This paper introduces a novel technique for minimizing losses in sensorless field-oriented induction motor (IM) drives using a search control (SC) approach based on improved adaptive quadratic interpolation (AQI). The...
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The detection of infectious viruses using the mechanical arm of an industrial robot can face challenges such as bending and deviations between the detection position and the actual position. This paper introduces a no...
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This study focuses on accurately predicting the excitation current in synchronous motors using a hybrid machine learning algorithm. Given the critical role of excitation current in maintaining motor stability and perf...
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The photoelectric communication remote control system is realized by combining AVR microcontroller with virtual instrument. This design is composed of temperature control module, DC drive module and PC control module....
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In this paper the various computational approaches for automatic generation control (AGC) of power systems is covers, with the goal of improving the automatic voltage regulator (AVR) and load frequency control (LFC) t...
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Digital-to-analogue converters (DACs) exhibit several non-ideal effects that deteriorate performance. Methods in feedback control can reduce such effects. Due to implementation limitations, the feedback signal in exis...
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Optimized and decentralized process control is crucial for energy systems incorporating renewable energy, as it enhances flexibility and reliability by dynamically managing variable energy inputs like solar and wind. ...
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This work investigates the adaptive iterative learning control (AILC) problem for a class of underactuated systems with unknown input distribution matrices. By introducing a newly designed control gain matrix, a novel...
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ISBN:
(纸本)9798350373707;9798350373691
This work investigates the adaptive iterative learning control (AILC) problem for a class of underactuated systems with unknown input distribution matrices. By introducing a newly designed control gain matrix, a novel AILC algorithm is proposed, which is able to deal with the unknown nonsquare control gain matrix effectively. Additionally, an auxiliary system is adopted to deal with the input saturation. The convergence of the proposed control algorithm is rigorously analyzed by using the composite energy function (CEF) method. The effectiveness is demonstrated through a numerical example.
With the rapid development of China's aerospace industry, the market demand for launch vehicles has greatly increased. The hydrogen nozzle is the core component of the thrust chamber injector of the hydrogen-oxyge...
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ISBN:
(纸本)9798350386783;9798350386776
With the rapid development of China's aerospace industry, the market demand for launch vehicles has greatly increased. The hydrogen nozzle is the core component of the thrust chamber injector of the hydrogen-oxygen engine. The flow performance of the injector directly affects the combustion efficiency, stability, rocket thrust and service life of the engine. Based on machine learning technology and hydrogen nozzle flow test data, this paper completed the research on the application and methods of hydrogen nozzle quality control. On the basis of the original data, suggestions for using machine learning technology for quality control are put forward from three aspects: feature engineering, model construction and model evaluation.
This paper proposes a new frequency regulation control strategy for photovoltaic and energy storage stations within new power systems based on Model Predictive control (MPC). This control strategy aims to minimize the...
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