Article
Automation & Control Systems
Yashan Xing, Lucile Bernadet, Marc Torrell, Albert Tarancon, Ramon Costa-Castello, Jing Na
Summary: This paper proposes an offline tuning strategy and an online parameter estimation method for calibrating the solid oxide fuel cell mathematical model. The offline tuning strategy is designed to tune the model under various operation conditions using particle swarm optimization and gradient-based search methods. The online parameter estimation method employs an adaptive optimal learning law to minimize a cost function with estimation error information. Experimental verification is conducted on a practical solid oxide fuel cell test bench.
Article
Energy & Fuels
Artun Sel, Bilgehan Sel, Umit Coskun, Cosku Kasnakoglu
Summary: This study investigates and compares two different parameter estimation algorithms, namely Iterated EKF and a nonlinear optimization algorithm based on on-line search methods, for estimating parameters of a permanent magnet synchronous motor with known and nonlinear dynamics. The differences between these algorithms lie in the consideration of unknown initial conditions of the dynamical system. The study also explores adaptations of these algorithms for various variations of the problem reported in the literature.
Article
Computer Science, Interdisciplinary Applications
Mirac Eryigit
Summary: This study aimed to improve the optimization model for groundwater flow modeling under more difficult conditions, successfully estimating groundwater flow parameters and demonstrating good performance.
JOURNAL OF HYDROINFORMATICS
(2021)
Article
Engineering, Electrical & Electronic
Hongyu Wei, Tao Zhang, Liang Zhang
Summary: The integrated navigation of visual and inertial measurement is a research hotpot, with analytical solution-based algorithms improving real-time performance but sacrificing accuracy, while iterative algorithms achieve high accuracy but at the cost of running time. The proposed method in this study provides a fast initial parameter estimation method for improving both real-time performance and accuracy.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Management
Taozeng Zhu, Jingui Xie, Melvyn Sim
Summary: The study introduces a joint estimation and robustness optimization framework to address the impact of estimation uncertainty in optimization problems. By incorporating both the parameter estimation process and the optimization problem seamlessly, the framework aims to obtain solutions that are immune to parameter perturbations. The size of the uncertainty set, based on the accuracy of parameter estimation from data using specific procedures, is maximized to achieve this goal.
MANAGEMENT SCIENCE
(2022)
Article
Green & Sustainable Science & Technology
Naveed Ahmed Malik, Naveed Ishtiaq Chaudhary, Muhammad Asif Zahoor Raja
Summary: The study focuses on the importance of power quality in sustainable power development and its impact on overall efficiency. The compatibility between instruments connected to the system is crucial for achieving smooth power flow. Understanding the effects of odd harmonics on amplitude and phase domain is necessary for effective system operation. The firefly optimization technique accurately estimates power signal harmonics and proves its robustness under different noise levels.
Article
Automation & Control Systems
Ling Xu
Summary: This paper considers the problem of estimating parameters in nonlinear models based on response data. It proposes a nonlinear dynamical optimization scheme to obtain parameter estimates by constructing a gradient criterion function and deriving a gradient recursion algorithm. To overcome the difficulty of determining the step-size in the algorithm, a trying method and a numerical approach are proposed. Furthermore, stochastic gradient estimation methods, including a recursive step-size method and a multi-innovation method using dynamical window data, are presented to enhance estimation accuracy.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Astronomy & Astrophysics
Junaid Yousuf, Shivaraj Kandhasamy, Manzoor A. Malik
Summary: Gravitational-wave backgrounds are expected to arise from a large number of unresolved sources and stochastic processes in the early Universe. Although we haven't detected any background yet, future improvements in detector sensitivity should make detection possible. The detection and analysis of the background will depend on the source model, search methods, and data generation in the detectors.
Article
Mathematics, Applied
Baolei Wei, Naiming Xie
Summary: This study investigates the parameter estimation of grey system models from noisy observations, and finds that nonlinear least squares has multiple advantages over the conventional integral matching method in terms of accuracy and robustness.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2021)
Article
Engineering, Electrical & Electronic
Yanbiao Zou, Jiaxin Chen, Xianzhong Wei
Summary: This article introduces a calibration optimization method for the welding robot laser vision system based on generative adversarial network, which improves the accuracy and efficiency of calibration data collection through an intelligent collection method, experimental results show its outstanding performance in uncertainty, point positioning, and tracking.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Computer Science, Interdisciplinary Applications
Anwesh Reddy Gottu Mukkula, Michal Mateas, Miroslav Fikar, Radoslav Paulen
Summary: The study focuses on robust model-based design of experiments in the context of maximum-likelihood estimation, utilizing a multi-stage robust optimization approach to address parametric uncertainties in experiment design. The findings suggest that conducting experiments in multiple stages can improve effectiveness when parameter knowledge is limited.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Environmental Sciences
Nicholas J. Elmer, James McCreight, Christopher Hain
Summary: The study assesses the utility of SWOT for model parameter selection in regions without in situ gauge networks, concluding that multi-point parameter selection is more robust than single-point selection and can yield reliable results nearly independent of observation frequency.
