Article
Mathematics, Applied
Dan Wilson
Summary: Koopman analysis provides theoretical basis for dynamic mode decomposition algorithms, which approximate nonlinear dynamical systems using linear operators. However, while these methods are widely used in time-series data analysis, the resulting linear models are usually of high order and may lead to overfitting, limiting predictive capabilities. This work explores strategies for nonlinear data-driven system identification inspired by Koopman analysis, presenting general approaches for both controlled and uncontrolled systems. By projecting the resulting nonlinear equations onto a low-rank basis, a low-order representation for the dynamical system can be obtained. Computational and experimental examples show that linear estimators of the Koopman operator only provide short-term predictions, while comparable nonlinear estimators accurately predict on longer timescales and replicate infinite-time behaviors.
SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS
(2023)
Article
Engineering, Mechanical
M. Wasi Ahmadi, Thomas L. Hill, Jason Z. Jiang, Simon A. Neild
Summary: In the field of structural dynamics, system identification is used to build mathematical models from experimental data sets. This study focuses on robust identification of geometrically nonlinear structures with large inertial effects. Drawing inspiration from reduced-order modelling, a suitable model for system identification is determined. The ROM-inspired model improves the accuracy of predicted response and exhibits robustness in estimating parameters.
NONLINEAR DYNAMICS
(2023)
Article
Engineering, Ocean
Nicholas Husser, Stefano Brizzolara
Summary: Using forced motion Unsteady RANSE CFD simulations and nonlinear system identification, a method to derive a nonlinear model of the vertical plane hydrodynamic forces and moments on a planing hull has been investigated. This methodology aims to provide higher fidelity predictions of vertical plane motions of planning hulls with lower computational expense, compared to comprehensive CFD evaluation in waves. The selected nonlinear model is found to predict the heave force and trimming moment with good accuracy.
APPLIED OCEAN RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Pranav Sharma, Venkataramana Ajjarapu, Umesh Vaidya
Summary: In this paper, a novel approach for the data-driven characterization of power system dynamics is proposed. The method called Extended Subspace Identification (ESI) is suitable for systems with output measurements when all the dynamics states are not observable. It is particularly applicable for power systems dynamic identification using Phasor Measurement Units (PMUs) measurements. The ESI method is suitable for system identification, capturing nonlinear modes, computing participation factor of output measurements in system modes and identifying system parameters such as system inertia.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Automation & Control Systems
Konstantinos Zisis, Charalampos P. Bechlioulis, George A. Rovithakis
Summary: In this article, we propose an adaptive parameter estimation problem based on the theoretical foundations of radial basis function neural networks, which is solved using the prescribed performance control methodology. This approach provides a compact and user-configurable method for identifying the dynamics of open-loop nonlinear plants in any region of interest.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Mathematics, Interdisciplinary Applications
Baolei Wei
Summary: The study proposes an integral SINDy (ISINDy) method to identify the model structure and parameters of nonlinear ordinary differential equations (ODEs) from noisy time-series observations. The approach combines penalized spline smoothing and sequential threshold least squares to achieve sparse pseudo linear regression and extract the fewest active terms. The method shows accuracy and robustness to noise in various simulations.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Computer Science, Artificial Intelligence
Zhechen Zhu, Quanxin Zhu
Summary: In this article, an adaptive fuzzy decentralized fault-tolerant control strategy is constructed for a stochastic nonlinear interconnected system with nontriangular structural uncertainties, unmodeled dynamics, and actuator faults. The difficulty caused by the nontriangular structural uncertainties mixed with unmodeled dynamics in system controller design is handled by utilizing the variable separation technique and fuzzy logic system. A fault-tolerant controller is designed based on the adaptive compensation technique to solve the influence of actuator faults on system stability. The stability of the stochastic nonlinear interconnected system is ensured by stochastic Lyapunov stability theory, and numerical and practical simulations demonstrate the effectiveness of the proposed control strategy.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Automation & Control Systems
Gerben I. Beintema, Maarten Schoukens, Roland Toth
Summary: This paper proposes a new method for nonlinear system identification, which addresses the issues of noise handling and model consistency. The method utilizes a truncated prediction loss and a subspace encoder to estimate the system's state. Theoretical analysis shows that the method is locally consistent, increases optimization stability, and improves data efficiency by allowing for overlap between truncated subsections. Practical insights and user guidelines are provided through a numerical example and benchmark results.
