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Hierarchical iterative identification of output nonlinear Box-Jenkins Wiener model with ARMA noise

ISA TRANSACTIONS 2023年 143卷 321-333页

作者： Nadi, Mahdi Arefi, Mohammad Mehdi Shiraz Univ Sch Elect & Comp Engn Dept Power & Control Engn Shiraz Iran

This paper focuses on development of a three-stage iterative identification algorithm for parameter estimation of a Wiener model with autoregressive moving average (ARMA) noise entering between linear and nonlinear part. The proposed three-stage algorithm is developed based on generalized extended gradient iterative (GEGI) algorithm to increase the convergence rate at a low number of iterations. To increase the convergence rate, a second algorithm is derived based on generalized extended least squares algorithm (GELSI). The proposed 3stage generalized extended least square iterative (3S-GELSI) algorithm will also decrease the computational burden compared to the single-stage algorithm. Finally, to show that the discussed methods can identify the considered system effectively, simulation results of three examples are provided. The results demonstrate that the 3-stage GEGI (3S-GEGI) algorithm outperforms its basic single-stage counterpart in terms of convergence rate. Moreover, the proposed 3S-GELSI algorithm exhibits even greater superiority in terms of convergence rate compared to other existing methods. Additionally, it will be demonstrated that the computational burden decreases in the 3S-GELSI algorithm, as indicated by the reduced number of total flops.

关键词： Gradient -based algorithm Hierarchical principal Iterative identification least squares algorithm Wiener systems

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Speed control of vehicle automatic driving system based on 5G vehicle network

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INTERNATIONAL JOURNAL OF VEHICLE DESIGN 2021年第1-4期86卷 71-87页

作者： Song Ming-lei Li Ai-zeng Liu Li-hua Henan Univ Urban Construct Sch Civil & Transportat Engn Pingdingshan 467036 Peoples R China

In order to solve the problem of low speed control accuracy and long control time in traditional vehicle speed control system, a speed control method of vehicle automatic driving system based on 5G network is proposed. 5G internet of vehicles technology is used to collect the motion data of vehicle automatic driving, and the vehicle motion model is constructed by least squares method. The speed control model of vehicle autopilot system is built, the minimum speed algorithm is used to solve the speed governing model of the vehicle automatic driving system, and the optimal trajectory of speed control for vehicle automatic driving system is obtained, and the speed control of vehicle automatic driving system is realised. The experimental results show that: the speed control method in this paper can effectively improve the speed control accuracy of the system, up to about 99%, and the speed of speed regulation is fast.

关键词： 5G vehicle interconnection vehicle automatic driving system speed control vehicle motion model least squares algorithm minimum value algorithm

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ENCODING PRIOR KNOWLEDGE INTO DATA DRIVEN DESIGN OF INTERVAL TYPE-2 FUZZY LOGIC SYSTEMS

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2011年第3期7卷 1133-1144页

作者： Li, Chengdong Yi, Jianqiang Wang, Tiechao Shandong Jianzhu Univ Sch Informat & Elect Engn Jinan 250101 Peoples R China Chinese Acad Sci Inst Automat Beijing 100190 Peoples R China

In system identification or modeling problems, interval type-2 fuzzy logic systems (IT2FISs), which have obvious advantages for handling different sources of uncertainties, are usually constructed only using the information from sample data. This paper tries to utilize the information from both sample data and prior knowledge to design IT2FLSs to compensate the insufficiency of the information from single knowledge source. First, sufficient conditions on the antecedent and consequent parameters of IT2FLSs are given to ensure that the prior knowledge can be incorporated into IT2FLSs and three kinds of prior knowledge - bounded range, symmetry (odd and even) and monotonicity (increasing and decreasing) - are explored. Then, design of IT2FLSs using the information from both sample data and prior knowledge is transformed to the constrained least squares optimization problem. At last, to show the superiority of the proposed method, simulations and comparisons are made.

关键词： Information fusion Type-2 fuzzy least squares algorithm Prior knowledge

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Decomposition optimization method for switching models using EM algorithm

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NONLINEAR DYNAMICS 2023年第10期111卷 9361-9375页

作者： Chen, Jing Mao, Yawen Hu, Manfeng Guo, Liuxiao Zhu, Quanmin Jiangnan Univ Sch Sci Wuxi 214122 Peoples R China Univ West England Dept Engn Design & Math Bristol BS16 1QY England

This study proposes a decomposition optimization-based expectation maximization algorithm for switching models. The identities of each sub-model are estimated in the expectation step, while the parameters are updated using the decomposition optimization method in the maximization step. Compared with the traditional expectation maximization algorithm and the gradient descent expectation maximization algorithm, the decomposition optimization-based expectation maximization algorithm avoids the matrix inversion and eigenvalue calculation;thus, it can be extended to complex nonlinear models and large-scale models. Convergence analysis and simulation examples are given to show the effectiveness of the proposed algorithm.

