Article
Automation & Control Systems
Kun Zhu, Chengpu Yu, Yiming Wan
Summary: This paper proposes a new recursive least squares (RLS) identification algorithm with variable-direction forgetting (VDF) for multi-output systems, aiming to improve parameter estimation performance under non-persistent excitation. The algorithm performs oblique projection decomposition of the information matrix, leading to a lower and upper bounded information matrix even without persistent excitation. Comparative analysis with a recent VDF algorithm shows the efficacy and advantage of the proposed algorithm in handling non-persistent excitation.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Automation & Control Systems
Die Gan, Zhixin Liu
Summary: This paper addresses the problem of distributed sparse identification over wireless sensor networks, where all sensors collaborate to estimate the unknown sparse parameter vector of stochastic dynamic systems using local information from neighbors. A distributed sparse least squares algorithm is proposed by minimizing a local information criterion combining accumulative local estimation error and L-1 regularization term. The upper bound of the algorithm's estimation error is derived, and the set convergence of zero elements is achieved by designing suitable adaptive weighting coefficients based on local observations. The proposed distributed algorithm demonstrates effective cooperation among sensors and can be applied to stochastic feedback systems without relying on independence assumptions of regression signals commonly used in existing literature.
Article
Engineering, Mechanical
Yang-Rui Li, Chao-Chung Peng, Jer-Nan Juang
Summary: This paper focuses on the parameter identification of nonlinear mechanical dynamic systems. It proposes a second-order integral method and an optimal excitation trajectory to obtain accurate parameter estimates. Additionally, it introduces a finite Fourier series for optimal estimation of position, velocity, and acceleration, improving the precision of parameter identification.
NONLINEAR DYNAMICS
(2023)
Article
Mathematics
Luis Alberto Cantera-Cantera, Ruben Garrido, Luis Luna, Cristobal Vargas-Jarillo, Erick Asiain
Summary: This work presents the parameter identification of servo systems using the least squares of orthogonal distances method. The parameter identification problem is reformulated as data fitting to a plane, corresponding to a nonlinear minimization problem. Three servo system models with different numbers of parameters were experimentally identified using classic least squares and least squares of orthogonal distances. The results showed that the least squares of orthogonal distances method produced consistent estimates without the need for the classic persistency-of-excitation condition, and the parameter estimates obtained from this method achieved the best tracking performance when used in trajectory-tracking controller computation.
Article
Engineering, Mechanical
Xinghao Du, Jinhao Meng, Kailong Liu, Yingmin Zhang, Shunli Wang, Jichang Peng, Tianqi Liu
Summary: This paper proposes a co-estimation framework utilizing the advantages of both recursive least squares (RLS) and recursive total least squares (RTLS) for a higher parameter identification performance of the battery equivalent circuit model (ECM). RLS quickly converges by updating the parameters along the gradient of the cost function, while RTLS is applied to attenuate the noise effect once the parameters have converged. Both simulation and experimental results show that the proposed method has good accuracy, a fast convergence rate, and robustness against noise corruption.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2023)
Article
Acoustics
Miaomiao Lin, Changming Cheng, Zhike Peng, Xingjian Dong, Yegao Qu, Guang Meng
Summary: This paper proposes a novel nonlinear dynamical system identification method based on the sparse regression algorithm and the separable least squares method, effectively transforming the identification of nonlinear dynamical systems into a separable least squares problem using Duhamel's integral. The method leverages separate identification of linear subsystem parameters and nonlinear coefficients, utilizing the sparse regression algorithm to select contributing nonlinear components and a de-noise method based on RKHS. Numerical simulations and dynamic experiments validate the effectiveness of the proposed method for nonlinear dynamical systems.
JOURNAL OF SOUND AND VIBRATION
(2021)
Article
Mathematics
Artur I. Karimov, Ekaterina Kopets, Erivelton G. Nepomuceno, Denis Butusov
Summary: This paper investigates the problem of parametric identification of a piece-wise linear mechanical system described by ordinary differential equations, using a novel approach to improve identification accuracy. By using acceleration and velocity as the main independent variables, and modifying the iteratively reweighted least squares method, classification errors were reduced and system identification accuracy was enhanced.
Article
Food Science & Technology
Ong Pauline, Hsin-Tze Chang, I-Lin Tsai, Che-Hsuan Lin, Suming Chen, Yung-Kun Chuang
Summary: The study used NIR spectroscopy combined with hybrid variable selection to rapidly and non-destructively assess histamine levels in mackerel. By optimizing the variables, the best model for prediction accuracy was obtained, outperforming traditional calibration models.
LWT-FOOD SCIENCE AND TECHNOLOGY
(2021)
Article
Automation & Control Systems
Horia Mania, Michael Jordan, Benjamin Recht
Summary: In this paper, we study a class of nonlinear dynamical systems with feature embeddings and propose an active learning approach that can estimate such systems at a parametric rate in finite time.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)
Article
Mathematics, Applied
Dinh Nho Hao, Akhtar A. Khan, Simeon Reich
Summary: This study focuses on establishing new convergence rates for nonlinear inverse problems, applicable to a wide array of practical models without the need for any smallness condition.
