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Improved tangential interpolation-based multi-input multi-output modal analysis of a full aircraft

EUROPEAN JOURNAL OF MECHANICS A-SOLIDS 2025年 110卷

作者： Dessena, Gabriele Civera, Marco Univ Carlos III Madrid Dept Aerosp Engn Ave Univ 30 Leganes 28911 Madrid Spain Politecn Torino Dept Struct Bldg & Geotech Engn Corso Duca Abruzzi 24 I-10129 Turin Piedmont Italy

In the field of Structural Dynamics, modal analysis is the foundation of System Identification and vibration- based inspection. However, despite their widespread use, current state-of-the-art methods for extracting modal parameters from multi-input multi-output (MIMO) frequency domain data are still affected by many technical limitations. Mainly, they can be computationally cumbersome and/or negatively affected by close-in-frequency modes. The Loewner Framework (LF) was recently proposed to alleviate these problems with the limitation of working with single-input data only. This work proposes a computationally improved version of the LF, or iLF, to extract modal parameters more efficiently. Also, the proposed implementation is extended in order to handle MIMO data in the frequency domain. This new implementation is compared to state-of-the-art methods such as the frequency domain implementations of the Least Square Complex Exponential method and the Numerical Algorithm for Subspace State Space System Identification on numerical and experimental datasets. More specifically, a finite element model of a 3D Euler-Bernoulli beam is used for the baseline comparison and the noise robustness verification of the proposed MIMO iLF algorithm. Then, an experimental dataset from MIMO ground vibration tests of a trainer jet aircraft with over 91 accelerometer channels is chosen for the algorithm validation on a real-life application. Its validation is carried out with known results from a single-input multi-output dataset of the starboard wing of the same aircraft. Excellent results are achieved in terms of accuracy, robustness to noise, and computational performance by the proposed improved MIMO method, both on the numerical and the experimental datasets. The MIMO iLF MATLAB implementation is shared in the work supplementary material.

关键词： Loewner framework multi-input multi-output Tangential interpolation Ground vibration testing Modal analysis Aeronautical structures Vibration

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multi-input multi-output temporal convolutional network for predicting the long-term water quality of ocean ranches

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2023年第3期30卷 7914-7929页

作者： Zhang, Xuan Li, Dashe Shandong Technol & Business Univ Sch Comp Sci & Technol Binhai Middle Rd Yantai 264005 Shandong Peoples R China Shandong Technol & Business Univ Key Lab Intelligent Informat Proc Binhai Middle Rd Yantai 264005 Shandong Peoples R China Shandong Technol & Business Univ Coinnovat Ctr Shandong Coll & Univ Future Intelli Binhai Middle Rd Yantai 264005 Shandong Peoples R China

The prediction of water quality parameters is of great significance to the control of marine environments and provides a scientific decision-making basis for maintaining the stability of water environments and ensuring the normal survival and growth of marine aquatic products. However, the water quality in ocean ranches is affected by the complex, dynamic, and changeable environments of open water, which have complex nonlinear relationships, poor accuracy, high time complexity, and poor long-term predictability. Therefore, in this paper, a multi-input multi-output end-to-end prediction model based on a temporal convolutional network (MIMO-TCN) is proposed to predict water quality. A ConvNeXt module and TCN module were used as the model encoder and decoder, respectively. ConvNeXt was used to extract the features of the input data, and the TCN used the extracted feature data to achieve improved prediction accuracy. The model adds skip connections between its modules to solve the gradient disappearance problem as the number of network layers increases. To prove the effectiveness of the proposed method, a model robustness and prediction ability evaluation was conducted in this paper based on the dissolved oxygen in multiple ocean pasture validation samples. Compared with other learning models, the mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) of the MIMO-TCN prediction results were reduced by 60.77%, 30.88%, and 52.45% on average, respectively, and the R-2 improved by 6.07% on average over those of other models. The experimental results show that the proposed method has higher forecasting accuracy than competing approaches.

关键词： Water quality Deep learning Temporal convolutional network Prediction Long term multi-input multi-output

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multi-input multi-output VIBRATION MODEL FOR MOTORBIKE EXCITED BY RIDE TEST

MULTI-INPUT MULTI-OUTPUT VIBRATION MODEL FOR MOTORBIKE EXCIT...

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ASME International Design Engineering Technical Conferences / 43rd Annual Computers and Information in Engineering Conference (IDETC-CIE)

作者： Cavacece, Massimo Figliolini, Giorgio Lanni, Chiara Univ Cassino & Southern Lazio Dept Civil & Mech Engn Frosinone Italy

ISBN: (纸本)9780791887295

This research proposes a multi-input multi-output model (MIMO) to identify the modal properties of a motorbike during the riding test. The MIMO process verifies that a linear combination of all inputs causes each output, and there are no causal relationships between the inputs. If there are causal relationships between one of the outputs, the MIMO process redefines the input signals. The process verifies the connection between input-output and the presence of noise extraneous to the inputs and outputs. The MIMO process represents a multiple-input system with a single output. The peculiar aspect is the decoupling of individual information. In the presence of coupling between the separate inputs, the authors propose the principal component analysis (PCA) to decouple the inputs.

