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Resilient Event-Triggered Model Predictive control for Adaptive Cruise control Under Sensor Attacks

IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 807-809页

作者： Zhijian Hu Rong Su Kai Zhang Zeyuan Xu Renjie Ma School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore Key Laboratory of Ultra-Precision Intelligent Instrumentation Ministry of Industry and Information Technologyand the Center of Ultra-Precision Optoelectronic Instrument EngineeringHarbin Institute of TechnologyHarbin 150001China Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China Department of Chemical and Biomolecular Engineering National University of SingaporeSingapore 117585Singapore State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150001China IEEE

Dear Editor,This letter addresses the resilient model predictive control(MPC)problems for adaptive cruise control(ACC)systems under sensor *** the light of vulnerabilities of ACC systems to sensor attacks,an intrusion detection mechanism is proposed at the controller side to distinguish abnormal ***,the robust control gains are derived to design the terminal region constraint for MPC.

关键词： Trigger Event constraint

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Experimental and theoretical insights into copper phthalocyanine-based covalent organic frameworks for highly efficien radioactive iodine capture

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Chinese chemical Letters 2022年第7期33卷 3549-3555页

作者： Xuewei Liu Anrui Zhang Ran Ma Bo Wu Tao Wen Yuejie Ai Mingtai Sun Jie Jin Suhua Wang Xiangke Wang MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environment and Chemical EngineeringNorth China Electric Power UniversityBeijing 102206China Guangdong Provincial Key Laboratory of Petrochemical Pollution Process and Control School of Environmental Science and EngineeringGuangdong University of Petrochemical TechnologyMaoming 525000China

Exploring efficient materials for capturing radioactive iodine in nuclear waste is of great significance for the progress of nuclear energy as well as the protection of ecological *** organic frameworks(COFs)have emerged as promising adsorbents because of their predesignable and functionalizable skeleton ***,it remains a grand challenge to achieve large scale preparation of *** this work,we developed a mild and efficient microwave irradiation method instead of the traditional solvothermal method to prepare copper phthalocyanine-based covalent organic frameworks(Cu_(x)Pc-COFs)within only 15 *** nitrogen-rich 1,2,4,5-tetracarbonitrilebenzene(TCNB)was selected as the solely organic ligand to construct copper phthalocyanine-based 2D conjugated *** resultant Cu_(x)Pc-COFs exhibited excellent iodine enrichment with 2.99 g/g for volatile iodine and 492.27 mg/g for iodine-cyclohexane solution,respectively,outperforming that of many porous *** indicated by spectroscopic analysis and DFT calculations,this impressive adsorption performance can be attributed to the charge transfer arising from nitrogen-rich phthalocyanine structures and electron-richπ-conjugated systems with iodine ***,the strong electrostatic interaction between Cu(Ⅱ)on chelate centers and polyiodide anions(I_(x)^(-))also play an important role in the firmly trapping radioactive ***,this study provides a facile and intelligent approach to implement metal-based COFs for the remediation of toxic radioactive iodine.

关键词： Cu_(x)Pc-COFs Microwave Iodine adsorption Charge transfer Electrostatic interaction

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Synthesis and Characterization of Biochar Obtained from Microwave-Assisted Copyrolysis of Torrefied Sawdust and Polystyrene

ACS Sustainable Resource Management

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ACS Sustainable Resource Management 2024年第9期1卷 2074-2085页

作者： Ramesh Potnuri Chinta Sankar Rao Control Systems and Machine Learning Research Laboratory Department of Chemical Engineering National Institute of Technology Karnataka Surathkal Mangalore Karnataka 575025 India

This study focuses on copyrolyzing pretreated sawdust and polystyrene utilizing microwave-assisted pyrolysis (MAP) with equal mixing to synthesize and characterize biochar. Graphite was used as a susceptor to facilitate precise pyrolysis temperature control. Potassium hydroxide (KOH) powder serves as a catalyst, influencing the char yields and properties. Torrefied raw sawdust at various temperatures (125–175 °C) enhances biochar yields (24–29 wt %). The feedstocks sawdust and polystyrene are characterized by elemental, proximate, and TGA examinations. Furthermore, comprehensive surface, crystallographic, FTIR, and SEM-EDX analyses are performed on microwave copyrolyzed biochar. The developments in BET surface area during copyrolysis show changes concerning pretreatment temperatures: 125 °C (5.6 m2/g) < 150 °C (6.8 m2/g) < 175 °C (8.6 m2/g). Functional groups connected to the alcohols’ O–H bend and C–O stretching vibrations are detected in the biochar samples through FTIR analysis. Sharp peaks with 2θ values between 33.2° and 36.2° appear in the XRD scan of biochar, indicating the presence of crystalline components in the sample. The EDX results demonstrated that the components of biochar included Mg, C, O, and Ca, indicating that it could have plenty of advantageous applications. The study highlights the obstruction of sawdust char’s porous structures by polystyrene, hindering volatile emissions and leading to increased heating rates. These findings underscore the unique contributions of this method to biochar production.