关键词： Parameter estimation Switching model Expectation maximization algorithm Decomposition optimization method least squares algorithm

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Analysis of the Kalman filter based estimation algorithm: an orthogonal decomposition approach

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AUTOMATICA 2004年第1期40卷 5-19页

作者： Cao, LY Schwartz, HM Carleton Univ Dept Syst & Comp Engn Ottawa ON K1S 5B6 Canada Micro Opt Design Corp Moncton NB E1E 4M3 Canada

In this paper we shall provide new analysis on some fundamental properties of the Kalman filter based parameter estimation algorithms using an orthogonal decomposition approach based on the excited subspace. A theoretical analytical framework is established based on the decomposition of the covariance matrix, which appears to be very useful and effective in the analysis of a parameter estimation algorithm with the existence of an unexcited subspace. The sufficient and necessary condition for the boundedness of the covariance matrix in the Kalman filter is established. The idea of directional tracking is proposed to develop a new class of algorithms to overcome the windup problem. Based on the orthogonal decomposition approach two kinds of directional tracking algorithms are proposed. These algorithms utilize a time-varying covariance matrix and can keep stable even in the case of unsufficient and/or unbounded excitation. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： Kalman filter recursive parameter estimation least squares algorithm windup directional tracking

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Extended depth-range dual-wavelength interferometry based on iterative two-step temporal phase-unwrapping

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JOURNAL OF MODERN OPTICS 2018年第3期65卷 287-297页

作者： Wang, Minmin Zhou, Canlin Si, Shuchun Li, XiaoLei Lei, Zhenkun Li, YanJie Shandong Univ Sch Phys Jinan Shandong Peoples R China Hebei Univ Technol Sch Mech Engn Tianjin Peoples R China Dalian Univ Technol Dept Engn Mech Dalian Peoples R China Jinan Univ Sch Civil Engn & Architecture Jinan Shandong Peoples R China

For dual-wavelength interferometry (DWI), we propose an extended depth-range phase-shifting interferometry technique of extracting phase distributions from randomly phase-shifted interferograms. First, the generalized phase-shifting algorithm is utilized to retrieve the single-wavelength phase from interferograms with random phase shifts. Then, the phase difference and phase-sum are calculated from the wrapped single-wavelength phases, and iterative two-step temporal phase-unwrapping is introduced to unwrap the phase-sum. Finally, the height of objects is determined. Simulations and experiments are conducted to demonstrate the excellent precision and overall performance of the proposed method. As the limitation of being exclusively applicable to interferograms with special phase shifts is broken, the proposed method will greatly facilitate the practical application of DWI. Furthermore, because the phase-sum and iterative two-step temporal phase-unwrapping is introduced to extend the depth-range, the sensitivity and precision of the retrieved phase are greatly improved.

关键词： Two-wavelength phase-shifting algorithm temporal phase-unwrapping interferometry least squares algorithm phase error

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Improved scheme for the problem of anti-fading of DSRC systems in IEEE 802.11p environments

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IET COMMUNICATIONS 2016年第6期10卷 632-640页

作者： Ma, Tian-Ming Chinese Acad Sci Shanghai Engn Ctr Microsatellites Shanghai 201210 Peoples R China

Vehicular communication for accident avoidance is an important application defined in the IEEE 802.11p. One of the challenges of vehicular communications in the current IEEE 802.11p standard is the complex and rapidly changing channel conditions. In this study, the author focusses on the vehicle-to-vehicle channels under the IEEE 802.11p standard and point out that there exist two different kinds of fading. Then, a new dedicated short range communication (DSRC) system with two improved methods is proposed for the weak performance of anti-fading of current system in IEEE 802.11p environments. The author adopts matrix spectral transformation method to replace least squares algorithm in spectral temporal averaging (STA) scheme proposed by Fernandez to further mitigate the negative effects of DSRC system caused by fast time-varying fading. Meanwhile, the author also proposes a spectral keying method to further enhance its ability of anti-frequency-selective fading. The final simulation results show that compared with STA and other methods, the improved scheme shows better performance on mean square error, bit error rate and packet error rate, which is promising for practical applications.