WATER RESOURCES RESEARCH
(2021)
Article
Mathematics, Interdisciplinary Applications
Miglena N. Koleva, Lubin G. Vulkov
Summary: This paper discusses the simultaneous estimation of coefficients and initial conditions for model fractional parabolic systems of porous media. It reduces the estimation problem to the minimization of a least-squares cost functional and utilizes pressure information at a finite number of space-time points. The Frechet gradient of the cost functional is derived and the application of the conjugate gradient method for numerical parameter estimation is discussed. Computational results with noise-free and noisy data demonstrate the efficiency and accuracy of the proposed algorithm.
FRACTAL AND FRACTIONAL
(2023)
Article
Engineering, Environmental
Thomas Krumpolc, D. W. Trahan, D. A. Hickman, L. T. Biegler
Summary: Applications of fixed-effects models for kinetic parameter estimation assume independence among batches, but biased residuals often exist in multiple longitudinal batch experiments with time series data. Nonlinear mixed-effects models provide an alternative approach to address the two types of random experimental variation resulting from longitudinal experiments: measurement error for each data point and random batch-to-batch variation. In our case study, implementing a mixed-effects model using nonlinear programming for a batch reactor system yields parameter estimates with less bias compared to a fixed-effects model. Additionally, the Bayesian notion of probability shares is applied to discriminate between several candidate mixed-effects models, demonstrating the ability to elucidate additional model information when fixed-effects models are inappropriate.
CHEMICAL ENGINEERING JOURNAL
(2022)
Article
Mathematics
Khizer Mehmood, Naveed Ishtiaq Chaudhary, Zeshan Aslam Khan, Khalid Mehmood Cheema, Muhammad Asif Zahoor Raja, Ahmad H. Milyani, Abdullah Ahmed Azhari
Summary: This study investigates the parameter optimization of the nonlinear Hammerstein model using the abilities of the marine predator algorithm (MPA) and the key term separation technique. The accuracy and robustness of the optimization scheme for nonlinear Hammerstein model identification are verified through a detailed analysis of MPA.
Article
Engineering, Multidisciplinary
M. Khodabandeh, A. Mohammad-Shahri
Article
Engineering, Multidisciplinary
Mehdi Fatan, Mohammad Reza Daliri, Alireza Mohammad Shahri
Article
Engineering, Aerospace
Hamid Shokri-Ghaleh, Alireza Alfi
Article
Engineering, Mechanical
H. Shokri-Ghaleh, A. Alfi
NONLINEAR DYNAMICS
(2014)
Review
Computer Science, Interdisciplinary Applications
Farshid Foroutan, S. M. Mousavi Gazafrudi, Hamid Shokri-Ghaleh
Summary: This study introduces the concept of Green Hybrid Traction Power Supply Substation (GHTPS) that utilizes renewable energy resources to meet the demand of traction substations. A comparative study on different optimization methods is conducted to determine the optimal size, and a sensitivity analysis indicates the potential future economic competitiveness of renewable energies.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2021)
Article
Automation & Control Systems
Hamid Shokri-Ghaleh, Soheil Ganjefar, Alireza Mohammad Shahri
Summary: This study proposes a robust iterative learning control scheme for linear continuous-time systems with input delay uncertainties using the internal model control structure in the frequency domain. Sufficient conditions are derived to ensure boundedness and monotonic convergence of the tracking error expectation and variance under uncertainties in reference trajectory, initial conditions, and disturbances. Illustrative examples are provided to demonstrate the effectiveness of the proposed method.
IET CONTROL THEORY AND APPLICATIONS
(2021)
Article
Automation & Control Systems
Hamid Shokri-Ghaleh, Soheil Ganjefar, Alireza Mohammad Shahri
Summary: This study extends the problem of robust iterative learning control to time-delay systems and considers the non-repetitive uncertainties in plant dynamic, external disturbances, initial conditions, reference trajectory, and time-delay. By utilizing the proposed ILC scheme and conducting frequency domain analysis, it is demonstrated that both monotonic convergence and boundedness of the expected tracking error can be achieved when the non-repetitiveness of uncertainties is taken into account.
