An integrated deep learning - economic model predictive control (EMPC) framework for large scale processes is presented. the framework is successfully implemented to a realistic fluid catalytic cracker (FCC) - fractio...
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ISBN:
(数字)9781665467469
ISBN:
(纸本)9781665467469
An integrated deep learning - economic model predictive control (EMPC) framework for large scale processes is presented. the framework is successfully implemented to a realistic fluid catalytic cracker (FCC) - fractionator process. Scenarios under the effect of no disturbances (nominal) and with disturbances are simulated demonstrating fast computation (potentially allowing industrial implementation) and improved performance (taking into account process nonlinear behavior, enhancing the process operating profit).
this paper deals withthe design of an MRAC-based adaptive control law for blood glucose regulation of T1DM patients. Parametric uncertainty in T1DM patients is one of the primary issues in designing adaptive control ...
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ISBN:
(数字)9798350364293
ISBN:
(纸本)9798350364309
this paper deals withthe design of an MRAC-based adaptive control law for blood glucose regulation of T1DM patients. Parametric uncertainty in T1DM patients is one of the primary issues in designing adaptive control laws. By designing an adaptive controller in the MRAC framework, the risk of hypoglycemia is eliminated. Extensive simulation experiments are used to examine the closed-loop response of plasma glucose concentration and external insulin infusion rate for a wide range of model parameter variations.
this work theoretically studies a ubiquitous reinforcement learning policy for controlling the canonical model of continuous-time stochastic linear-quadratic systems. We show that randomized certainty equivalent polic...
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ISBN:
(数字)9781665467469
ISBN:
(纸本)9781665467469
this work theoretically studies a ubiquitous reinforcement learning policy for controlling the canonical model of continuous-time stochastic linear-quadratic systems. We show that randomized certainty equivalent policy addresses the exploration-exploitation dilemma in linear controlsystems that evolve according to unknown stochastic differential equations and their operating cost is quadratic. More precisely, we establish square-root of time regret bounds, indicating that randomized certainty equivalent policy learns optimal control actions fast from a single state trajectory. Further, linear scaling of the regret withthe number of parameters is shown. the presented analysis introduces novel and useful technical approaches, and sheds light on fundamental challenges of continuous-time reinforcement learning.
this paper presents a training information system for studying biomedical cardiological data. the software system examines cardiological data obtained in real conditions (electrocardiographic, photoplethysmographic, a...
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ISBN:
(数字)9781665467469
ISBN:
(纸本)9781665467469
this paper presents a training information system for studying biomedical cardiological data. the software system examines cardiological data obtained in real conditions (electrocardiographic, photoplethysmographic, and Holter data). the interactive system is oriented toward upgrading the training of students in medicine and health care, providing an opportunity to create a preliminary experience for future medical professionals in working with different types of cardiological data. the use of photoplethysmographic and Holter data is discussed in more detail. the presented system provides an opportunity to conduct research and studies on the interaction between the heart and the functioning of the human organism. the article shows the results obtained in the analysis of cardiac data registered in healthy subjects and patients with cardiovascular disease. Graphical results (Spectrogram and Global Power Spectral Density) from the study of healthy subjects compared withthe graphic results of subjects with arrhythmia are presented and discussed.
Unmanned aerial vehicles can improve short- term weather forecasting by acquiring information from weather sensors and other sensors. Withthis information, there is the possibility of making relevant maps like solar ...
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ISBN:
(数字)9798350364293
ISBN:
(纸本)9798350364309
Unmanned aerial vehicles can improve short- term weather forecasting by acquiring information from weather sensors and other sensors. Withthis information, there is the possibility of making relevant maps like solar radiation, pollen, emissions, particles, and others. Another advantage of this acquisition system is the high rate of flights, compared to the classic measurements made withthe weather balloon, which is launched twice a day. In addition to the advantages listed above, we discuss the multiplication factor of the acquired data, these systems being able to operate in various geographical locations.
Monitoring water consumption has multiple benefits nowadays. Big data collected from the sensors provide a consistent basis for the decision-making processes in terms of establishing the indices and criteria needed to...
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ISBN:
(数字)9781665467469
ISBN:
(纸本)9781665467469
Monitoring water consumption has multiple benefits nowadays. Big data collected from the sensors provide a consistent basis for the decision-making processes in terms of establishing the indices and criteria needed to optimize the water demand. In this study, the data provided by four distinct water consumption outlets (hot/cold water sink, toilet, and shower) from multiple households were analyzed. A clustering analysis revealed a visual overview of the consumption events from each outlet. then, classification methods were used to predict the source of water consumption events using four algorithms based on machine learning and deep learning. the proposed methods and results are promising towards the development of a decision support system for streamlining water consumption in urban water distribution systems.
the main objective of this paper is to design a suitable control strategy which solves the the so-called Artificial Pancreas Problem, which affects patients with Type 1 Diabetes Mellitus. the theoretical background co...
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this paper considers the design of observer based guaranteed cost control of time-delay nonlinear systems represented by TS fuzzy models. We consider that boththe states and the inputs are affected by time varying de...
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ISBN:
(数字)9781665467469
ISBN:
(纸本)9781665467469
this paper considers the design of observer based guaranteed cost control of time-delay nonlinear systems represented by TS fuzzy models. We consider that boththe states and the inputs are affected by time varying delay, which is assumed to be known. We propose conditions for observer and controller design withthe aim that the closed-loop is asymptotically stable and the cost is minimized the conditions are bilinear and we solve them in two steps. We also give different possibilities for minimizing the cost function along with a performance comparison between them. the results are validated on a numerical example.
In recent years, the edge computing paradigm enables the movement of processing units and storage nearer to the data available locations. the mechanism completes the computation in a short span of time in minimum band...
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the Low Earth Orbit (LEO) satellite network, serving as a vital complement to the terrestrial backbone network, has emerged as a prospective path for future mobile communication systems, owing to its extensive coverag...
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ISBN:
(纸本)9798400709265
the Low Earth Orbit (LEO) satellite network, serving as a vital complement to the terrestrial backbone network, has emerged as a prospective path for future mobile communication systems, owing to its extensive coverage. In this paper, a three-tier computing architecture catering for application scenarios where ground terminal has limited resources and elevated quality of service (QoS) requisites is presented. the proposed design features vertical collaboration among ground users, LEO satellites, and remote cloud servers, providing collaborative computing task offloading capabilities. We consider the delay and energy consumption of the system, formulated the offloading decision problem as a nonlinear integer programming problem, and then introduced an offloading mechanism that utilizes an improved version of the Gale-Shapley (GS) algorithm and non-cooperative game theory (MGSCO) to approximate the optimal solution under specified constraints. the outcomes of simulations indicate that this strategy can significantly mitigate system delays and energy consumption, in contrast to reference strategies.
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