Compared to other energy sources, nuclear reactors offer several advantages as a spacecraft power source, including compact size, high power density, and long operating life. These qualities make nuclear power an idea...
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Compared to other energy sources, nuclear reactors offer several advantages as a spacecraft power source, including compact size, high power density, and long operating life. These qualities make nuclear power an ideal energy source for future deep space exploration. A whole system model of the space nuclear reactor consisting of the reactor neutron kinetics, reactivity control, reactor heat transfer, heat exchanger, and thermoelectric converter was developed. In addition, an electrical power controlsystem was designed based on the developed dynamic model. The GRS method was used to quantitatively calculate the uncertainty of coupling parameters of the neutronics, thermal-hydraulics, and controlsystem for the space reactor. The Spearman correlation coefficient was applied in the sensitivity analysis of system input parameters to output parameters. The calculation results showed that the uncertainty of the output parameters caused by coupling parameters had the most considerable variation, with a relative standard deviation < 2.01%. Effective delayed neutron fraction was most sensitive to electrical power. To obtain optimal control performance, the non-dominated sorting genetic algorithm method was employed to optimize the controller parameters based on the uncertainty quantification calculation. Two typical transient simulations were conducted to test the adaptive ability of the optimized controller in the uncertainty dynamic system, including 100% full power (FP) to 90% FP step load reduction transient and 5% FP/min linear variable load transient. The results showed that, considering the influence of system uncertainty, the optimized controller could improve the response speed and load following accuracy of electrical power control, in which the effectiveness and superiority have been verified.
Boiler systemcontrol presents significant challenges due to its complex, high-order dynamics, which make real-time control computationally demanding. Traditional model order reduction (MOR) techniques often compromis...
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Boiler systemcontrol presents significant challenges due to its complex, high-order dynamics, which make real-time control computationally demanding. Traditional model order reduction (MOR) techniques often compromise system accuracy, while conventional Proportional-Integral-Derivative (PID) tuning methods struggle with nonlinearities and dynamic uncertainties. This study proposes a dual-stage optimization framework that integrates balanced truncation-based model order reduction with nature-inspired metaheuristic algorithms for PID controller tuning to address these issues. The PID controllers are optimized using both classical methods such as Ziegler-Nichols (ZN), Simple Internal Model control (SIMC), Approximate M-Constrained Integral Gain optimization (AMIGO), and Chien-Hrones-Reswick (CHR), as well as advanced optimization techniques like Particle Swarm optimization (PSO), Krill Herd optimization (KHO), Harris Hawks optimization (HHO), Moth-Flame optimization (MFO), and Sparrow Search optimization (SSO). Experimental results demonstrate that the PSO-optimized PID controller achieves a 20% reduction in settling time and a 14.68% improvement in Integral Square Error (ISE) compared to conventional tuning methods. The HHO-based approach improves overall performance by 15%, while SSO significantly reduces computational complexity by 65% while maintaining 98% system accuracy. Statistical analysis (p < 0.05) confirms the robustness of the proposed methodology, showing a 45% reduction in standard deviation compared to traditional approaches. The proposed framework offers a scalable, computationally efficient, and high-performance solution for industrial boiler controlsystems, ensuring improved stability, faster response times, and real-time adaptability over existing strategies.
This paper presents a combined plant and controller performance analysis and optimization for a tethered rigid wing with on-board rotors, flying in crosswind patterns. Specifically, we use a 3-D model of the tethered ...
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This paper presents a combined plant and controller performance analysis and optimization for a tethered rigid wing with on-board rotors, flying in crosswind patterns. Specifically, we use a 3-D model of the tethered wing to assess the influence of critical design parameters on both quality of flight and energy-generation performance, as quantified by the "Loyd Factor," which compares energy-generation performance to a theoretical upper bound. Recognizing that the optimal performance occurs when the system is on the verge of closed-loop instability, we demonstrate how a combined optimization of the plant and controller can aid in further pushing the boundaries of the system. The results of this combined optimization show a critical tradeoff between robustness and energy-generation performance. We demonstrate that attaining maximum energy-generation performance requires operating on the verge of closed-loop instability and also results in a reduced set of parameters for which the system is stable.
Optogenetics describes the use of genetically encoded photosensitive proteins to direct intended biological processes with light in recombinant and native systems. While most of these light-responsive proteins were or...
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Optogenetics describes the use of genetically encoded photosensitive proteins to direct intended biological processes with light in recombinant and native systems. While most of these light-responsive proteins were originally discovered in photosynthetic organisms, the past few decades have been punctuated by experiments that not only commandeer but also engineer and enhance these natural tools to explore a wide variety of physiological questions. In addition, the ability to tune dynamic range and kinetic rates of optogenetic actuators is a challenging question that is heavily explored with computational methods devised to facilitate optimization of these systems. Here, we explain the basic mechanisms of a few popular photodimerizing optogenetic systems, discuss applications, compare optogenetic tools against more traditional chemical methods, and propose a simple quantitative understanding of how actuators exert their influence on targeted processes.
An experimental study of a modern ultra high frequency (UHF) radio frequency identification (RFID) system is here proposed. Some relationships between the electromagnetic field levels received by the deployed devices ...
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ISBN:
(纸本)9781424428328;9781424428335
An experimental study of a modern ultra high frequency (UHF) radio frequency identification (RFID) system is here proposed. Some relationships between the electromagnetic field levels received by the deployed devices and the system overall performance are in particular analyzed. The main purpose is to experimentally analyze the behavior and performance of a real world UHF RFID system underlying the importance of preliminary measurements in the setup and optimization of these systems. Practical rules to improve the system reliability are finally deduced. To this aim, a detailed description of tags operation in near and far field regions of the reader is given, along with meaningful results from experiments conducted on purpose. Experiments have been carried out by using an ad-hoc realized testbed, equipped with a real-life UHF RFID system.
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