IET CONTROL THEORY AND APPLICATIONS
(2023)
Article
Automation & Control Systems
Hamid Shokri-Ghaleh, Soheil Ganjefar, Alireza Mohammad Shahri
Summary: This study addresses the unresolved problem of robust iterative learning control (ILC) design in batch processes with uncertain time-delay and repetitive nature. It removes the conventional assumptions of cycle-invariant uncertainties and considers the variation of all existing uncertainties from a random point of view. A novel IMC-based ILC structure is proposed based on the ideas of internal model control and indirect ILC. Practical convergence conditions are derived and adjusted to ensure the expected tracking error converges monotonically to zero and achieve an acceptable convergence rate. Simulation tests demonstrate the effectiveness of the proposed design.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
Milad Khorasani, Alireza Mohammad Shahri
2017 5TH RSI INTERNATIONAL CONFERENCE ON ROBOTICS AND MECHATRONICS (ICROM 2017)
(2017)
Proceedings Paper
Engineering, Electrical & Electronic
Amin Basiri, Mohammadreza A. Oskoei, Anahid Basiri, Alireza Mohammad Shahri
2017 5TH RSI INTERNATIONAL CONFERENCE ON ROBOTICS AND MECHATRONICS (ICROM 2017)
(2017)
Proceedings Paper
Engineering, Electrical & Electronic
Abolfazl Khorshidi, Alireza Mohammad Shahri, Mohammadreza Asghari Oskoei
2016 4TH RSI INTERNATIONAL CONFERENCE ON ROBOTICS AND MECHATRONICS (ICROM)
(2016)
Proceedings Paper
Computer Science, Artificial Intelligence
Parichehr Shahidi Sadeghi, Alireza Mohammad Shahri, Mahdi Alinaghizadeh Ardestani, Sina Rezazadeh
2016 ARTIFICIAL INTELLIGENCE AND ROBOTICS (IRANOPEN)
(2016)
Article
Engineering, Multidisciplinary
Sicheng Jiao, Shixiang Wang, Minge Gao, Min Xu
Summary: This paper presents a non-contact method of thickness measurement for thin-walled rotary shell parts based on a chromatic confocal sensor. The method involves using a flip method to obtain surface profiles from both sides of the workpiece, measuring the decentration and tilt errors of the workpiece using a centering system, establishing a unified reference coordinate system, reconstructing the external and internal surface profiles, and calculating the thickness. Experimental results show that the method can accurately measure the thickness of a sapphire spherical shell workpiece and is consistent with measurements of other materials.
Article
Engineering, Multidisciplinary
Rajeev Kumar, Sajal Agarwal, Sarika Pal, Alka Verma, Yogendra Kumar Prajapati
Summary: This study evaluated the performance of a CaF2-Ag-MXene-based surface plasmon resonance (SPR) sensor at different wavelengths. The results showed that the sensor achieved the maximum sensitivity at a wavelength of 532 nm, and higher sensitivities were obtained at shorter wavelengths at the expense of detection accuracy.
Article
Engineering, Multidisciplinary
Attilio Di Nisio, Gregorio Andria, Francesco Adamo, Daniel Lotano, Filippo Attivissimo
Summary: Capacitive sensing is a widely used technique for a variety of applications, including avionics. However, current industry standard Capacitive Level Sensors (CLSs) used in helicopters perform poorly in terms of sensitivity and dynamic characteristics. In this study, novel geometries were explored and three prototypes were built and tested. Experimental validation showed that the new design featuring a helicoidal slit along the external electrode of the cylindrical probe improved sensitivity, response time, and linearity.
Article
Engineering, Multidisciplinary
Kai Yang, Huiqin Wang, Ke Wang, Fengchen Chen
Summary: This paper proposes an effective measurement method for dynamic compaction construction based on time series model, which enables real-time monitoring and measurement of anomalies and important construction parameters through simulating motion state transformation and running time estimation.
Article
Engineering, Multidisciplinary
Hui Fu, Qinghua Song, Jixiang Gong, Liping Jiang, Zhanqiang Liu, Qiang Luan, Hongsheng Wang
Summary: An automatic detection and pixel-level quantification model based on joint Mask R-CNN and TransUNet is developed to accurately evaluate microcrack damage on the grinding surfaces of engineering ceramics. The model is effectively trained on actual micrograph image dataset using a joint training strategy. The proposed model achieves reliable automatic detection and fine segmentation of microcracks, and a skeleton-based quantification model is also proposed to provide comprehensive and precise measurements of microcrack size.
Review
Engineering, Multidisciplinary
Sang Yeob Kim, Da Yun Kwon, Arum Jang, Young K. Ju, Jong-Sub Lee, Seungkwan Hong
Summary: This paper reviews the categorization and applications of UAV sensors in forensic engineering, with a focus on geotechnical, structural, and water infrastructure fields. It discusses the advantages and disadvantages of sensors with different wavelengths and addresses the challenges of current UAV technology and recommendations for further research in forensic engineering.