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Humidity Sensing Elements Based on Silica-Graphene Surface Layers 15

Humidity Sensing Elements Based on Silica-Graphene Surface L...

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15th International Scientific and Practical Conference on Environment. Technology. Resources, ETR 2024

作者： Nedev, Nedyu Nenova, Zvezditza Kozhukharov, Stephan Ivanov, Stefan Nenov, Toshko Fundamentals of Electrical and Power Engineering Technical University of Gabrovo Gabrovo Bulgaria LAMAR Laboratory for Advanced Materials Research University of Chemical Technology and Metallurgy Sofia Bulgaria Automation Information and Control Systems Technical University of Gabrovo Gabrovo Bulgaria

ISBN: (纸本)9781713899570

The paper presents humidity sensing elements based on silica-graphene surface layers, prepared via a sol-gel method. The samples were sintered at temperatures of 400 °C, 600 °C and 800 °C. Tetraethoxysilane was used as a precursor of SiO2 and as a dopant - graphene aggregates of nanoplatelets. A description of the sample preparation procedure is provided. Using a precise impedance analyzer and a calibrator for humidity and temperature, the changes in their resistance R were investigated with variations in relative humidity in the range of 30% to 90% at a temperature of 25 °C and at a frequency of 20 Hz. Morphological observations and map data analyses were carried out by Scanning Electron Microscopy (SEM) and Energy Dispersion Spectroscopy (EDX). The developed sensor elements have a good sensitivity to the humidity, and the resistance change reaches two orders of magnitude. Additions of graphene improve the sensitivity of the elements. The characteristics of the sensing elements at different sintering temperatures and different amounts of graphene dopant were modeled using an artificial neural network. © 2024 Nedyu Nedev, Zvezditza Nenova, Stephan Kozhukharov, Stefan Ivanov, Toshko Nenov.

关键词： Silica

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Degradation of metribuzin in the UV/chlorine process: kinetic model, degradation by-products and transformation pathways

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Environmental Science: Water Research and Technology 2023年第7期9卷 1932-1943页

作者： Hu, Chen-Yan Huang, Dan-Dan Lin, Yi-Li Wang, Qiang-Bing Xu, Ling Dong, Zi-Yi Wu, Yi-Hui Ji, Sheng-Jie College of Environmental and Chemical Engineering Shanghai Engineering Research Center of Energy-Saving in Heat Exchange Systems Shanghai University of Electric Power Shanghai200090 China Department of Safety Health and Environmental Engineering National Kaohsiung University of Science and Technology No. 1 University Rd. Yanchao Dist. Taiwan Kaohsiung824 Taiwan Shanghai Institute of Pollution Control and Ecological Security Shanghai200092 China

This study novelly reported the degradation kinetics and the correlated formation of disinfection by-products (DBPs) of metribuzin, a widely used herbicide that contains nitrogen, in the UV/chlorine process. The influencing factors, including chlorine dosage, pH, and the presence of chloride (Cl−) and natural organic matter (NOM, simulated using humic acid (HA)) in water for metribuzin degradation were evaluated. The pseudo-first-order rate constant (kobs) of metribuzin during UV/chlorination was calculated to be 0.0986 min−1, which was 6.90 times higher than those of UV-alone and 1.53 times greater than that of chlorine-alone. The kobs increased with increasing chlorine dosage and decreasing pH value. Cl− could promote the degradation of metribuzin, while the content of metribuzin changed non-monotonically with HA concentration. Through the establishment of the kinetic model, the kobs of HO• with metribuzin was calculated to be 5.6 × 109 M−1 s−1, and HO• contributed to 20% of metribuzine degradation. The possible degradation pathways of metribuzin in the UV/chlorine process were proposed. In the sequential chlorine disinfection process, trichloromethane (TCM) was the dominant DBP in non-bromine water, while the content of tribromomethane (TBM) raised with increasing molar ratio of bromine to chlorine, which has to be carefully controlled in drinking water treatment plants to provide safe drinking water to the public. © 2023 The Royal Society of Chemistry.

