Topic
Transfer function
About: Transfer function is a research topic. Over the lifetime, 14362 publications have been published within this topic receiving 214983 citations. The topic is also known as: system function & network function.
Papers published on a yearly basis
Papers
More filters
TL;DR: In this article, the authors present an efficient method for computing low-order linear system models of solid oxide fuel cells (SOFCs) from time domain simulations using the Box-Jenkins algorithm.
61 citations
TL;DR: The key idea to obtain all the results is system theoretic characterizations of BAE, QND, and DFS in terms of controllability and observability properties or transfer functions of linear systems, which are consistent with their standard definitions.
Abstract: To control a quantum system via feedback, we generally have two options in choosing control scheme. One is the coherent feedback, which feeds the output field of the system, through a fully quantum device, back to manipulate the system without involving any measurement process. The other one is the measurement-based feedback, which measures the output field and performs a real-time manipulation on the system based on the measurement results. Both schemes have advantages/disadvantages, depending on the system and the control goal, hence their comparison in several situation is important. This paper considers a general open linear quantum system with the following specific control goals; back-action evasion (BAE), generation of a quantum non-demolished (QND) variable, and generation of a decoherence-free subsystem (DFS), all of which have important roles in quantum information science. Then some no-go theorems are proven, clarifying that those goals cannot be achieved by any measurement-based feedback control. On the other hand it is shown that, for each control goal, there exists a coherent feedback controller accomplishing the task. The key idea to obtain all the results is system theoretic characterizations of BAE, QND, and DFS in terms of controllability and observability properties or transfer functions of linear systems, which are consistent with their standard definitions.
60 citations
12 Nov 2012
TL;DR: In this paper, a modeling and analysis methodology for the current loop control design for three-phase high power converters with extremely low sampling ratios is presented, which applies the complex transfer function and the double-sided Frequency-Response-functions to quantitatively characterize the system such as the phase margin, dynamic performance and the noise immunity.
Abstract: This paper presents a modeling and analysis methodology for the current loop control design for three-phase high power converters with extremely low sampling ratios. It applies the complex transfer function and the double-sided Frequency-Response-Functions to quantitatively characterize the system such as the phase margin, dynamic performance and the noise immunity. Both standard PI control and PI control with a current state feedback are modeled and validated via circuit simulations in SABER, which demonstrate the precision and the intuitiveness of the proposed modeling concept. Based on these precise models, some special phenomena and design challenges of the current control loops for high power converters are summarized followed by some generalized design recommendations. Since the precision of the modeling concept is independent of the sampling ratio, the methodology can also be leveraged to research topics such as the “negative impedance” and “active damping”. Generally, this simple and precise modeling concept is highly attractive for control loop analysis and design of three-phase converters.
60 citations
TL;DR: A new approach to the problem of time-variant filtering is presented, based upon the generation of the mixed time-frequency representation (MTFR) of a signal, multiplication of that representation by a time- Frequency function H(ω,t), and obtaining a filtered output by an inverse operation.
Abstract: A new approach to the problem of time-variant filtering is presented. This approach is based upon the generation of the mixed time-frequency representation (MTFR) of a signal, multiplication of that representation by a time-frequency function H(ω,t), and obtaining a filtered output by an inverse operation. The resultant filter is linear if the time-frequency representation used is the complex spectrogram. In contrast, the filter is nonlinear if the Wigner distribution function is used. Not every function of two variables is an allowed MTFR of a signal; some conditions must be satisfied. If the function produced by the product of the signal MTFR and the filter function is not an allowed MTFR, an approximation based on projection onto the space of allowed MTFR functions is investigated. This approximation yields a filtered function whose MTFR is as close as possible (in the least-squared sense) to the desired.
60 citations
TL;DR: The two-sided Laplace transform is revived to express the stable inversion for linear nonminimum phase systems that was recently proposed from the viewpoint of state-space representations and it is demonstrated that those two different expressions for thestable inversion are mathematically equivalent.
60 citations