Article
Computer Science, Information Systems
Haoyu Li, Ke Zhang, Minghu Tan
Summary: In this research, a novel identification algorithm for nonlinear Markov jump systems (NMJSs) is proposed, which utilizes a new particle system and an extended smoother to infer hidden states and update parameters of nonlinear functions. Experimental results demonstrate that the proposed algorithm can approximate the parameters that describe the data well, and outperform other related approaches.
INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Rodolphe Sepulchre
Summary: This article is the introductory editorial for this issue of the publication.
IEEE CONTROL SYSTEMS MAGAZINE
(2022)
Article
Chemistry, Multidisciplinary
Hsin-Lin Chiu
Summary: A systematic identification approach for the rotor/RAMB system is proposed, including the identification and construction of linear dynamic models for the controller, as well as the utilization of a parallel amplitude-modulated pseudo-random binary sequence generator to excite the nonlinearities of the system. The dynamics of the rotor/RAMB system are identified using a Hammerstein-Wiener model, and the effectiveness of the identified model is verified through a comparison with NARX and NARMAX models.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Mechanical
Tong Liu, Hadi Meidani
Summary: In this paper, a novel physics-informed neural network approach is proposed for nonlinear structural system identification and its application in multiphysics cases is demonstrated. The proposed approach improves the estimation of the parameters of nonlinear structural systems by integrating auxiliary physics-based loss terms, and uses subsampling and early stopping strategies to ensure effective learning. The framework also has the capability to predict nonlinear responses for unseen ground excitations.
JOURNAL OF ENGINEERING MECHANICS
(2023)
Article
Automation & Control Systems
Jarrad Courts, Adrian G. Wills, Thomas B. Schon, Brett Ninness
Summary: This paper addresses the challenging problem of parameter estimation for nonlinear state-space models by employing a variational inference approach, which provides deterministic and tractable estimates through an optimization problem. A specialized method for systems with additive Gaussian noise is also presented. Numerical experiments demonstrate the robustness of the proposed method in parameter initialization and favorable comparisons against state-of-the-art alternatives.
Review
Engineering, Mechanical
Kai Zhou, Zequn Wang, Qingbin Gao, Sichen Yuan, Jiong Tang
Summary: Structural dynamics has various practical applications, but current research tends to overlook uncertainties that arise from numerical model inadequacy, as well as randomness in experimental setup and measurement. Therefore, there is a need to develop a unified numerical or experimental platform that can account for inherent uncertainties to achieve successful engineering practices.
PROBABILISTIC ENGINEERING MECHANICS
(2023)
Article
Automation & Control Systems
Adil Brouri
Summary: In this paper, a new approach is developed to identify Wiener-Hammerstein model structures. The method does not make any assumptions about the structure of the linear elements' transfer functions and successfully separates the dynamics of input and output elements through a two-stage identification process.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Engineering, Mechanical
Xuanen Kan, Yanjun Lu, Fan Zhang, Weipeng Hu
Summary: A blade disk system is crucial for the energy conversion efficiency of turbomachinery, but differences between blades can result in localized vibration. This study develops an approximate symplectic method to simulate vibration localization in a mistuned bladed disk system and reveals the influences of initial positive pressure, contact angle, and surface roughness on the strength of vibration localization.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Zimeng Liu, Cheng Chang, Haodong Hu, Hui Ma, Kaigang Yuan, Xin Li, Xiaojian Zhao, Zhike Peng
Summary: Considering the calculation efficiency and accuracy of meshing characteristics of gear pair with tooth root crack fault, a parametric model of cracked spur gear is established by simplifying the crack propagation path. The LTCA method is used to calculate the time-varying meshing stiffness and transmission error, and the results are verified by finite element method. The study also proposes a crack area share index to measure the degree of crack fault and determines the application range of simplified crack propagation path.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Rongjian Sun, Conggan Ma, Nic Zhang, Chuyo Kaku, Yu Zhang, Qirui Hou
Summary: This paper proposes a novel forward calculation method (FCM) for calculating anisotropic material parameters (AMPs) of the motor stator assembly, considering structural discontinuities and composite material properties. The method is based on multi-scale theory and decouples the multi-scale equations to describe the equivalence and equivalence preconditions of AMPs of two scale models. The effectiveness of this method is verified by modal experiments.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Hao Zhang, Jiangcen Ke
Summary: This research introduces an intelligent scheduling system framework to optimize the ship lock schedule of the Three Gorges Hub. By analyzing navigational rules, operational characteristics, and existing problems, a mixed-integer nonlinear programming model is formulated with multiple objectives and constraints, and a hybrid intelligent algorithm is constructed for optimization.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Jingjing He, Xizhong Wu, Xuefei Guan