关键词： Chlorine

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Active non-bonding oxygen mediate lattice oxygen oxidation on NiFe_(2)O_(4)achieving efficient and stable water oxidation

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Chinese Journal of Catalysis 2025年第5期72卷 164-175页

作者： Jiangyu Tang Xiao Wang Yunfa Wang Min Shi Peng Huo Jianxiang Wu Qiaoxia Li Qunjie Xu Shanghai Key Laboratory of Materials Protection and Advanced Materials in Electric Power Shanghai Engineering Research Center of Energy-Saving in Heat Exchange SystemsShanghai University of Electric PowerShanghai 200090China School of Environmental and Chemical Engineering Shanghai UniversityShanghai 200444China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092China

The oxygen evolution reaction(OER)serves as a fundamental half–reaction in the electrolysis of water for hydrogen production,which is restricted by the sluggish OER reaction kinetics and unable to be practically *** traditional lattice oxygen oxidation mechanism(LOM)offers an advantageous route by circumventing the formation of M-OOH^(*)in the adsorption evolution mechanism(AEM),thus enhancing the reaction kinetics of the OER but resulting in possible structural destabilization due to the decreased M–O bond ***,the asymmetry of tetrahedral and octahedral sites in transition metal spinel oxides permits the existence of non-bonding oxygen,which could be activated by rational band structure design for direct O-O coupling,where the M–O bond maintains its initial bond ***,non-bonding oxygen was introduced into NiFe_(2)O_(4)via annealing in an oxygen-deficient ***,in-situ grown sulfate species on octahedral nickel sites significantly improved the reactivity of the non-bonding oxygen electrons,thereby facilitating the transformation of the redox center from metal to *** based on non-bonding oxygen(LOMNB)was successfully activated within NiFe_(2)O_(4),exhibiting a low overpotential of 206 mV to achieve a current density of 10 mA cm^(-2)and excellent durability of stable operation for over 150 ***,catalysts featuring varying band structures were synthesized for comparative analysis,and it was found that the reversible redox processes of non-bonding oxygen and the accumulation of non-bonding oxygen species containing 2p holes are critical prerequisites for triggering and sustaining the LOMNB pathway in transition metal spinel *** findings may provide valuable insights for the future development of spinel-oxide-based LOM catalysts.

关键词： Non-bonding oxygen Lattice oxygen oxidation mechanism Oxygen evolution reaction NiFe_(2)O_(4) Spinel oxide

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3D Vision Based Lamination Gap Detection of Carbon Fiber Composite

3D Vision Based Lamination Gap Detection of Carbon Fiber Com...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Xu, Yuanye Yuan, Libiao Liang, Wei Yang, Yutuo Liu, Shuai Zeng, Ziming Zhang, Yinlong Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Shenyang University of Chemical Technology College of Information Engineering Shenyang110142 China Shenzhen Polytechnic School of Automotive and Transportation Engineering Shenzhen518055 China

ISBN: (纸本)9798350327182

The paper presents a machine learning approach to detect laminate gaps and to classify them as open or closed. Compared with the traditional detection methods, which suffer from low precision of point cloud segmentation and poor effect of gap extraction in traditional gap detection, this paper proposes a gap detection algorithm based on 3D Vision. First, an improved undirected graph point cloud segmentation algorithm is used to overcome the under-segmentation of the target region. Second, an adaptive vector for angle discriminant model is proposed to solve the problem of poor extraction effect of the gap edge points. Finally, the B-spline curve-fitting model is used to describe the 3D points on the lamination edges. The proposed algorithm has been evaluated in a visual quality detection platform for carbon fiber composite laminates. The results show that the proposed approach is able to accurately detect and classify laminate gaps in carbon fiber composite structures, providing a reliable tool for quality control in industrial manufacturing processes. © 2023 IEEE.

关键词： Extraction

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Batch-to-Batch Optimization with Model Adaptation Leveraging Gaussian Processes: The Case of Optogenetically Assisted Microbial Consortia 23

Batch-to-Batch Optimization with Model Adaptation Leveraging...

