Human pose estimation technology has important applications in many fields. Existing research mainly focuses on precise localization of human key points in unobstructed situations but neglects the common occlusion pro...
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This work proposes an open-loop methodology to solve chance constrained stochastic optimal control problems for linear systems with a stochastic control matrix. We consider a joint chance constraint for polytopic time...
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This paper addresses the challenge of sluggish defect detection, suboptimal accuracy, and susceptibility to adverse environmental conditions in the textile production process. Extensive research on textile defect poin...
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Research and innovations in the fields of renewable energy and sustainable design have been sparked by the need for sustainable and environmentally friendly energy solutions. This research paper describes the design, ...
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This paper presents the stable and robust control of Surface Permanent Magnet Synchronous Motor (SPMSM) with Active LC Low Pass Filter (LC-LPF) by IRM-ILQ (Inverse Reference Model - Inverse Linear Quadratic) method. T...
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ISBN:
(纸本)9798350337938
This paper presents the stable and robust control of Surface Permanent Magnet Synchronous Motor (SPMSM) with Active LC Low Pass Filter (LC-LPF) by IRM-ILQ (Inverse Reference Model - Inverse Linear Quadratic) method. The output voltages of PWM inverters, which used for motor driving contain harmonic components due to its switching. LC-LPF is effective to eliminate those harmonics though, it has two dynamics. Therefore, applying the IRM-ILQ method is necessary since they have two degrees of freedom and can control followability and robustness at the same time. In this paper, the stable and robust control has been confirmed by experiments.
Machine control systems have undergone a significant transformation, transitioning from centralized computer numeric control to automatic control. One of the key challenges in this evolution stems from the complex and...
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ISBN:
(纸本)9798350362664;9798350362671
Machine control systems have undergone a significant transformation, transitioning from centralized computer numeric control to automatic control. One of the key challenges in this evolution stems from the complex and varied nature of many manufacturing systems, characterized by multiscale, Multiphysics, dynamic, and stochastic elements. This complexity has spurred numerous innovations at the convergence of artificial intelligence (AI), data analytics, and manufacturing sciences. Consequently, the question of how the manufacturing industry can leverage the technology flexibility available is addressed through the inherent adaptive capabilities of AI. This research aims to articulate and establish a process for imbuing flexibility into manufacturing processes, leveraging the technology of the manufacturing system with the integration of AI. The objective is to harness the adaptive potential of technology-based flexibility using AI, employing a combination of AI methods, mechanism-driven principles, and engineering technology. In this context, flexibility denotes a manufacturing process's ability to respond effectively to new system requirements, whether planned or unforeseen. The paper asserts that the value of system flexibility is an intrinsic advantage of manufacturing system technology. A qualitative research approach is employed to investigate and elucidate how the manufacturing system can be modeled to unlock its flexibility potential, utilizing Mechanistic AI applications.
In practical applications, wireless charging systems (WCS) should solve unavoidable misalignment problems and realize stable output over a wide load range. Therefore, a detuned WCS with solid anti-misalignment capacit...
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Air traffic management aims to mitigate congestion in air traffic networks mainly caused by capacity constraints of air centers. In this paper, an air traffic network is effectively modeled as a compartmental system, ...
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This paper presents the design and simulation of a single-phase grid-connected inverter control system, focusing on enhancing power quality and dynamic performance. The control system comprises a resonant controller f...
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Increasing energy consumption has required a greater need for connections between the grid and nonconventional energy sources. Recently, doubly fed induction machine (DFIM) fed hydro power units are increasingly conne...
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Increasing energy consumption has required a greater need for connections between the grid and nonconventional energy sources. Recently, doubly fed induction machine (DFIM) fed hydro power units are increasingly connected to the power system due to the requirement of large energy storage option and cost-effective converter solution in the variable speed units. On the other hand, stability related issues are raised in the power system due to the sub synchronous control interaction (SSCI) that occurs between radially connected DFIM, and series compensated transmission line. This article focuses on analysis of resonance stability in a doubly fed induction machine (DFIM) based hydropower system. The controller of the rotor side converter is tuned using a dampness optimization approach. Additionally, optimized SSCI damping controller in the grid side converter is designed to attenuate the sub-synchronous oscillation (SSO) of the DFIM. Time domain simulation analysis is conducted for this research to validate the SSCI mitigation in the DFIM-based hydro units. In MATLAB/Simulink environment, the efficacy of the proposed system with 250 MW DFIM and a series compensated 765 kV extra high voltage transmission line is tested. To scale down the model and check SSO in the 2.2 kW DFIM system, a practical demonstration is carried out in the Lab.
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