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

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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Auxiliary Variable-Based Identification algorithms for Uncertain-Input Models

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2020年第7期39卷 3389-3404页

作者： Chen, Jing Zhu, Quanmin Chandra, Budi Pu, Yan Jiangnan Univ Sch Sci Wuxi 214122 Jiangsu Peoples R China Univ West England Dept Engn Design & Math Bristol BS16 1QY Avon England

This study presents two auxiliary variable-based identification algorithms for uncertain-input models. The auxiliary variable-based least squares algorithm can obtain unbiased parameter estimates by introducing suitable auxiliary variable vectors. Furthermore, an auxiliary variable-based recursive least squares algorithm is proposed to reduce the computational efforts. To validate the framework and algorithms developed, it has conducted a series of bench tests with computational experiments. The simulated numerical results/plots are consistent with the analytically derived results in terms of the feasibility and effectiveness of the proposed procedure.

关键词： Uncertain-input model Auxiliary variable least squares algorithm Unbiased parameter estimate Computational effort

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System Parameters’ Identification and Optimal Tracking Control for Nonlinear Systems

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IFAC-PapersOnLine 2018年第13期51卷 431-436页

作者： Vega, David Cortes Paz, Serafin Ramos Ornelas-Tellez, Fernando Rico-Melgoza, J. Jesus The authors are with the School of Electrical Engineering Universidad Michoacana de San Nicolas de Hidalgo Morelia58030 Mexico

This paper proposes a parameters’ identification methodology via the continuous-time least-squares algorithm for those nonlinear systems which are linear with respect to their parameters. The parameter identification method can be used for easily determining all the parameters in real plants from only input-output data measurements, such that a posteriori, a model-based control strategy can be synthesized. It is worth mentioning that when a control engineer wants to design a modern and sophisticated controller, usually the system model is used for such purposes, which depends on its parameters, however, in general the system parameters are not easy to determine. Also, this paper uses the parameters’ identification methodology for the design of an optimal tracking controller for state-dependent coefficient factorized (SDCF) nonlinear systems. Both, the parameters’ identification scheme and the optimal control strategy are applied via simulations for the control of a Permanent Magnet Synchronous Motor (PMSM), a three-phase nonlinear machine. © 2018

关键词： Parameter estimation Continuous time systems Controllers Identification (control systems) Nonlinear control systems Optimal control systems Permanent magnets least squares algorithm Optimal control strategy Optimal nonlinear control Optimal tracking control Parameter identification methods Permanent Magnet Synchronous Motor PMSM State dependent coefficients

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Nonlinear FIR Identification with Model Order Reduction Steiglitz-McBride⁎

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IFAC-PapersOnLine 2018年第15期51卷 646-651页

作者： Ferizbegovic, Mina Galrinho, Miguel Hjalmarsson, Håkan Department of Automatic Control School of Electrical Engineering KTH Royal Institute of Technology Stockholm Sweden

In system identification, many structures and approaches have been proposed to deal with systems with non-linear behavior. When applicable, the prediction error method, analogously to the linear case, requires minimizing a cost function that is non-convex in general. The issue with non-convexity is more problematic for non-linear models, not only due to the increased complexity of the model, but also because methods to provide consistent initialization points may not be available for many model structures. In this paper, we consider a non-linear rational finite impulse response model. We observe how the prediction error method requires minimizing a non-convex cost function, and propose a three-step least-squares algorithm as an alternative procedure. This procedure is an extension of the Model Order Reduction Steiglitz-McBride method, which is asymptotically efficient in open loop for linear models. We perform a simulation study to illustrate the applicability and performance of the method, which suggests that it is asymptotically efficient. © 2018

关键词： least squares approximations Cost functions Identification (control systems) Impulse response Model structures Religious buildings Asymptotically efficient Finite impulse response model least squares algorithm least squares identification Non linear Nonconvex cost functions Prediction error method Steiglitz Mcbride method

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GAUSSIAN BEAM APPROACH FOR THE BOUNDARY VALUE PROBLEM OF HIGH FREQUENCY HELMHOLTZ EQUATION

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COMMUNICATIONS IN MATHEMATICAL SCIENCES 2010年第4期8卷 1041-1066页

作者： Zheng, Chunxiong Tsinghua Univ Dept Math Sci Beijing 100084 Peoples R China

We propose an asymptotic numerical method called the Gaussian beam approach for the boundary value problem of high frequency Helmholtz equation. The basic idea is to approximate the traveling waves with a summation of Gaussian beams by the least squares algorithm. Gaussian beams are asymptotic solutions of linear wave equations in the high frequency regime. We deduce the ODE systems satisfied by the Gaussian beams up to third order. The key ingredient of the proposed method is the construction of a finite-dimensional beam space which has a good approximating property. If the exact solutions of boundary value problems contain some strongly evanescent wave modes, the Gaussian beam approach might fail. To remedy this problem, we resort to the domain decomposition technique to separate the domain of definition into a boundary layer region and its complementary interior region. The former is handled by a domain-based discretization method, and the latter by the Gaussian beam approach. Schwarz iterations should then be performed based on suitable transmission boundary conditions at the interface of two regions. Numerical tests demonstrate that the proposed method is very promising.