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23rd International Conference on control, Automation and systems, ICCAS 2023

作者： Espinel-Rios, Sebastian Kok, Rudolph Klamt, Steffen Avalos, Jose L. Findeisen, Rolf Analysis and Redesign of Biological Networks Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany Princeton University Department of Chemical and Biological Engineering Princeton United States Institute for Automation Engineering Otto von Guericke University Magdeburg Magdeburg Germany Control and Cyber-Physical Systems Laboratory TU Darmstadt Germany

ISBN: (纸本)9788993215274

Microbial consortia are promising biotechnological production systems with the potential to divide complex metabolic pathways into smaller submodules, as well as make products and consume substrates that monocultures cannot. Maintaining optimal cell population levels and preventing mono culture formation challenge bioproduction by microbial consortia. Optogenetics allows for regulating the expression of key growth-regulatory genes through light to modulate cell population levels. Model-based dynamic optimization can determine optimal light trajectories and inoculum sizes that maximize product synthesis while satisfying system constraints, e.g., safety, economic, or technical aspects. Further-more, closed-loop dynamic optimization can address system uncertainty to a certain extent;however, its implementation is challenging due to limited online sensors. Alternatively, here we propose to perform open-loop optimization with batch-to-batch model adaptation based on Gaussian processes for maximizing bioproduction by optogenetically assisted consortia. The proposed approach enables knowledge transfer from existing to new models, improving predictability and optimization performance in each batch while avoiding costly and time-consuming modeling experiments. Compared to closed-loop optimization, this strategy is easier to implement as it does not rely on online monitoring, contributing to the state of the art in optimizing bioproduction by microbial consortia. We outline the applicability of the approach using simulation experiments of an optogenetically assisted consortium for the biosynthesis of the flavonoid naringenin, considering both parameter and model structure uncertainty. © 2023 ICROS.

关键词： Substrates

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Disturbance Observer-Based Optimal Tracking control for Slot Coating Process with Mismatched Input Disturbances

Disturbance Observer-Based Optimal Tracking Control for Slot...

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UKACC International Conference on control (control)

作者： Zezhi Tang Christopher Passmore J Anthony Rossiter Stephen Ebbens Gary Dunderdale George Panoutsos Department of Automatic Control and Systems Engineering University of Sheffield Department of Chemical and Biological Engineering University of Sheffield Sustainable Aviation Fuels Innovation Centre Sheffield

ISBN: (数字)9798350374261

ISBN: (纸本)9798350374278

Slot coating is a widely used technique in various manufacturing processes. The efficiency of the process mostly depends on the precise control of diverse inputs such as pump rate and gap. However, this method can be sensitive to minor disturbances in process conditions, which can disrupt the uniformity of the film thickness. To overcome the challenge, through the implementation of the generalized disturbance observer and compensator, the impact of disturbances can be attenuated in the output channel. In addition, by combining with an output tracking controller, the proposed composite architecture effectively compensates the disturbances while guaranteeing the tracking of the specified film thickness across a wide range of situations. The simulation results were illustrated to showcase the effectiveness of the disturbance observer-based optimal tracking control (DOBOTC) system.

关键词： Manufacturing processes Simulation Perturbation methods Process control Disturbance observers Coatings Closed loop systems

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Stability-informed Bayesian Optimization for MPC Cost Function Learning

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IFAC-PapersOnLine 2024年第18期58卷 208-213页

作者： Sebastian Hirt Maik Pfefferkorn Ali Mesbah Rolf Findeisen Control and Cyber-Physical Systems Laboratory Technical University of Darmstadt Darmstadt Germany Department of Chemical and Biomolecular Engineering University of California Berkeley CA 94720 USA

Designing predictive controllers towards optimal closed-loop performance while maintaining safety and stability is challenging. This work explores closed-loop learning for predictive control parameters under imperfect information while considering closed-loop stability. We employ constrained Bayesian optimization to learn a model predictive controller's (MPC) cost function parametrized as a feedforward neural network, optimizing closed-loop behavior as well as minimizing model-plant mismatch. Doing so offers a high degree of freedom and, thus, the opportunity for efficient and global optimization towards the desired and optimal closed-loop behavior. We extend this framework by stability constraints on the learned controller parameters, exploiting the optimal value function of the underlying MPC as a Lyapunov candidate. The effectiveness of the proposed approach is underlined in simulations, highlighting its performance and safety capabilities.

关键词： Closed-loop Learning Model Predictive control Bayesian Optimization Lyapunov Stability Policy Optimization Neural Network

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