Article
Engineering, Multidisciplinary
Anton Nunez-Seoane, Joaquin Martinez-Sanchez, Erik Rua, Pedro Arias
Summary: This article compares the use of Mobile Laser Scanners (MLS) and Aerial Laser Scanners (ALS) for digitizing the road environment and detecting road slopes. The study found that ALS data and its corresponding algorithm achieved better detection and delimitation results compared to MLS. Measuring the road from a terrestrial perspective negatively impacted the detection process, while an aerial perspective allowed for scanning of the entire slope structure.
Article
Engineering, Multidisciplinary
Nur Luqman Saleh, Aduwati Sali, Raja Syamsul Azmir Raja Abdullah, Sharifah M. Syed Ahmad, Jiun Terng Liew, Fazirulhisyam Hashim, Fairuz Abdullah, Nur Emileen Abdul Rashid
Summary: This study introduces an enhanced signal processing scheme for detecting mouth-click signals used by blind individuals. By utilizing additional band-pass filtering and other steps, the detection accuracy is improved. Experimental results using artificial signal data showed a 100% success rate in detecting obstacles. The emerging concepts in this research are expected to benefit radar and sonar system applications.
Article
Engineering, Multidisciplinary
Jiqiang Tang, Shengjie Qiu, Lu Zhang, Jinji Sun, Xinxiu Zhou
Summary: This paper studies the magnetic noise level of a compact high-performance magnetically shielded room (MSR) under different operational conditions and establishes a quantitative model for magnetic noise calculation. Verification experiments show the effectiveness of the proposed method.
Review
Engineering, Multidisciplinary
Krzysztof Bartnik, Marcin Koba, Mateusz Smietana
Summary: The demand for miniaturized sensors in the biomedical industry is increasing, and optical fiber sensors (OFSs) are gaining popularity due to their small size, flexibility, and biocompatibility. This study reviews various OFS designs tested in vivo and identifies future perspectives and challenges for OFS technology development from a user perspective.
Article
Engineering, Multidisciplinary
Yue Wang, Lei Zhou, Zihao Li, Jun Wang, Xuangou Wu, Xiangjun Wang, Lei Hu
Summary: This paper presents a 3-D reconstruction method for dynamic stereo vision of metal surface based on line structured light, overcoming the limitation of the measurement range of static stereo vision. The proposed method uses joint calibration and global optimization to accurately reconstruct the 3-D coordinates of the line structured light fringe, improving the reconstruction accuracy.
Article
Engineering, Multidisciplinary
Jaafar Alsalaet
Summary: Order tracking analysis is an effective tool for machinery fault diagnosis and operational modal analysis. This study presents a new formulation for the data equation of the second-generation Vold-Kalman filter, using separated cosine and sine kernels to minimize error and provide smoother envelopes. The proposed method achieves high accuracy even with small weighting factors.
Article
Engineering, Multidisciplinary
Tonglei Cao, Kechen Song, Likun Xu, Hu Feng, Yunhui Yan, Jingbo Guo
Summary: This study constructs a high-resolution dataset for surface defects in ceramic tiles and addresses the scale and quantity differences in defect distribution. An improved approach is proposed by introducing a content-aware feature recombination method and a dynamic attention mechanism. Experimental results demonstrate the superior accuracy and efficiency of the proposed method.
Article
Engineering, Multidisciplinary
Qinghong Fu, Yunxi Lou, Jianghui Deng, Xin Qiu, Xianhua Chen
Summary: Measurement and quantitative characterization of aging-induced gradient properties is crucial for accurate analysis and design of asphalt pavement. This research proposes the composite specimen method to obtain asphalt binders at different depths within the mixture and uses dynamic shear rheometer tests to measure aging-induced gradient properties and reveal internal mechanisms. G* master curves are constructed to investigate gradient aging effects in a wide range. The study finds that the composite specimen method can effectively restore the boundary conditions and that it is feasible to study gradient aging characteristics within the asphalt mixture. The study also observes variations in G* and delta values and the depth range of gradient aging effects for different aging levels.
Article
Engineering, Multidisciplinary
Min Li, Kai Wei, Tianhe Xu, Yali Shi, Dixing Wang
Summary: Due to the limitations of ground monitoring stations in China for the BDS, the accuracy of BDS Medium Earth Orbit (MEO) satellite orbits can be influenced. To overcome this, low Earth orbit (LEO) satellites can be used as additional monitoring stations. In this study, data from two LEO satellites were collected to improve the precise orbit determination of the BDS. By comparing the results with GPS and BDS-2/3 solutions, it was found that including the LEO satellites significantly improved the accuracy of GPS and BDS-2/3 orbits.