关键词： multi-input multi-output Modal properties Comfort Assessment Ride Test

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Control method for multi-input multi-output non-Gaussian random vibration test with cross spectra consideration

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Chinese Journal of Aeronautics 2017年第6期30卷 1895-1906页

作者： Ronghui ZHENG Huaihai CHEN Xudong HE State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and Astronautics Nanjing 210016 China

A control method for multi-input multi-output（MIMO） non-Gaussian random vibration test with cross spectra consideration is proposed in the paper. The aim of the proposed control method is to replicate the specified references composed of auto spectral densities, cross spectral densities and kurtoses on the test article in the laboratory. It is found that the cross spectral densities will bring intractable coupling problems and induce difficulty for the control of the multioutput kurtoses. Hence, a sequential phase modification method is put forward to solve the coupling problems in multi-input multi-output non-Gaussian random vibration test. To achieve the specified responses, an improved zero memory nonlinear transformation is utilized first to modify the Fourier phases of the signals with sequential phase modification method to obtain one frame reference response signals which satisfy the reference spectra and reference kurtoses. Then, an inverse system method is used in frequency domain to obtain the continuous stationary drive signals. At the same time, the matrix power control algorithm is utilized to control the spectra and kurtoses of the response signals further. At the end of the paper, a simulation example with a cantilever beam and a vibration shaker test are implemented and the results support the proposed method very well.

关键词： Cross spectra Kurtosis control multi-input multi-output Non-Gaussian Random vibration test

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Low-rank based multi-input multi-output Takagi-Sugeno fuzzy modeling for prediction of molten iron quality in blast furnace

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FUZZY SETS AND SYSTEMS 2021年 421卷 178-192页

作者： Li, Junpeng Hua, Changchun Qian, Junlei Guan, Xinping Yanshan Univ Engn Res Ctr Minist Educ Intelligent Control Syst & Intelligen Qinhuangdao 066004 Hebei Peoples R China North China Univ Sci & Technol Coll Elect Engn Tangshan 063000 Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China

For complex blast furnace smelting systems with large time delay, accurate prediction of molten iron quality indicators plays an important guiding role in blast furnace control. Recently, some data-driven multi-input multi-output (MIMO) modeling methods have been proposed to model multiple molten iron quality indicators including molten iron temperature (MIT), silicon content ([Si]), phosphorus content ([P]) and sulfur content ([S]). However, those data-driven MIMO models do not consider the inter indicator correlation, which leads to the suboptimal model for the estimation of multiple molten iron quality indicators. This paper proposed a novel MIMO Takagi-Sugeno (T-S) fuzzy model with taking full account of the inter-indicator correlation. In the novel method, the inter-indicator correlation was explicitly modeled by a low-rank learning in a latent space that overcame the great challenge of jointly determining the fuzzy rules of MIMO T-S model and the inter-indicator correlation. For the corresponding optimization problem, an effective alternating optimization algorithm is presented. The validity of the proposed method is verified by simulation and comparison with some related methods on real blast furnace data. (c) 2020 Elsevier B.V. All rights reserved.

关键词： Takagi-Sugeno fuzzy model multi-input multi-output Blast furnace Molten iron quality Silicon content

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A compact multi-band multi-input multi-output antenna for 4G/5G and IoT devices using theory of characteristic modes

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2020年第1期30卷 e22012-e22012页

作者： Kumar, Naveen Khanna, Rajesh Thapar Inst Engn & Technol Dept Elect & Commun Engn POB 32Bhadson Rd Patiala Punjab India

A compact four element multi-band multi-input multi-output (MIMO) antenna system for 4G/5G and IoT applications is presented in this paper. The proposed antenna is developed using the theory of characteristic modes helping in systematic design of MIMO antenna system. It consists of four L-shaped planar inverted-F antenna (PIFA) elements each operating at 3.5, 12.5, and 17 GHz bands with the bandwidth of 359 MHz, 1 GHz, and more than 3.7 GHz, respectively. The proposed antenna system is suitable for both 4G/5G and internet of things devices as it shows the satisfactory MIMO system performance. Good isolation characteristics are observed by implementing complimentary Metamaterial structure on the ground plane resulting in isolation level lower than -21 dB between the antenna elements. The proposed antenna is fabricated and experimental results are also presented and discussed.

关键词： 5G IoT multi-input multi-output planar inverted-F antenna theory of characteristic modes

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L₁ adaptive controller for a class of non-affine multi-input multi-output nonlinear systems

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INTERNATIONAL JOURNAL OF CONTROL 2013年第2期86卷 348-359页

作者： Luo, Jie Cao, Chengyu Yang, Qinmin Univ Connecticut Dept Mech Engn Storrs CT 06269 USA Zhejiang Univ Dept Control Sci & Engn Hangzhou Zhejiang Peoples R China

In this article, an extension of the L-1 adaptive control design is introduced for a class of non-affine multi-input multi-output nonlinear systems with unknown dynamics and unmeasured states. The system dynamics is represented in the normal form with the bounded-input-bounded-output internal dynamics. At first, a stable virtual reference counterpart is constructed. Thereafter, a piece-wise continuous adaptive law is introduced to the actual system along with a low-pass filtered control signal that allows for achieving arbitrarily close tracking of the input and the output signals of the reference system. Rigorous mathematical proof is provided, and the theoretical results are verified with the simulation.