JOURNAL OF NONLINEAR AND VARIATIONAL ANALYSIS
(2023)
Article
Chemistry, Analytical
Qiankai Wang, Wen Jing, Xiang Liu, Bo Huang, Ge Jiang
Summary: In this paper, a novel semi-analytical waveform model and signal processing method for SAR altimeters with vertical movement and large antenna mis-pointing angles are proposed. The proposed model achieves high applicability and accuracy in waveform re-tracking, as shown by the evaluation using simulated data.
Article
Engineering, Marine
Shiyang Li, Tongtong Wang, Guoyuan Li, Houxiang Zhang
Summary: This paper proposes a ship maneuvering model optimization method that simplifies the model identification process by reducing the requirement on data excitation. The preliminary parameters of the ship mathematical model are identified using the least squares method, and correlation analysis is used to determine the correlation among the parameters and categorize them into groups based on their correlation. Sensitivity analysis is employed to detect the influence level of parameters and select the more critical ones. Based on the results of these analyses, a standard is established to simplify the ship maneuvering mathematical model. The experiment results verify that the simplified model outperforms the complete model when identifying with less excitation data.
Article
Automation & Control Systems
Arnaud Munch, Emmanuel Trelat
Summary: This article presents a constructive proof and algorithm for the exact controllability of semilinear 1D wave equations. The proposed least-squares algorithm yields an explicit sequence converging to a controlled solution for the equation.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2022)
Article
Engineering, Electrical & Electronic
Mouncef El Marghichi, Azeddine Loulijat, Issam El Hantati
Summary: This article proposes a battery parameter update method based on the variable recursive least squares algorithm to improve the accuracy of battery state-of-charge estimation. Comparisons with other methods reveal that the VRLS algorithm outperforms others in terms of predictive performance indicators.
ELECTRICAL ENGINEERING
(2023)
Article
Mathematics
Andreas Tataris, Tristan van Leeuwen
Summary: In this paper, we study the inverse scattering problem for a Schrodinger operator related to a static wave operator with variable velocity using the GLM integral equation. We assume the presence of noisy scattering data and derive a stability estimate for the error of the solution of the GLM integral equation by showing the invertibility of the GLM operator between suitable function spaces. To regularize the problem, we formulate a variational total least squares problem and prove the existence of minimizers under certain regularity assumptions. Finally, we compute the regularized solution of the GLM equation numerically using the total least squares method in a discrete sense.
Article
Construction & Building Technology
Parth Bansal, Steven Jige Quan
Summary: This study investigates the relationship between urban form and canopy layer urban heat island (CUHI) using a relatively large sample of microclimate sensors in Seoul, Korea. The study compares different statistical models and finds that the spatially explicit gradient boosting decision tree (GBDT) model has the highest accuracy. The study also shows that the effect of urban form on CUHI varies at different time instances during the day. These findings provide valuable insights for planners to understand the complexity of urban climate and reduce CUHI magnitude.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Miaomiao Liu, Salah Almazmumi, Pinlu Cao, Carlos Jimenez-bescos, John Kaiser Calautit
Summary: Windcatchers provide effective low-energy ventilation and summer passive cooling in temperate climates. However, their use in winter is limited due to significant ventilation heat loss and potential discomfort. This study evaluates the applicability of windcatchers in low-temperature conditions, highlighting the need for control strategies to reduce over-ventilation and the integration of heat recovery or thermal storage to enhance winter thermal conditions.
