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arXiv 2022年

作者： Martin, Hector Garcia Radivojevic, Tijana Zucker, Jeremy Bouchard, Kristofer Sustarich, Jess Peisert, Sean Arnold, Dan Hillson, Nathan Babnigg, Gyorgy Marti, Jose Manuel Mungall, Christopher J. Beckham, Gregg T. Waldburger, Lucas Carothers, James Sundaram, ShivShankar Agarwal, Deb Simmons, Blake A. Backman, Tyler Banerjee, Deepanwita Tanjore, Deepti Ramakrishnan, Lavanya Singh, Anup Lawrence Berkeley National Laboratory Biological Systems and Engineering Division BerkeleyCA United States Department of Energy Agile BioFoundry EmeryvilleCA United States Joint BioEnergy Institute EmeryvilleCA United States BCAM Basque Center for Applied Mathematics Bilbao Spain Lawrence Berkeley National Laboratory Scientific Data Division BerkeleyCA United States Helen Wills Neuroscience Institute Redwood Center for Theoretical Neuroscience BerkeleyCA United States Lawrence Berkeley National Laboratory Energy Storage and Distributed Resources Division BerkeleyCA United States University of California Davis Department of Computer Science DavisCA United States Global Security Computing Applications Division Lawrence Livermore National Laboratory LivermoreCA United States Engineering Directorate Lawrence Livermore National Laboratory LivermoreCA United States Center for Bioengineering Lawrence Livermore National Laboratory LivermoreCA United States Department of Chemical Engineering Molecular Engineering & Sciences Institute Center for Synthetic Biology University of Washington SeattleWA United States Biosciences Division Argonne National Laboratory ArgonneIL United States Advanced Biofuels and Bioproducts Process Development Unit Lawrence Berkeley National Laboratory BerkeleyCA United States Biomaterials and Biomanufacturing Division Sandia National Laboratories LivermoreCA United States Earth and Biological Sciences Division Pacific Northwest National Laboratories RichlandWA United States Resources and Enabling Sciences Center National Renewable Energy Laboratory GoldenCO80401 United States Department of Bioengineering University of California BerkeleyCA United States

Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. While there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single target for affecting the incredibly wide repertoire of biological cell behavior. However, the level of investment required for the creation of biological SDLs is only warranted if directed towards solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology. © 2022, CC BY.

关键词： Synthetic biology

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Robust Stabilization of T-S Fuzzy Stochastic Descriptor systems via Integral Sliding Modes

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IEEE TRANSACTIONS ON CYBERNETICS 2018年第9期48卷 2736-2749页

作者： Li, Jinghao Zhang, Qingling Yan, Xing-Gang Spurgeon, Sarah K. Institute of Systems Science State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Instrumentation Control and Embedded Systems Research Group School of Engineering and Digital Arts University of Kent Canterbury U.K. Department of Electronic and Electrical Engineering University College London London U.K.

This paper addresses the robust stabilization problem for T-S fuzzy stochastic descriptor systems using an integral sliding mode control paradigm. A classical integral sliding mode control scheme and a nonparallel distributed compensation (Non-PDC) integral sliding mode control scheme are presented. It is shown that two restrictive assumptions previously adopted developing sliding mode controllers for Takagi-Sugeno (T-S) fuzzy stochastic systems are not required with the proposed framework. A unified framework for sliding mode control of T-S fuzzy systems is formulated. The proposed Non-PDC integral sliding mode control scheme encompasses existing schemes when the previously imposed assumptions hold. Stability of the sliding motion is analyzed and the sliding mode controller is parameterized in terms of the solutions of a set of linear matrix inequalities which facilitates design. The methodology is applied to an inverted pendulum model to validate the effectiveness of the results presented.