关键词： Gaussian beam high frequency Helmholtz equation domain decomposition least squares algorithm

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FINDING WELL APPROXIMATING LATTICES FOR A FINITE SET OF POINTS

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MATHEMATICS OF COMPUTATION 2019年第315期88卷 369-387页

作者： Hajdu, A. Hajdu, L. Tijdeman, R. Univ Debrecen Fac Informat POB 12 H-4010 Debrecen Hungary Univ Debrecen Inst Math POB 12 H-4010 Debrecen Hungary Leiden Univ Math Inst Postbus 9512 NL-2300 RA Leiden Netherlands

In this paper we address the task of finding well approximating lattices for a given finite set A of points in R-n motivated by practical texture analytic problems. More precisely, we search for o, d(1),..., d(n) is an element of R-n such that a - o is close to Lambda = d(1)Z + ... + d(n)Z for every a is an element of A. First we deal with the one-dimensional case, where we show that in a sense the results are almost the best possible. These results easily extend to the multi-dimensional case where the directions of the axes are given, too. Thereafter we treat the general multidimensional case. Our method relies on the LLL algorithm. Finally, we apply the least squares algorithm to optimize the results. We give several examples to illustrate our approach.

关键词： Diophantine approximation lattice LLL algorithm least squares algorithm

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System Identification of a Small Hydropower Plant 14

System Identification of a Small Hydropower Plant

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14th IEEE International Conference on Industry Applications (INDUSCON)

作者： Gracino, Rogerio Hansen, Victor Goia, Leandro Campo, Alexandre Campos, Bruno Fed Inst Sao Paulo Dept Elect Engn Sao Paulo Brazil Automal Automat Syst Jundiai Brazil

ISBN: (纸本)9781665441186

This paper presents mathematical modeling and system identification of Ninho da Aguia, a Small Hydropower Plant, considering as input the power production and as output the reservoir water level. Due to the difficulty to obtain a unique dynamic that represents the process in study, it has been developed an algorithm that identifies the system over the time. In order to establish a comparison base, the data from the real system and the prediction from the algorithm were used to analyze the efficiency of the identified model.

关键词： Small Hydropower Plant least squares algorithm System identification System modeling Simulation

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Fault Detection for a Hydrostatic Drive Chain using Online Parameter Estimation

Fault Detection for a Hydrostatic Drive Chain using Online P...

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17th International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Ritzke, Joeran Windelberg, Jens Aschemann, Harald Univ Rostock Chair Mechatron D-18059 Rostock Germany

ISBN: (纸本)9781467321242

This paper presents an approach to detect faults in a hydrostatic drive chain by means of an online recursive parameter estimation. A mechatronic model of a hydrostatic drive chain is derived with focus on single components that are composed to an overall model suitable for fault detection and identification. Assuming that faults will lead to parameter changes, this contribution proposes a least square algorithm with exponential forgetting capable of detecting faults online. Results of thorough simulation studies emphasize the performance of the algorithm and will conclude this article.

关键词： Parameter estimation Defect detection hydrostatic drive faults least squares algorithm linearly ordered set SINGLE-COMPONENT

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Automatic Generation of Movement Sequences to Robotic Arm Based on Three-Dimensional Data Obtained Through Fringe Projection Technique 5

Automatic Generation of Movement Sequences to Robotic Arm Ba...

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5th International Symposium on Experimental Mechanics (ISEM) / 9th Symposium on Optics in Industry (SOI)

作者： Bustos, S. Aguilera, C. Martinez-Garcia, Amalia Univ Bio Bio Concepcion Chile Ctr Invest Opt Leon Mexico

ISBN: (纸本)9783319285139;9783319285115

The use of robotic manipulators is a subject that has become relevant in the process of automation in different branches of industrial manufacturing. Today is possible to make routines works with robotic manipulator in dangerous conditions for human operators, providing flexibility in production lines, doing multiple types of tasks and executing actions with precision and quickly. All operations of a robotic arm is controlled by a computer system that controls the mechanism positions. Since the work of these machines is to manipulate tools or pieces, it is necessary to have tridimensional information of the environment or manipulated elements. In this work, the fringe projection technique is used to obtain three-dimensional shape of an object, and based on this information to generate the trajectories of the manipulator for the painting of complex objects through paint spraying. The obtained results have been successful, generating simulated trajectories for the painting of pieces with good quality and short times compared with times using traditional methods to program sequences.

关键词： Fringe projection least squares algorithm Robotic arm Industrial manufacturing Painting

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Identification and Robust Control for The Micro-hand Systems Using Robust Right Coprime Factorization Method 6

Identification and Robust Control for The Micro-hand Systems...

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6th International Conference on Information Science and Control Engineering (ICISCE)

作者： Bu, Ni Li, Wenpeng Liu, Haoyu Qingdao Univ Sci & Technol Coll Automat & Elect Engn Qingdao Peoples R China

ISBN: (纸本)9781728157122

In the existing Micro-hand model study, the rubber radius r(a) is a fixed value, but the rubber radius r(a) is time-varying, which needs identification. Thus, in this paper, the least squares identification algorithm is used to estimate the value of r(a). Then with the estimated value, the robust right coprime factorization combined with adaptive control are proposed to deal with the robust tracking issue, which is verified by the simulation result.

关键词： Micro-hand model actuator robust right coprime factorization least squares algorithm

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