关键词： wireless LAN fading channels wireless channels least squares approximations mean square error methods error statistics antifading problem DSRC systems IEEE 802.11p environments vehicular communication accident avoidance channel conditions vehicle-to-vehicle channels dedicated short range communication DSRC system least squares algorithm spectral temporal averaging STA fast time-varying fading spectral keying method antifrequency selective fading mean square error bit error rate packet error rate

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Fitting of giant magnetoimpedance curves using the complex method in optimization techniques

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PHYSICA SCRIPTA 2024年第10期99卷 105923-105923页

作者： Sun, Xutao Shen, Guotu Zhao, Zhenjie East China Normal Univ Engn Res Ctr Nanophoton & Adv Instrument Sch Phys & Elect Sci Minist Educ Shanghai 200241 Peoples R China

The giant magnetoimpedance (GMI) effect is characterized by substantial variations in both the real and imaginary components of the impedance when subjected to an alternating current in the presence of a static magnetic field. In quasistatic models, the GMI profile can be effectively delineated by the changes in transverse permeability in response to variations in the external magnetic field. Building on this, the magnetic anisotropy field and anisotropy angle for specific magnetic phases can be determined by fitting the experimental data points. The dual magnetic phase structure of the CoP/NiCoP/Cu composite wire results in a four-peak profile in its GMI curves, making it suitable as a target curve for fitting. By preprocessing the GMI curves and applying the Complex Method within optimization techniques through multiple iterations, the theoretical target curve is ultimately obtained, along with the extraction of the physical parameters embedded within it. This approach presents a novel solution to the multi-parameter curve fitting.

关键词： complex method giant magnetoimpedance spectral fitting optimization method least squares algorithm

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Experimental evaluation of parameter identification schemes on a direct-drive robot

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING 2012年第I10期226卷 1419-1431页

作者： Chavez-Olivares, Cesar A. Reyes-Cortes, Fernando Gonzalez-Galvan, Emilio J. Mendoza-Gutierrez, Marco O. Bonilla-Gutierrez, Isela Univ Autonoma San Luis Potosi Fac Ingn Ctr Invest & Estudios Posgrad San Luis Potosi 78290 Mexico Benemerita Univ Autonoma Puebla Grp Robot Puebla Mexico Univ Sonora Dept Invest Fis Hermosillo 83000 Sonora Mexico Univ Autonoma San Luis Potosi Fac Ciencias San Luis Potosi 78290 Mexico

The dynamic and friction parameters of a robot are used in advanced control schemes, and their accuracy significantly affects their performance. These parameters can also be used for a realistic simulation. In principle, the numerical value of the parameters could be obtained via computer-aided design analysis but inevitable assembly and manufacturing errors exist. Direct measurement is not a realistic option because the complex nature of the system would involve an intense time-consuming effort. Alternatively, we can deduce the values of the parameters by observing the natural response of the system under appropriate experimental conditions, that is, by using identification schemes. This article presents the experimental evaluation of five identification schemes used to obtain the dynamic and friction parameters of a two-degree-of-freedom, direct-drive robot. We assume that the dynamic and friction parameters are totally unknown but, by design, the dynamic model is fully known. We consider the schemes based on the dynamic regression model, filtered-dynamic regression model, supplied-energy regression model, power regression model, and filtered-power regression model. The article presents a comparison between experimental and simulated robot responses, which enable us to verify the accuracy of each regression model.

关键词： Direct-drive robot identification schemes regression models least squares algorithm

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Soft Fault Diagnosis and Recovery Method Based on Model Identification in Rotation FOG Inertial Navigation System

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IEEE SENSORS JOURNAL 2017年第17期17卷 5705-5716页

作者： Wang, Lingcao Li, Kui Zhang, Jun Ding, Zhenxing Beihang Univ Dept Sch Instrumentat Sci & Optoelect Engn Beijing 100191 Peoples R China

Inertial navigation system (INS) is a critical and essential equipment for vehicles, ships, and aircrafts. However, as the soft fault parameters of the INS vary with time, internal device operations and external environmental disturbances, periodic diagnosis and recovery of the soft faults are required to satisfy their accuracy requirements. The deployment of human experts for fault diagnosis and recovery in INS would mean low efficiency and heavy workload, as well as low-speed operations. In this paper, a method for automatic diagnosis and recovery of the soft faults, based on the rotation INS (RINS) error model is proposed. This method is implemented by means of a self-rotation mechanism, driven by a specially designated rotation strategy. On the basis of the attitude and change rate of velocity errors in stationary base navigation, a least squares algorithm is used for optimal soft fault parameter identification. Experimental results from a real dual-axis RINS demonstrate the effectiveness of the method in automatically, accurately, and quickly diagnosing and recovering soft faults, and further improving the accuracy of INS, after recovery.

关键词： Fault diagnosis and recovery rotation inertial navigation system calibration rotation strategy optical parameter identification least squares algorithm

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