关键词： Integral sliding mode control inverted pendulum nonparallel distributed compensation (Non-PDC) robust stabilization Takagi-Sugeno (T-S) fuzzy stochastic descriptor systems

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Synchronization of Chaotic systems: a survey study

Synchronization of Chaotic Systems: a survey study

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Signal, control and Communication (SCC), International Conference on

作者： Noussaiba Griba Faiçal Hamidi Kamel Menighed Boumedyen Boussaid Mohamed Naceur Abdelkrim Lobaratory of Modelling Analysis and Control of Systems (MACS) University of Gabes Gabes Tunisia Petrochemical and Process Engineering Department University August 20 1955-Skikda Skikda Algeria

ISBN: (数字)9781728135960

ISBN: (纸本)9781728135977

This paper gives a survey study of the synchronization of nonlinear systems with chaotic behavior. The chaotic systems studied are Lorenz and Rössler systems. The principal configuration of the synchronization techniques belong to the "Master-Slave" configuration. The techniques widely used to achieve synchronization are "linear active control" and "Nonlinear active control". Numerical simulations are provided to show the effectiveness of these methods.

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Dexterous Manipulation through Imitation Learning: A Survey

arXiv

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arXiv 2025年

作者： An, Shan Meng, Ziyu Tang, Chao Zhou, Yuning Liu, Tengyu Ding, Fangqiang Zhang, Shufang Mu, Yao Song, Ran Zhang, Wei Hou, Zeng-Guang Zhang, Hong School of Electrical and Information Engineering Tianjin University Tianjin300072 China School of Control Science and Engineering Shandong University Jinan250061 China State Key Laboratory of General Artificial Intelligence Beijing100086 China Department of Mechanical and Process Engineering ETH Zurich Zurich8092 Switzerland Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China School of Informatics University of Edinburgh EH8 9AB United Kingdom Department of Computer Science University of Hong Kong 999077 Hong Kong State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China CASIA-MUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology 999078 China

Dexterous manipulation, which refers to the ability of a robotic hand or multi-fingered end-effector to skillfully control, reorient, and manipulate objects through precise, coordinated finger movements and adaptive force modulation, enables complex interactions similar to human hand dexterity. With recent advances in robotics and machine learning, there is a growing demand for these systems to operate in complex and unstructured environments. Traditional model-based approaches struggle to generalize across tasks and object variations due to the high-dimensionality and complex contact dynamics of dexterous manipulation. Although model-free methods such as reinforcement learning (RL) show promise, they require extensive training, large-scale interaction data, and carefully designed rewards for stability and effectiveness. Imitation learning (IL) offers an alternative by allowing robots to acquire dexterous manipulation skills directly from expert demonstrations, capturing fine-grained coordination and contact dynamics while bypassing the need for explicit modeling and large-scale trial-and-error. This survey provides an overview of dexterous manipulation methods based on imitation learning (IL), details recent advances, and addresses key challenges in the field. Additionally, it explores potential research directions to enhance IL-driven dexterous manipulation. Our goal is to offer researchers and practitioners a comprehensive introduction to this rapidly evolving domain. Copyright © 2025, The Authors. All rights reserved.

关键词： Grippers

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controller Parametrization for Offset-free control Using Set-Based Feasibility Methods

Controller Parametrization for Offset-free Control Using Set...

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American control Conference

作者： Petar Andonov Anton Savchenko Rolf Findeisen IMPRS ProEng International Max Planck Research School Magdeburg for Advanced Methods in Process and Systems Engineering Germany Laboratory for Systems Theory and Automatic Control Otto-von-Guericke University Magdeburg Germany

ISBN: (纸本)9781538679012;9781538679265

Achieving a new set point and maintaining it with a desired precision is a common control problem. In case the reference is not fixed, or a priori unknown disturbances are present, the problem is often referred to as offset-free control. We consider the problem of finding suitable controller parameters to obtain an offset-free control up to a certain degree. We tackle the problem in two steps: first, we find controller parameters to steer the controlled system in the neighborhood of the desired reference;second, we identify controller parameters such that the system is robustly controlled invariant with respect to the desired neighborhood of the reference value. For each subproblem we determine the set of parameters that guarantee the desired behavior despite bounded uncertainties. We employ a set-based feasibility formulation which is able to handle nonlinear systems with set constraints. The approach is illustrated with an example.

