Article
Energy & Fuels
Yali Cheng, Fanfei Min, Hui Li, Jun Chen, Xiaoheng Fu
Summary: This study investigated the effects of reagent interaction on the performance of froth using a self-made test device. The results showed that different collectors and frothers had an impact on the foaming and stability of the froth, and the concentration of the reagent also affected the maximum foam height and half-life of the three-phase froth.
Article
Engineering, Chemical
Yueyi Pan, Ghislain Bournival, Seher Ata
Summary: The study shows that potassium amyl xanthate and sodium hydrosulphide can significantly increase bubble lifetime at the air-liquid interface, while helping to inhibit bubble coalescence. Additionally, xanthates and NaHS targeting the solid-liquid interface also affect the size and stability of bubbles.
MINERALS ENGINEERING
(2021)
Article
Engineering, Chemical
A. Jahedsaravani, M. Massinaei, M. Zarie
Summary: Bubble size and froth velocity are critical characteristics for evaluating and controlling flotation systems. Traditional image processing algorithms have limitations in accurately measuring these characteristics, while pre-trained convolutional neural networks offer a more reliable and efficient alternative.
MINERALS ENGINEERING
(2023)
Article
Engineering, Chemical
S. J. Neethling, D. Mesa, P. R. Brito-Parada
Summary: In this paper, a model for froth recovery that incorporates the effects of detachment and subsequent transport of particles is presented. The model is compared to experimental results and shown to accurately describe the evolution of froth recovery behavior under decreasing froth stability.
MINERALS ENGINEERING
(2024)
Review
Chemistry, Physical
Min Uk Jung, Yeo Cheon Kim, Ghislain Bournival, Seher Ata
Summary: The depletion of high-grade and coarse-grain ores has increased the demand for efficient separation technologies for low-grade and fine-grain ores. Conventional froth flotation techniques are not adequate for recovering fine and ultrafine particles, leading to the study of microbubble generation methods. This review focuses on scalable methods for industrial applications, discussing their mechanisms, characteristics, limitations, and potential enhancements.
ADVANCES IN COLLOID AND INTERFACE SCIENCE
(2023)
Article
Metallurgy & Metallurgical Engineering
C. Bhondayi
Summary: This paper reviews methods for measuring bubble sizes in mineral froth flotation, including industrial machine vision and traditional photographic methods. It also introduces new methods for overcoming limitations of transparent systems and measuring bubble sizes within the froth/foam. However, further testing is needed for these methods.
MINERAL PROCESSING AND EXTRACTIVE METALLURGY REVIEW
(2022)
Article
Engineering, Chemical
Diego Mesa, Paulina Quintanilla, Francisco Reyes
Summary: This article presents an open-source software, Bubble Analyser, for processing bubble images and quantifying bubble size distribution. The software includes a standard image processing algorithm with less than 5% error in calculating the Sauter mean diameter. Additionally, it supports integration of new segmentation algorithms to expand its capabilities and foster research collaboration.
MINERALS ENGINEERING
(2022)
Article
Engineering, Chemical
Paulina Quintanilla, Stephen J. Neethling, Daniel Navia, Pablo R. Brito-Parada
Summary: This study describes the development of a dynamic flotation model suitable for model predictive control, incorporating equations that describe the physics of flotation froths. The model proposed in this study includes important variables related to froth stability, and simulations showed good adaptability to changes in important variables for control. Sensitivity analysis revealed the significant impact of parameter estimation accuracy on prediction accuracy, with two highly sensitive parameters identified.
MINERALS ENGINEERING
(2021)
Article
Engineering, Chemical
Paulina Quintanilla, Daniel Navia, Stephen J. Neethling, Pablo R. Brito-Parada
Summary: This paper presents the development of an economic model predictive control (E-MPC) strategy that utilizes a dynamic flotation model to improve the performance of froth flotation systems. By incorporating air recovery dynamics and concentrate grade dynamics, the E-MPC strategy achieved significant improvements in metallurgical recovery while maintaining the specified grade. The strategy also introduced a dynamic variable, air recovery, which offers great potential for performance improvement in existing flotation systems.
