This research article considers the design of static output-feedback sliding mode control for Markovian jump systems,in which the attacker may inject false information into the communication channel between the contro...
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ISBN:
(纸本)9781665431293
This research article considers the design of static output-feedback sliding mode control for Markovian jump systems,in which the attacker may inject false information into the communication channel between the controller and the *** key issue is how to design the feasible sliding mode control law to overcome the effects of unknown and time-varying *** this end,an on-line estimation scheme is introduced to deal with the unknown network attack *** then,a linear sliding surface is constructed based on the measured output information and an outputfeedback sliding mode controller is correspondingly *** is shown that the reachability of the specified sliding surface can be achieved and the asymptotic stability of the closed-loop system can be ensured under the derived sufficient ***,simulation examples are provided to verify the developed static output-feedback sliding mode control strategy.
The extractive dividing-wall column(EDWC)is one of the most efficient technologies for separation of azeotropic or close boiling-point mixtures,but its design is fairly *** this paper we extend the hybrid feasible pat...
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The extractive dividing-wall column(EDWC)is one of the most efficient technologies for separation of azeotropic or close boiling-point mixtures,but its design is fairly *** this paper we extend the hybrid feasible path optimisation algorithm(Ma Y,McLaughlan M,Zhang N,Li ***&Chemical Engineering,2020,143:107058)for such optimal *** tolerances-relaxation integration method is refined to allow for long enough integration time that can ensure the solution of the pseudo-transient continuation simulation close to the steady state before the required tolerance is *** ensure the gradient and Jacobian information available for optimisation,we allow a relaxed tolerance for the simulation in the sensitivity analysis mode when the simulation diverges under small *** addition,valid lower bounds on purity of the recycled entrainer and the vapour flow rate in column sections are imposed to improve computational *** computational results demonstrate that the extended hybrid algorithm can achieve better design of the EDWC compared to those in *** energy consumption can be reduced by more than 20%compared with existing literature *** addition,the optimal design of the heat pump assisted EDWC is achieved using the improved hybrid algorithm for the first time.
The Yi lacquerware pattern is abundant in content and exquisite in design. It has extremely strong regional characteristics and value connotations. Through field investigation, literature research and physical researc...
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Venous thromboembolism (VTE) is a major global cause of death, with recurrence risk rising after inadequate treatment. Existing VTE recurrence prediction models often overlook the phenomenological aspects of blood clo...
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In the pursuit of personalized medicine, there is a growing demand for computational models with parameters that are easily obtainable to accelerate the development of potential solutions. Blood tests, owing to their ...
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In the pursuit of personalized medicine, there is a growing demand for computational models with parameters that are easily obtainable to accelerate the development of potential solutions. Blood tests, owing to their affordability, accessibility, and routine use in healthcare, offer valuable biomarkers for assessing hemostatic balance in thrombotic and bleeding disorders. Incorporating these biomarkers into computational models of blood coagulation is crucial for creating patient-specific models, which allow for the analysis of the influence of these biomarkers on clot formation. This systematic review aims to examine how clinically relevant biomarkers are integrated into computational models of blood clot formation, thereby advancing discussions on integration methodologies, identifying current gaps, and recommending future research directions. A systematic review was conducted following the PRISMA protocol, focusing on ten clinically significant biomarkers associated with hemostatic disorders: D-dimer, fibrinogen, Von Willebrand factor, factor VIII, P-selectin, prothrombin time (PT), activated partial thromboplastin time (APTT), antithrombin III, protein C, and protein S. By utilizing this set of biomarkers, this review underscores their integration into computational models and emphasizes their integration in the context of venous thromboembolism and hemophilia. Eligibility criteria included mathematical models of thrombin generation, blood clotting, or fibrin formation under flow, incorporating at least one of these biomarkers. A total of 53 articles were included in this review. Results indicate that commonly used biomarkers such as D-dimer, PT, and APTT are rarely and superficially integrated into computational blood coagulation models. Additionally, the kinetic parameters governing the dynamics of blood clot formation demonstrated significant variability across studies, with discrepancies of up to 1,000-fold. This review highlights a critical gap in the avail
Semi-supervised learning models often rely on the restricted assumptions, and can easily suffer from corvariate shift or noise. Few studies have explored the use of fuzzy rule-based methods in the semi-supervised disc...