Summary: A sensitivity and reliability enhanced ultrasonic method has been developed in this study to monitor and predict stress loss in pre-stressed multi-layer structures. The method leverages the potential breathing effect of porous cushion materials in the structures to increase the sensitivity of the signal feature to stress loss. Experimental investigations show that the proposed method offers improved accuracy, reliability, and sensitivity to stress change.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Benyamin Hosseiny, Jalal Amini, Hossein Aghababaei
Summary: This paper presents a method for monitoring sub-second or sub-minute displacements using GBSAR signals, which employs spectral estimation to achieve multi-dimensional target detection. It improves the processing of MIMO radar data and enables high-resolution fast displacement monitoring from GBSAR signals.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xianze Li, Hao Su, Ling Xiang, Qingtao Yao, Aijun Hu
Summary: This paper proposes a novel method for bearing fault identification, which can accurately identify faults with few samples under complex working conditions. The method is based on a Transformer meta-learning model, and the final result is determined by the weighted voting of multiple models.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xiaomeng Li, Yi Wang, Guangyao Zhang, Baoping Tang, Yi Qin
Summary: Inspired by chaos fractal theory and slowly varying damage dynamics theory, this paper proposes a new health monitoring indicator for vibration signals of rotating machinery, which can effectively monitor the mechanical condition under both cyclo-stationary and variable operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Hao Wang, Songye Zhu
Summary: This paper extends the latching mechanism to vibration control to improve energy dissipation efficiency. An innovative semi-active latched mass damper (LMD) is proposed, and different latching control strategies are tested and evaluated. The latching control can optimize the phase lag between control force and structural response, and provide an innovative solution to improve damper effectiveness and develop adaptive semi-active dampers.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Menghao Ping, Xinyu Jia, Costas Papadimitriou, Xu Han, Chao Jiang, Wang-Ji Yan
Summary: Identification of non-Gaussian processes is a challenging task in engineering problems. This article presents an improved orthogonal series expansion method to convert the identification of non-Gaussian processes into a finite number of non-Gaussian coefficients. The uncertainty of these coefficients is quantified using polynomial chaos expansion. The proposed method is applicable to both stationary and nonstationary non-Gaussian processes and has been validated through simulated data and real-world applications.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Lei Li, Wei Yang, Dongfa Li, Jianxin Han, Wenming Zhang
Summary: The frequency locking phenomenon induced by modal coupling can effectively overcome the dependence of peak frequency on driving strength in nonlinear resonant systems and improve the stability of peak frequency. This study proposes the double frequencies locking phenomenon in a three degrees of freedom (3-DOF) magnetic coupled resonant system driven by piezoelectricity. Experimental and theoretical investigations confirm the occurrence of first frequency locking and the subsequent switching to second frequency locking with the increase of driving force. Furthermore, a mass sensing scheme for double analytes is proposed based on the double frequencies locking phenomenon.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Kai Ma, Jingtao Du, Yang Liu, Ximing Chen
Summary: This study explores the feasibility of using nonlinear energy sinks (NES) as replacements for traditional linear tuned mass dampers (TMD) in practical engineering applications, specifically in diesel engine crankshafts. The results show that NES provides better vibration attenuation for the crankshaft compared to TMD under different operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Wentao Xu, Li Cheng, Shuaihao Lei, Lei Yu, Weixuan Jiao
Summary: In this study, a high-precision hydraulic mechanical stand and a vertical mixed-flow pumping station device were used to conduct research on cavitation signals of mixed-flow pumps. By analyzing the water pressure pulsation signal, it was found that the power spectrum density method is more sensitive and capable of extracting characteristics compared to traditional time-frequency domain analysis. This has significant implications for the identification and prevention of cavitation in mixed-flow pump machinery.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xiaodong Chen, Kang Tai, Huifeng Tan, Zhimin Xie
Summary: This paper addresses the issue of parasitic motion in microgripper jaws and its impact on clamping accuracy, and proposes a symmetrically stressed parallelogram mechanism as a solution. Through mechanical modeling and experimental validation, the effectiveness of this method is demonstrated.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Zhifeng Shi, Gang Zhang, Jing Liu, Xinbin Li, Yajun Xu, Changfeng Yan
Summary: This study provides useful guidance for early bearing fault detection and diagnosis by investigating the effects of crack inclination and propagation direction on the vibration characteristics of bearings.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)