MINERALS ENGINEERING
(2023)
Article
Automation & Control Systems
Jin Zhang, Zhaohui Tang, Yongfang Xie, Mingxi Ai, Guoyong Zhang, Weihua Gui
Summary: Efforts are devoted to enabling data-driven process models with incremental learning ability. A novel incremental learning method is proposed for process model updating. Experimental results demonstrate that the newly developed adaptive process model can accommodate new process excitation patterns and preserve its performance on old patterns.
Article
Engineering, Chemical
Paulina Quintanilla, Stephen J. Neethling, Diego Mesa, Daniel Navia, Pablo R. Brito-Parada
Summary: The study established a dynamic model of the flotation process suitable for control purposes, conducted sensitivity analysis, parameter fitting, and simulations. Experimental data and model calibrations demonstrated the model's accurate predictions of important flotation variables, validating its reliability and potential for future control strategies.
MINERALS ENGINEERING
(2021)
Article
Engineering, Chemical
Behzad Karkari Gharehchobogh, Ziaddin Daie Kuzekanani, Jafar Sobhi, Abdolhamid Moallemi Khiavi
Summary: This paper presents a real-time image analysis system based on Mask R-CNN for flotation froth segmentation and bubble size measurement. The system can effectively detect bubbles, measure the size distribution of the bubbles, and detect non-loaded bubbles in the froth. Application of the classical image segmentation methods showed considerable errors in bubble identification and sizing.
MINERALS ENGINEERING
(2023)
Review
Engineering, Chemical
Sayed Janishar Anzoom, Ghislain Bournival, Seher Ata
Summary: This review discusses the benefits and challenges of coarse particle flotation, as well as recent developments in improving the process. Coarse particle flotation has various applications and offers advantages in technical, economic, and sustainability aspects. However, it also faces challenges such as particle detachment, transfer between phases, and persistence in the froth phase. Technological advancements, such as fluidized-bed flotation and processes enhancing bubble-particle attachment, have shown promising results in efficiently recovering larger particles.
MINERALS ENGINEERING
(2024)
Article
Engineering, Chemical
J. Yianatos, P. Vallejos
Summary: In this paper, the metallurgical performance of flotation cells was evaluated based on the cell volume and operating variables. The results showed that increasing the cell volume leads to a higher bubble loading, and the use of internal launders expands the range of operating conditions.
MINERALS ENGINEERING
(2022)
Article
Engineering, Chemical
Hangtao Liu, Ruibo Jia, Zhiping Wen, Jinhe Pan, Lei Zhang, Shulan Shi, Changchun Zhou
Summary: This study proposes a new working condition recognition method based on nonsubsampled contourlet transform (NSCT) to accurately identify flotation conditions. The method extracts multiscale features from enhanced froth images using NSCT and achieves the highest classification accuracy in actual froth images.
MINERALS ENGINEERING
(2023)
Article
Automation & Control Systems
Keke Huang, Yiming Wu, Chen Wang, Yongfang Xie, Chunhua Yang, Weihua Gui
Summary: A semisupervised robust projective and discriminative dictionary learning method is proposed to address the complexity of real industrial process data, characterized by multimode, high dimensional, corrupted, and less labeled data. The method introduces a semisupervised strategy to label unsupervised training data, utilizes low-rank and sparse features for data decomposition, and extracts features of clean data through a simultaneously projective and discriminative model. The efficiency of this hybrid framework is demonstrated through synthetic examples and real industrial process cases.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Automation & Control Systems
Keke Huang, Yiming Wu, Cheng Long, Hongquan Ji, Bei Sun, Xiaofang Chen, Chunhua Yang
Summary: The study introduces an online dictionary learning method that outperforms traditional methods by adapting to time-varying processes, having lower computational complexity, and more reliably resolving issues in principal component analysis.