BUILDING AND ENVIRONMENT
(2024)
Review
Construction & Building Technology
Behrouz Nourozi, Aneta Wierzbicka, Runming Yao, Sasan Sadrizadeh
Summary: This article presents a systematic review of ventilation solutions in hospital wards, aiming to enhance pathogen removal performance while maintaining patient and healthcare staff comfort using air-cleaning techniques. The study reveals the importance of proper ventilation systems in reducing infection risk and adverse effects of cross-contamination.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Zhen Yang, Weirong Zhang, Hongkai Liu, Weijia Zhang, Mingyuan Qin
Summary: The study examines the influence of personalized local heating on the thermal comfort of occupants in old residential buildings. The findings reveal that personalized local heating can increase the overall thermal sensation of occupants, but only a few methods are effective in enhancing thermal comfort. The chosen heating methods and background temperature affect the participants' selection of heating parts.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Hong Cheng, Dan Norback, Huilin Zhang, Liu Yang, Baizhan Li, Yinping Zhang, Zhuohui Zhao, Qihong Deng, Chen Huang, Xu Yang, Chan Lu, Hua Qian, Tingting Wang, Ling Zhang, Wei Yu, Juan Wang, Xin Zhang
Summary: The home environment and sick building syndrome (SBS) symptoms in five southern Chinese cities have been studied over time. The study found a decrease in asthma prevalence and an increase in allergic rhinitis. Cockroaches, rats, mice, mosquitoes or flies were identified as consistent biological risk factors for SBS symptoms, while redecoration, buying new furniture, and traffic air pollution were identified as other risk factors.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Chaojie Xing, Zhengtao Ai, Zhiwei Liu, Cheuk Ming Mak, Hai Ming Wong
Summary: This study experimentally investigated the emission characteristics of droplets around the mouth during dental treatments. The results showed that the peak mass fraction of droplets occurs within the size range of 20 μm to 100 μm, and droplets with a diameter less than 200 μm account for over 80% of the mass fraction. The dominant emission direction of droplets is towards the dummy's head and chest, forming an approximately cone shape.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Zhijian Liu, Zhe Han, Lina Hu, Chenxing Hu, Rui Rong
Summary: This study compared the effects of different respiratory behaviors on the distribution of aerosols in a ward and the risk of infection for healthcare workers using numerical simulation. It was found that talking in the ward significantly increased aerosol concentrations, particularly short periods of talking. Wards designed with side-supply ventilation had lower overall infection risk. Talking alternately between healthcare workers and patients slightly extended the impact time of aerosols.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Yan Yan, Mengyuan Kang, Haodong Zhang, Zhiwei Lian, Xiaojun Fan, Chandra Sekhar, Pawel Wargocki, Li Lan
Summary: In a high-density city, opening windows for sleep may lead to increased indoor temperature, higher PM2.5 concentration, and noise disturbance, which can negatively impact sleep quality.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Yan Bai, Liang Liu, Kai Liu, Shuai Yu, Yifan Shen, Di Sun
Summary: This study developed a non-intrusive personal thermal comfort model using machine learning techniques combined with infrared facial recognition. The results showed that the ensemble learning models perform better than traditional models, and the broad learning model has a higher prediction precision with lower computational complexity and faster training speed compared to deep neural networks. The findings provide a reference for optimizing building thermal environments.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Yue Lei, Zeynep Duygu Tekler, Sicheng Zhan, Clayton Miller, Adrian Chong
Summary: Mixed-mode ventilation is a promising solution for achieving energy-efficient and comfortable indoor environments. This study found that occupants can thermally adapt when switching between natural ventilation (NV) and air-conditioning (AC) modes within the same day, with the adaptation process stabilizing between 35 to 45 minutes after the mode switch. These findings are important for optimizing thermal comfort in mixed-mode controls, considering the dynamic nature of thermal adaptation.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Nan Mo, Jie Han, Yingde Yin, Yelin Zhang
Summary: This study develops a method based on the LCZ framework for a comprehensive evaluation of urban-scale heat island effects, considering the impact of geographic factors on LST. The results show that Guilin's geomorphological conditions lead to abnormal heat island effects during winter, and the cooling effects of mountains and water bodies vary seasonally in different built areas, with LCZ 2 exhibiting the strongest cooling effect.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Tunga Salthammer
Summary: Monitoring the potential formaldehyde emission of wood-based materials through test chamber investigations has significantly contributed to reducing indoor formaldehyde concentrations. However, the different methodologies used in these procedures prevent direct result comparison. Empirical models for converting formaldehyde steady-state concentrations based on temperature, humidity, air change rate, and loading were developed in the 1970s and have been modified to accommodate the development of lower-emitting materials. Formaldehyde emissions from wood-based materials are complex and require nonlinear regression tools for mathematical analysis.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Katarina Stebelova, Katarina Kovacova, Zuzana Dzirbikova, Peter Hanuliak, Tomas Bacigal, Peter Hartman, Andrea Vargova, Jozef Hraska
Summary: This study investigated the impact of reduced short-wavelength light on the hormone melatonin metabolite 6-sulfatoxymelatonin (u-sMEL) and examined the association between previous day's light exposure and u-sMEL. It was found that reducing short-wavelength light during the day did not change the concentration of u-sMEL. Personal photopic illuminance was positively correlated with u-sMEL in the reference week. The illuminance had a significant impact on u-sMEL, as shown by the evaluation of the mean of all three urine samples. However, this correlation was not found in the experimental week.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Ruoxin Xiong, Ying Shi, Haoming Jing, Wei Liang, Yorie Nakahira, Pingbo Tang
Summary: This study proposes a data-model integration method to identify and calibrate uncertainties in machine learning models, leading to improved thermal perception predictions. The method utilizes the Multidimensional Association Rule Mining algorithm to identify biased human responses and enhances prediction accuracy and reliability. The study also evaluates different calibration techniques and discovers their potential in enhancing prediction reliability.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Beichao Hu, Zeda Yin, Abderrachid Hamrani, Arturo Leon, Dwayne McDaniel
Summary: This paper introduces an innovative super-resolution approach to model the air flow and temperature field in the cold aisle of a data center. The proposed method reconstructs a high-fidelity flow field by using a low-fidelity flow field, significantly reducing the computational time and enabling real-time prediction.
BUILDING AND ENVIRONMENT
(2024)