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In practical control engineering,delay and actuator saturation are main challenges which may lead to system performance degradation,or even controlled variables *** of Smith predictor and model recovery anti windup me...
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In practical control engineering,delay and actuator saturation are main challenges which may lead to system performance degradation,or even controlled variables *** of Smith predictor and model recovery anti windup method is an effective solution to linear delay system anti-windup synthesis,however model dependent property of the above two methods brings obstacles for the application and *** overcome such a difficulty,a data-driven approach is proposed in this paper,operating data is collected and utilized to simultaneously tune feedback controller parameters and estimate internal model applied in Smith ***,anti-windup compensator is constructed with the estimated model and a compensator gain optimization structure is proposed based on Lyapunov ***,simulations have been implemented to three typical processes in chemical engineering,and detailed performance comparison is provided to illustrate the effectiveness of the proposed method.
The smelting process of the fused magnesium furnace(FMF) is prone to semi-molten abnormal conditions, which may lead to low product quality and production efficiency, and is also prone to safety accidents. At present,...
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ISBN:
(数字)9798350368604
ISBN:
(纸本)9798350368611
The smelting process of the fused magnesium furnace(FMF) is prone to semi-molten abnormal conditions, which may lead to low product quality and production efficiency, and is also prone to safety accidents. At present, the operating conditions of FMF mainly rely on manual observation of the furnace shell features for diagnosis, and it is hard to timely and effectively identify abnormalities in the smelting process. Given the difficulty in identifying abnormal operating conditions of FMF, this paper proposes a deep multiview fuzzy classification method(DMFC) that can automatically identify abnormal operating conditions. First, based on the three-phase current data, CNN and Transformer are used to extract features as multiple views. Secondly, the Takagi-Sugeno-Kang(TSK) fuzzy model is used as a single-view model, and the evidence theory is used for dynamic fusion of multiple views. This method can effectively fuse multiple deep features, and has strong scalability and a certain degree of interpretability. Through verification of the real historical data of multiple FMFs, our model has relatively high accuracy, false detection rate(FDR), and missed detection rate(MDR).
Chemical spills on complex geometry are difficult to model due to the uneven concentration distribution caused by air flow over ground obstacles. Computational fluid dynamics(CFD) is one of the powerful tools to estim...
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Chemical spills on complex geometry are difficult to model due to the uneven concentration distribution caused by air flow over ground obstacles. Computational fluid dynamics(CFD) is one of the powerful tools to estimate the building-resolving wind flow as well as pollutant dispersion. However, it takes too much time and requires enormous computational power in emergency situations. As a time demanding task, the estimation of the chemical spill consequence for emergency response requires abundant wind field information. In this paper, a comprehensive wind field reconstruction framework is proposed, providing the ability of parameter tuning for best reconstruction accuracy. The core of the framework is a data regression model built on principal component analysis(PCA) and extreme learning machine(ELM). To improve the accuracy, the wind field estimation from the regression model is further revised from local wind observations. The optimal placement of anemometers is provided based on the maximum projection on minimum eigenspace(MPME) algorithm. The fire dynamic simulator(FDS) generates high-resolution data of wind flow over complex geometries for the framework to be implemented. The reconstructed wind field is evaluated against simulation data and an overall reconstruction error of 9% is achieved. When used in real case,the error increases to around 12% since no convergence check is available. With parameter tuning abilities,the proposed framework provides an efficient way of reconstructing the wind flow in congested areas.
Microgrid is an advanced application of distributed renewable energy utilization. With the development of energy Internet technology, microgrid is characterized by strong decentralization and high intelligence. The op...
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