Article
Automation & Control Systems
Zhenxiang Feng, Yonggang Li, Bei Sun, Chunhua Yang, Hongqiu Zhu, Zhisheng Chen
Summary: The stability of the roasting temperature is crucial for product quality in the zinc roasting process, but controlling the temperature in a large-scale zinc roaster is challenging due to complex process characteristics, fluctuating working conditions, and delayed detection of product quality. A new trend-based event-triggering fuzzy control strategy has been proposed to improve the utilization of information contained in temperature measurements.
JOURNAL OF PROCESS CONTROL
(2021)
Article
Computer Science, Information Systems
Keke Huang, Haofei Wen, Han Liu, Chunhua Yang, Weihua Gui
Summary: Data-driven process monitoring methods rely on geometry constrained dictionary learning to balance reconstructive and discriminative items. Inspired by the manifold method, discriminative sparse coding is employed to identify samples from the same class.
INFORMATION SCIENCES
(2021)
Article
Automation & Control Systems
Xiang Xie, Haiyang Zhang, Xinzhi Liu, Honglei Xu, Xiaodi Li
Summary: This paper studies the input-to-state stabilization problem of nonlinear time-delay systems by proposing a novel event-triggered hybrid controller and using the Lyapunov-Krasovskii method to construct sufficient conditions for input-to-state stability. The obtained criteria are applicable to time-delay systems with various impulsive effects.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Engineering, Electrical & Electronic
Chao Yang, Zhiliang Wu, Tao Peng, Hongqiu Zhu, Chunhua Yang
Summary: In this article, a new method for transient fault diagnosis in high-speed train TDCS is proposed, which can handle TF scenarios with small amplitude, short duration, and energy feature pattern. The research overcomes the ambiguity between transient signals and noise through parameter optimization and energy distribution.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2021)
Article
Computer Science, Artificial Intelligence
Keke Huang, Ke Wei, Yonggang Li, Chunhua Yang
Summary: This paper proposes a distributed dictionary learning algorithm based on the MapReduce framework for process monitoring in industrial systems. The method efficiently extracts useful information from high-dimensional data and improves the effectiveness and robustness of process monitoring for industrial processes.
APPLIED INTELLIGENCE
(2021)
Article
Automation & Control Systems
Xiaofeng Yuan, Lin Li, Yuri A. W. Shardt, Yalin Wang, Chunhua Yang
Summary: An LSTM network with spatiotemporal attention is proposed for soft sensor modeling in industrial processes, improving prediction performance by identifying important input variables related to the quality variable and discovering quality-related hidden states adaptively.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Green & Sustainable Science & Technology
Gang Lin, Shaoli Wang, Conghua Lin, Linshan Bu, Honglei Xu
Summary: This research proposes a public transport criteria matrix AHP model to assess the performance of public transport networks and provides specific evaluation criteria. Through this model, local public transport authorities can monitor the performance of public transport networks and provide improvement recommendations.
Article
Computer Science, Information Systems
Jing Huang, Wei Xiong, Honglei Xu, Jingyu Zhang, Xiaofeng Yu
Summary: The study focuses on the quality of agricultural product drying, designing an expert system of drying schemes based on fuzzy algorithm and BP neural network. Through experiments, it is verified that the system's reasoning ability can gradually improve.
JOURNAL OF INTERNET TECHNOLOGY
(2021)
Article
Energy & Fuels
Gang Lin, Honglei Xu, Shaoli Wang, Conghua Lin, Chenyu Huang
Summary: This study proposes an optimization approach to improve the performance of public transportation networks by combining multiple criteria evaluation and multi-objective programming. The approach uses analytic hierarchy process to calculate system weights and incorporates multiple aspiration levels for goal selection. The study demonstrates the effectiveness of the approach in optimizing public transportation networks in different scenarios.
Article
Mathematics
Manlika Ratchagit, Honglei Xu
Summary: This paper proposes a new linear combination model that predicts the closing prices on multivariate financial data sets. The model combines two delays of deep learning methods using differential evolution weights. Experimental results demonstrate that this approach outperforms individual models and state-of-the-art combination methods in terms of forecast accuracy.