关键词： L-1 adaptive control non-affine nonlinear systems multi-input multi-output

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Control algorithm update for multi-input multi-output random environment test

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2018年 111卷 643-662页

作者： Cui, Song Chen, Huaihai He, Xudong Zheng, Wei Nanjing Univ Aeronaut & Astronaut State Key Lab Mech & Control Mech Struct Nanjing 210016 Jiangsu Peoples R China

When conducting multi-input multi-output (MIMO) random vibration environment test, response spectral lines of under test article may exceed their tolerances and some of them can hardly be controlled by control algorithms. The cause of this phenomenon is the high level noises in the input forces, which are induced by the inverse of the ill-conditioned frequency response function matrices. These spectral lines may even trigger the instability of control algorithms and eventually result in an accidental test shutoff. The classical control algorithm for MIMO random vibration environment test contributed by Smallwood is analyzed theoretically and experimentally in the paper to reveal its weakness on dealing with this kind of error. An updated algorithm is proposed on the basis of inverse theory to overcome the difficulty of controlling these stubborn spectral lines. The main idea of the work is to reduce the level of noise components in input forces by regularizing singular values of ill-conditioned frequency response function matrices. An adjusting rule is set up according to the auto-power spectra tolerances. A simulation and an experiment are supplied in the paper to verify the effectiveness of the updated algorithm, the results are satisfactory. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： multi-input multi-output Vibration environment test Random Ill-condition Control algorithm

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Three bounded proofs for nonlinear multi-input multi-output approximate dynamic programming based on the Lyapunov stability theory

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OPTIMAL CONTROL APPLICATIONS & METHODS 2018年第1期39卷 35-50页

作者： Huang, Zhijian Xiong, Xuemei Chen, Wentao Zhang, Qin Liu, Yihua Chen, Yuli Shanghai Maritime Univ Merchant Marine Coll Shanghai 201306 Peoples R China Shanghai Jiao Thng Univ Inst Power Plant & Automat Shanghai 200030 Peoples R China

The approximate dynamic programming needs 2 prerequisites to be an effective optimal control method. Firstly, it must be assured to be stable and convergent before application. Secondly, the control system should mainly he a nonlinear multi-input multi-output form. Thus, this paper introduces a nonlinear multi-input multi-output approximate dynamic programming and proves that it is stable in Lyapunov sense, therefore it is convergent. Besides, the Lyapunov function design is also analyzed. These proofs are based on the Lyapunov stability theory in the form of the utility function of quadratic, square-weighted sum, and absolute value. Thereafter, 3 typical control examples of nonlinear multi-input multi-output approximate dynamic programming arc offered to show their applications and verify the proofs. The proof overcomes the complex derivation, and the results contain 3 practical and systematic bounded proofs. It is for the first time that the proof focuses on nonlinear multi-input multi-output approximate dynamic programming from the view of utility function. What is more, the results can also serve as an effective analysis and guide for the utility function design and the stability criterion of nonlinear multi-input multi-output approximate dynamic programming as well.

关键词： approximate dynamic programming bounded proof convergent emission glider idling Lyapunov stability theory multi-input multi-output nonlinear utility function

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Probability distributions control for multi-input multi-output stationary non-Gaussian random vibration test

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JOURNAL OF VIBRATION AND CONTROL 2018年第21期24卷 5201-5210页

作者： Zheng, Ronghui Chen, Huaihai He, Xudong Zheng, Wei Nanjing Univ Aeronaut & Astronaut State Key Lab Mech & Control Mech Struct Nanjing Jiangsu Peoples R China

An inverse system method for multi-input multi-output stationary non-Gaussian random vibration test is proposed in the paper to control the response characteristics both in time-domain and frequency-domain simultaneously. Hence, the control objectives are not only the traditional response power spectral densities but also probability distributions. The control of the probability distributions is more comprehensive and reasonable than the control of kurtoses in order to duplicate the time-domain characteristics of the measured data because kurtoses provide only partial behaviors of the probability distributions. The nonlinear transformation process is introduced to generate non-Gaussian random signals with specified probability distributions. To obtain the desired vibration environments for the test, the reference response signals are synthesized first by the reference spectra and probability distributions, and then the coupled drive signals are generated via the inverse system in the time domain. The close loop correction algorithms are implemented to update the drive signals, actually to update the reference response signals according to the deviations between the references and the measured responses. Finally, a numerical example by a cantilever beam and a biaxial vibration test are carried out and the results demonstrate the effectiveness and feasibility of the proposed method.

关键词： Inverse system multi-input multi-output non-Gaussian probability distribution vibration control

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