关键词： controllers reference value Free control Standing Orders parameterization parameters common control

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Corrigendum to "Current challenges of hydrothermal treated wastewater (HTWW) for environmental applications and their perspectives: A review" [Environ. Res. 212 Part D (2022) 113532]

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Environmental research 2024年第PT 3期252卷 119005页

作者： Muhammad Usman Zhijian Shi Nalok Dutta Muhammad Awais Ashraf Bushra Ishfaq Mohamed Gamal El-Din Department of Civil and Environmental Engineering University of Alberta Edmonton AB T6G 2W2 Canada Bioproducts Sciences and Engineering Laboratory (BSEL) Washington State University Tri-Cities Richland WA 99354 United States Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3) Department of Environmental Science and Engineering Fudan University Shanghai 200433 China Shanghai Technical Service Platform for Pollution Control and Resource Utilization of Organic Wastes Shanghai 200438 China. Electronic address: musman4@ualberta.ca. Shanghai Technical Service Platform for Pollution Control and Resource Utilization of Organic Wastes Shanghai 200438 China. Bioproducts Sciences and Engineering Laboratory (BSEL) Washington State University Tri-Cities Richland WA 99354 United States. State Key Laboratory of Multiphase Complex Systems CAS Key Laboratory of Green Process and Engineering Institute of Process Engineering Chinese Academy of Sciences Beijing 100190 China. Food Technology Section Post-harvest Research Center Ayub Agricultural Research Institute Faisalabad Pakistan. Department of Civil and Environmental Engineering University of Alberta Edmonton AB T6G 2W2 Canada. Electronic address: mgamalel-din@ualberta.ca.

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Size-induced axial segregation of binary mixtures in rotating drum of different lengths

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Chemical engineering Science 2025年 316卷

作者： Jielong He Yuelei Wang Liuyimei Yang Jin Xu Qijun Zheng Sida Liu Zongyan Zhou Jiangxi Provincial Key Laboratory of Particle Technology Jiangxi University of Science and Technology Nanchang 330013 China Research Centre for Intelligent Mineral Processing & Metallurgy International Institute for Innovation Jiangxi University of Science and Technology Nanchang 330013 China Ganjiang Innovation Academy Chinese Academy of Sciences Ganzhou 341000 China Centre for Simulation and Modelling of Particulate Systems Monash-Southeast University Joint Research Institute Suzhou 215123 China ARC Research Hub for Smart Process Design and Control Department of Chemical and Biological Engineering Monash University Melbourne VIC 3800 Australia

This study investigates the size-induced axial segregation of binary mixtures in rotating drums, particularly focusing on the effect of drum length. The results indicate that long drums require more time to achieve stable segregation and form more segregation bands. The core region under the free bed surface remains predominantly filled with small particles, indicating that radial segregation occurs simultaneously with the axial segregation. The angle of repose of large particle bands is consistently greater than that of small particle bands, which drives the migration of large particles. Short drums are more sensitive to changes in rotational speed, while long drums with moderate rotational speed promote the formation of segregation bands. The width of small particle bands shows an increasing–decreasing-stabilizing trend with the drum length increasing. An analysis of particle velocities reveals that the characteristics of segregation bands are closely related to the relative velocity difference between large and small particles.

关键词： Binary mixtures

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Real-Time Characterization of Crystal Shape and Size Distribution Based on Moving Window and 3D Imaging in a Stirred Tank

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Journal of Crystallization process and Technology 2019年第2期9卷 13-38页

作者： Rui Zhang Xuezhong Wang Yang Zhang Tao Liu School of Chemistry and Chemical Engineering South China University of Technology Guangzhou China Centre for Pharmaceutical and Crystallization Process Systems Engineering School of Chemical Engineering Beijing Institute of Petrochemical Technology Beijing China Institute of Advanced Control Technology Dalian University of Technology Dalian China