Review
Construction & Building Technology
Junxiang Zhu, Heap-Yih Chong, Hongwei Zhao, Jeremy Wu, Yi Tan, Honglei Xu
Summary: This paper systematically investigates the applications of graph-based technologies, RDF and LPG, in BIM/GIS data integration. The findings suggest that an LPG-based graph database is suitable for data query and analysis applications, while RDF is more suitable for linking and sharing data applications. Therefore, an LPG-based graph database is proposed for BIM/GIS data integration.
Article
Engineering, Multidisciplinary
Wucheng Zi, Jiayu Zhou, Honglei Xu, Guodong Li, Gang Lin
Summary: Agricultural cooperatives in China have developed rapidly under the farmland transfer policy, playing a significant role in the new operation pattern of fresh agricultural product supply chains. An appropriate relational contract can improve freshness and increase profit in a three-level supply chain, but cannot ensure its stability completely. Government subsidy policies can enhance the stability of fresh agricultural product supply chains by providing protection price contracts and cold chain facility subsidies.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2021)
Article
Computer Science, Artificial Intelligence
Yichi Zhang, Chunhua Yang, Keke Huang, Marko Jusup, Zhen Wang, Xuelong Li
Summary: The paper discusses the fundamental problem of reconstructing complex networks from observed data and proposes a novel method that combines the alternating direction method of multipliers and clustering algorithm to overcome the drawbacks of compressive sensing in network reconstruction. Experimental results demonstrate the accuracy and robustness of the proposed method.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
(2021)
Article
Automation & Control Systems
Subhashis Nandy
Summary: This research focuses on the design and stability analysis of nonlinear controllers for an electrically driven marine cycloidal propeller, along with estimating various parameters using the Extended Kalman Filter. The controller is defined using an efficient physics-based model and is able to accurately process multiple control signals. The robustness of the controller is assessed using Monte Carlo simulation, and its performance is evaluated through validation investigations.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Lucas C. Borin, Guilherme Hollweg, Caio R. D. Osorio, Fernanda M. Carnielutti, Ricardo C. L. F. Oliveira, Vinicius F. Montagner
Summary: This work presents a new automated test-driven design procedure for robust and optimized current controllers applied to LCL-filtered grid-tied inverters. The design of control gains is guided by high-fidelity simulations and particle swarm optimization algorithm, considering various normal and abnormal operating conditions. The proposed design ensures superior performance compared with other current control designs.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Wei He, Xiang Wang, Mohammad Masoud Namazi, Wangping Zhou, Josep M. Guerrero
Summary: The main objective of this paper is to develop a reduced-order adaptive state observer for a large class of DC-DC converters with constant power load, in order to estimate their unavailable states and unknown parameter and achieve an output feedback control scheme. The observer is designed using a generalized parameter estimation based observer technique and dynamic regressor extension and mixing method. The comparison study shows that the observer has the advantage of verifying the observability of the systems for exponential convergence without any extra excitation condition.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Te Zhang, Bo Zhu, Lei Zhang, Qingrui Zhang, Tianjiang Hu
Summary: This paper introduces a control technique called time-varying uncertainty and disturbance estimator (TV-UDE) which extends the classic UDE approach to handle more complicated issues. By combining TV-UDE with a nominal dynamic output-feedback controller, robust control for uncertain second-order attitude control systems without velocity measurements is achieved. Numerical simulations and physical experiments on a 2-DOF AERO attitude helicopter platform demonstrate the effectiveness of the proposed design in reducing steady-state errors and avoiding issues caused by high-gain estimation.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Kanishke Gamagedara, Taeyoung Lee, Murray Snyder
Summary: This paper presents the developments of flight hardware and software for a multirotor unmanned aerial vehicle capable of autonomously taking off and landing on a moving vessel in ocean environments. The flight hardware consists of a general-purpose computing module connected to a low-cost inertial measurement unit, real-time kinematics GPS, motor speed controller, and a camera through a custom-made printed circuit board. The flight software is developed in C++ with multi-threading to execute control, estimation, and communication tasks simultaneously. The proposed flight system is verified through autonomous flight experiments on a research vessel in Chesapeake Bay, utilizing real-time kinematics GPS for relative positioning and vision-based autonomous flight for shipboard launch and landing.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Yun Zhu, Kangkang Zhang, Yucai Zhu, Pengfei Jiang, Jinming Zhou
