation

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A PID-like controller for nonlinear systems

A PID-like controller for nonlinear systems

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1997 American Control Conference

作者： Wang, J Gao, WZ Wang, FL Northeastern Univ SHENYANG 110006 PEOPLES R CHINA

ISBN: (纸本)0780338324;0780338332

This paper presents an adaptive PID-like controller(PIDLC) using a modified Neural network(MNN) for learning the characteristics of a dynamic system. The PIDLC can adapt parameters' variation and uncertainty in the controlled plant through on-line learning. The MNN's learning algorithm is considerably faster because of the introduction of recursive least squares(RLS) algorithm. The simulation results show that this kind of control algorithm is very effective especially when there are variations in the plant dynamics.

关键词： nonlinear systems adaptive control three-term control neurocontrollers learning (artificial intelligence) recurrent neural nets least squares approximations nonlinear systems PID-like controller adaptive control recurrent neural network learning algorithm recursive least squares algorithm system dynamics

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Identification of the Model of Acoustic Feedback Path in Active Noise Control

Identification of the Model of Acoustic Feedback Path in Act...

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Chinese Automation Congress (CAC)

作者： Huang Shuang Chen Yuanbao Xie Chengxi Zhang Huajun Zhao Yibo Wuhan Second Ship Design & Res Inst Intelligence Design Ctr Wuhan Hubei Peoples R China Wuhan Univ Technol Sch Automat Wuhan Hubei Peoples R China

ISBN: (纸本)9781728113128

Active noise control is used to deal with noise pollution in many fields, and it reduces the noise intensity by generating an antisound which has the same amplitude and opposite phase to the original noise. However, the antisound is a secondary sound source compared to the original noise, and it influences the performances of the active noise control. The sound sensor detects original noise and the antisound simultaneously, in order to cancel the influence of the antisound, this paper proposes a method to identify the model of the acoustic feedback path between the secondary sound source and the sound error sensor. This paper uses a finite impulse response filter to express the model of the above acoustic feedback path. It designs an offline experiment without original noise to identify the model individually. In the experiment, it generates white noise as the antisound and uses recursive least squares algorithm to identify the parameters of the model. It deduces the formula of the identification and analyzes the results of the experiment. The experiment results show that the proposed method model the acoustic feedback model accurately.

关键词： active noise control secondary sound source recursive least squares algorithm model identification adaptive filter

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The parameter identification of the autonomous underwater vehicle based on multi-innovation least squares identification algorithm

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INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 2020年第2期17卷

作者： Zhang, Huajun Tong, Xinchi Hang, Guo Shou, Xia Wuhan Univ Technol Sch Automat Wuhan 430070 Peoples R China

An accurate model is important for the engineer to design a robust controller for the autonomous underwater vehicle. There are two factors that make the identification difficult to get accurate parameters of an AUV model in practice. Firstly, the autonomous underwater vehicle model is a coupled six-degrees-of-freedom model, and each state of the kinetic model influences the other five states. Secondly, there are more than 100 hydrodynamic coefficients which have different effects, and some parameters are too small to be identified. This article proposes a simplified six-degrees-of-freedom model that contains the essential parameters and employs the multi-innovation least squares algorithm based on the recursive least squares algorithm to obtain the parameters. The multi-innovation least squares algorithm leverages several past errors to identify the parameters, and the identification results are more accurate than those of the recursive least squares algorithm. It collects the practical data through an experiment and designs a numerical program to identify the model parameters. Meanwhile, it compares the performances of the multi-innovation least squares algorithm with those of the recursive least squares algorithm and the least square method, the results show that the multi-innovation least squares algorithm is the most effective way to identify parameters for the simplified six-degrees-of-freedom model.

关键词： Autonomous underwater vehicle multi-innovation least squares algorithm parameter identification recursive least squares algorithm hydrodynamic coefficients

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Parameter-Free Model Predictive Current Control for PMSM Based on Current Variation Estimation without Position Sensor

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ENERGIES 2023年第19期16卷 6792页

作者： Luo, Laiwu Yu, Feng Ren, Lei Lu, Cheng Nantong Univ Sch Elect Engn Nantong 226019 Peoples R China

To remove parameter dependence in existing sensorless control strategies, a parameter-free model predictive current control is proposed for permanent magnet synchronous motor without any position sensor. First, the current variation during one sampling period is analyzed and divided into two elements: natural attenuation and forced response. Second, recursive least squares algorithm is utilized to estimate the future current variation so that the model predictive current control can be successfully executed paying no attention to motor parameters. Meanwhile, the position information is obtained by the arc tangent function according to the estimated forced response of current variation. At last, experimental results verify that the estimation errors of rotor position are reduced to around 0.1 rad with smaller current prediction error even at low speed where no motor parameters are required.