Crystal shape distribution, i.e. the multidimensional size distribution of crystals, is of great importance to their down-stream processing such as in filtration as well as to the end-use properties including the dissolution rate and bioavailability for crystalline pharmaceuticals. engineering crystal shape and shape distribution requires knowledge about the growth behavior of different crystal facets under varied operational conditions e.g. supersaturations. Measurement of the facet growth rates and growth kinetics of static crystals in a crystallizer without stirring has been reported previously. Here attention is given to study on real-time characterization of the 3D facet growth behavior of crystals in a stirred tank where crystals are constantly moving and rotating. The measurement technique is stereo imaging and the crystal shape reconstruction is based on a stereo imaging camera model. By reference to a case study on potash alum crystallization, it is demonstrated that the crystal size and shape distributions (CSSD) of moving and rotating potash alum crystals in the solution can be reconstructed. The moving window approach was used to correlate 3D face growth kinetics with supersaturation (in the range 0.04 - 0.12) given by an ATR FTIR probe. It revealed that {100} is the fastest growing face, leading to a rapid reduction of its area, while the {111} face has the slowest growth rate, reflected in its area continuously getting larger.

关键词： Stereo Imaging Camera Model Crystal Size and Shape Distribution 3D Reconstruction Potash Alum Facet Growth Kinetics

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The effect of thermal radiation on singularities in the dark universe

arXiv

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arXiv 2021年

作者： Brevik, Iver Timoshkin, A.V. Paul, Tanmoy Department of Energy and Process Engineering Norwegian University of Science and Technology TrondheimN-7491 Norway Tomsk State Pedagogical University Kievskaja Street 60 Tomsk634061 Russia International Laboratory of Theoretical Cosmology Tomsk State University of Control Systems and Radio Electronics Lenin Avenue 36 Tomsk634050 Russia Department of Physics Chandernagore College Hooghly712 136 India Department of Theoretical Physics Indian Association for the Cultivation of Science 2A & 2B Raja S.C. Mullick Road Kolkata700 032 India

Cosmological models with an inhomogeneous viscous dark fluid, coupled with dark matter in the Friedmann- Robertson-Walker (FRW) flat universe, are considered. The influence of thermal effects caused by Hawking radiation on the visible horizon is studied, in connection with the classified type I and type III singularities which are known to occur within a finite amount of time. Allowance of thermal effects implies that a transition to a type II singularity can take place, in a finite time. We take into account a bulk viscosity of the dark fluid, observing the equation of state in the case of radiation, and find that there is a qualitative change in the singular universe of type I: it may pass into a singularity of type III, or it may avoid the singularity at all. © 2021, CC BY.

关键词： Equations of state

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Statistical Monitoring of processes with Multiple Operating Modes

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IFAC-PapersOnLine 2019年第1期52卷 635-642页

作者： Ruomu Tan Tian Cong Nina F. Thornhill James R. Ottewill Jerzy Baranowski Centre for Process Systems Engineering Imperial College London London U.K. Department of Automatic Control and Robotics AGH University of Science and Technology Kraków Poland ABB Corporate Research Center Kraków Poland

Varying production regimes and loading conditions on equipment often result in multiple operating modes in process operations. The data recorded from such processes will typically be multimodal in nature leading to challenges in applying standard data-driven process monitoring approaches. Moreover, even if a monitoring approach is able to account for the variability present in a training set comprised of historical process data, in order to be robust and reliable the method will need to account for any new operating modes which might emerge during production. Therefore, it is desirable to have a monitoring algorithm that can both handle data multimodality in off-line training and, when implemented on-line, can actively update in order to incorporate new operating modes. This paper proposes a monitoring framework which combines an unsupervised clustering approach with a kernel-based Multivariate Statistical process Monitoring (MSPM) algorithm. A monitoring model is trained off-line and is subsequently used to detect anomalies on-line. An anomaly might be indicative of either a developing fault or a change in the process to a new operating mode. In the latter case, the monitoring model can be updated to account for the new mode whilst still being able to detect faults under this framework. The advantages of the off-line training procedure relative to a standard kernel-based method are demonstrated via a numerical simulation. Additionally, the monitoring performance in the presence of faults and the capability of updating the model in the presence of new operating modes is demonstrated using a benchmark data set from an experimental pilot plant.

关键词： Fault detection unsupervised learning process monitoring multimode process kernel method

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