Summary: In this study, a three-term Dynamic Matrix Control (DMC) algorithm using quadratic programming is developed and compared with the traditional two-term DMC algorithm. Simulation studies and real-life tests show that the three-term DMC algorithm outperforms the two-term DMC algorithm in control effectiveness.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Jayu Kim, Taehoon Lee, Cheol-Joong Kim, Kyongsu Yi
Summary: This paper presents a data-based model predictive control method for a semi-active suspension system. The method utilizes a continuous damping controller and a stiffness controller to improve ride comfort and reduce vehicle pitch motion. Gaussian process regression is also used to compensate for model parameter uncertainties. The algorithm has been verified through computer simulations and vehicle tests, demonstrating its effectiveness and robustness.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Kunpeng Zhang, Jikang Gao, Zongqi Xu, Hui Yang, Ming Jiang, Rui Liu
Summary: A improved dynamic programming model is proposed in this paper for joint operation optimization of virtual coupling of heavy-haul trains. By simultaneously optimizing the headway and energy savings, as well as performing locomotive engineering advisory analysis, significant improvements in train performance can be achieved.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Demian Garcia-Violini, Yerai Pena-Sanchez, Nicolas Faedo, Fernando Bianchi, John V. Ringwood
Summary: This study presents a model invalidation methodology for wave energy converters (WECs) that can effectively handle dynamic uncertainty and external noise. The results indicate that neglecting dynamic uncertainty can lead to overestimation of performance, highlighting the importance of accurate dynamic description for estimating control performance.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Shengyang Lu, Yue Jiang, Xiaojun Xu, Hanxiang Qian, Weijie Zhang
Summary: This paper proposes an adaptive heading tracking control strategy based on wheelbase changes for unmanned ground vehicles (UGVs) with variable configuration. The strategy adjusts the wheelbase according to different working conditions to optimize driving performance. The impact of changing wheelbase on sideslip angle and heading angle is analyzed, and a robust-active disturbance rejection control method is developed to achieve desired front-wheel steering angle. A torque distribution method based on tire load rate and real-time load is applied to enhance longitudinal stability.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Domenico Dona, Basilio Lenzo, Paolo Boscariol, Giulio Rosati
Summary: This paper proposes a new method for designing minimum energy trajectories for servo-actuated systems and demonstrates its accuracy and effectiveness through numerical comparisons and experimental validation.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Haolin Wang, Luyao Zhang, Yao Mao, Qiliang Bao
Summary: This paper proposes a method of transforming the core element of ADRC, ESO, into a novel fuzzy self-tuning observer structure to improve the stability of LOS in the electro-optical tracking system. It effectively solves the conflict between disturbance rejection ability and noise attenuation ability in traditional ESO.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Alejandro Toro-Ossaba, Juan C. Tejada, Santiago Rua, Juan David Nunez, Alejandro Pena
Summary: This work presents the development of a myoelectric Model Reference Adaptive Controller (MRAC) with an Adaptive Kalman Filter for controlling a cable driven soft elbow exoskeleton. The proposed MRAC controller is effective in both passive and active control modes, showing good adaptability and control capabilities.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Mehrad Jaloli, Marzia Cescon
Summary: This study presents an advanced multi-agent reinforcement learning (RL) strategy for personalized glucose regulation, which is shown to improve glucose regulation and reduce the risk of severe hyperglycemia compared to traditional therapy.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Yingming Tian, Kenan Du, Jianfeng Qu, Li Feng, Yi Chai
Summary: This paper investigates the control strategy for PMSM with position sensor fault in railway. A learning observer-based control strategy is proposed, which achieves high-precision estimation of electromotive force and accelerates speed response.
CONTROL ENGINEERING PRACTICE
(2024)