关键词： sensorless control parameter-free model predictive current control permanent magnet synchronous motor recursive least squares algorithm

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Modified RLS algorithm for second-order Volterra filter

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Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China 2005年第4期34卷 467-469+473页

作者： Chen, Kai-Ya Wang, Min-Xi Inst. of Electromag. Field and Microwave Tech. Southwest Jiaotong Univ. Chengdu 610031 China

A fast RLS algorithm for second-order Volterra filter is analyzed. And the contradiction between speed and accuracy of convergence is revealed. The modified RLS algorithm is presented by substituting constant forgetting-factor with function of forgetting-factor constructed in this paper. The rules for constructing forgetting-factor function and the method for selecting parameters is discussed. Finally, a numerical example shows that the modified RLS algorithm result in faster convergence speed by solving the contradiction between speed and accuracy.

关键词： Adaptive filtering algorithm Forgetting-factor least squares criterion recursive least squares algorithm Second-order Volterra filter

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Adaptive Notch Filter for Piezo-Actuated Nanopositioning System via Position and Online Estimate Dual-Mode

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MICROMACHINES 2021年第12期12卷 1525-1525页

作者： Huang, Chengsi Li, Hongcheng Guangdong Univ Technol Sch Electromech Engn Guangzhou 510006 Peoples R China

Due to the excellent advantages of high speed, high precision, and driving force, piezoelectric actuators nanopositioning systems have been widely used in various micro/nanomachining fields. However, the inherent resonance dynamic of the nanopositioning system generated by the flexure-hinge greatly deteriorates the positioning performance and limits the closed-loop bandwidth. Even worse, the notch filter for eliminating the effect of resonance does not work due to the varying resonant frequency resulting from the external disturbance or mass load. To this end, an adaptive notch filter for piezo-actuated nanopositioning system via position and online estimate dual-mode (POEDM) has been proposed in this paper, which can estimate the varying resonant frequency in real-time and suppress the resonance to improve the closed-loop bandwidth. First, a novel variable forgetting factor recursive least squares (VFF-RLS) algorithm for estimating resonant frequency online is presented, which is robust to the noise and provides the performances of both fast tracking and stability. Then, a POEDM method is proposed to achieve the online identification of the resonant frequency in the presence of noise and disturbance. Finally, a series of validation simulations are carried out, and the results indicate that, the frequency of input signal and the bandwidth have been achieved up to 12.5% and 87.5% of the first resonant frequency, respectively.

关键词： online system identification adaptive notch filter variable forgetting factor recursive least squares algorithm piezoelectric actuator nanopositioning

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Real-Time State of Charge Estimation of the Extended Kalman Filter and Unscented Kalman Filter algorithms Under Different Working Conditions

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JOURNAL OF ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE 2021年第4期18卷 041007-041007页

作者： Peng, Xiongbin Li, Yuwu Yang, Wei Garg, Akhil Shantou Univ Minist Educ Key Lab Intelligent Mfg Shantou 515063 Peoples R China Zhejiang Univ Ningbo Res Inst Ningbo 313100 Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Digital Mfg Equipment & Technol Wuhan 515063 Peoples R China

In the battery management system (BMS), the state of charge (SOC) is a very influential factor, which can prevent overcharge and over-discharge of the lithium-ion battery (LIB). This paper proposed a battery modeling and online battery parameter identification method based on the Thevenin equivalent circuit model (ECM) and recursive least squares (RLS) algorithm with forgetting factor. The proposed model proved to have high accuracy. The error between the ECM terminal voltage value and the actual value basically fluctuates between +/- 0.1 V. The extended Kalman filter (EKF) algorithm and the unscented Kalman filter (UKF) algorithm were applied to estimate the SOC of the battery based on the proposed model. The SOC experimental results obtained under dynamic stress test (DST), federal urban driving schedule (FUDS), and US06 cycle conditions were analyzed. The maximum deviation of the SOC based on EKF was 1.4112-2.5988%, and the maximum deviation of the SOC based on UKF was 0.3172-0.3388%. The SOC estimation method based on UKF and RLS provides a smaller deviation and better adaptability in different working conditions, which makes it more implementable in a real-world automobile application.

关键词： lithium-ion battery state of charge recursive least squares algorithm extended kalman filter unscented kalman filter battery thermal management

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