Frequency Domain Thermal Analysis of Future Spacecraft and Systems

Purpose – Analytical determination of harmonic components of current in electric circuits containing semiconductor converters with the use of a small parameter method (SPM) in frequency domain. The paper aims to discuss these issues. Design/methodology/approach – A SPM realized in frequency domain was used in the analytical analysis of electric circuits with semiconductor converters. An automated method of formation of orthogonal harmonic components of electrical values on the basis of discrete convolution algorithm was used to provide the possibility of realization of calculation in frequency domain. A nonlinear characteristic of a semiconductor converter was presented by the method of numerical approximation. A numerical structured simulation method was applied to determination of the reference values of current in the analyzed circuit. Laws of theoretical electrical engineering were used for formation of the equations of voltage balance in the circuit with a nonlinear element. Findings – It is shown th...

The high penetration of power electronic converters with complex control systems is changing the power system dynamics, introducing new challenges such as converter-driven stability incidents. Traditional stability analysis methods, suitable for classical problems like voltage, frequency, and rotor angle stability in large systems, are insufficient for addressing the fast control dynamics of converters, which involve electromagnetic phenomena. These phenomena require detailed converter and network modeling, which can be performed in both the frequency and time domains, enabling the respective stability analyses to be carried out. However, frequency domain methods, based on small-signal impedances linearized at a single operating point, inherently ignore time domain phenomena like switching events and nonlinear behaviors. In contrast, time domain electromagnetic transient (EMT) simulations are effective for analyzing converter-driven stability but are computationally intensive when applied to large transmission systems with numerous use cases. Therefore, to reduce the simulation complexity in EMT tools, a complexity reduction procedure is proposed in this paper. Leveraging the advantages of the frequency domain, such as faster simulation times and information on wideband frequency characteristics of the system, this procedure utilizes the small-signal impedances and introduces a method for network reduction. The procedure also uses the frequency domain stability analysis method to screen for critical network use cases. Primarily, this procedure is a frequency domain toolchain encompassing frequency domain stability analysis and frequency domain network reduction. The result of the toolchain is a reduced network size and reduced network use cases that can be used for EMT simulations. The procedure is applied to an IEEE 39 bus system, where converter-driven stability is evaluated for two use cases. Furthermore, the network reduction method is tested on a critical use case, demonstrating reductions in network size and computation times without compromising the quality of stability analysis results.

This paper is concerned with distributed consensus control of unknown multiagent systems. As the system’s dynamics is unknown, an adaptive Fourier decomposition (AFD) based iterative learning control (ILC) dynamics adaptive matching method in frequency domain is put forward to deal with it. First, large amounts of input and output measurement data are used to estimate the frequency domain characteristics of the system by Takenaka-Malmquist functions. Second, convert the traditional time domain ILC to the frequency domain to establish a matching relationship with the estimated frequency domain features. Then, an adaptive iterative learning rate is constructed to achieve the optimal convergence at each sampling point. The feasibility of the proposed algorithm is guaranteed by the convergence of AFD in Hardy space <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H^{2}(\mathbb {D})$ </tex-math></inline-formula> under the maximum selection principle. Compared with the reinforcement learning data-driven control scheme, the method proposed in this paper has obvious advantages in the control accuracy and convergence efficiency. In addition, this paper takes two kinds of denoising algorithms based on unwinding AFD to deal with the multi-agent systems with channel noise. Finally, the feasibility and effectiveness of the developed method are verified by a series of simulations.

Review: 70 refs.

Parameter estimation and identification is an important part of flight mechanic. In this study the purpose is to estimate flying parameters for resistance derivation and aircraft control. At first those parameters were estimated for lateral-directional motion with which we could reach more precise results and fewer errors in time domain. In frequency domain we could reach nearly acceptable results with a specific step in special frequency band limit. In longitude motion we also had suitable responses in time domain. But we didn't have good results in frequency domain method. So to get answers from this system we analyzed motion modes and after processing frequencies to attain effective and critical signals, analysis was done in the frequency limit and therefore better results were obtained.

The case study presents modern robust control methods of the Bergman minimal model of Type I diabetic patients under intensive care using computer algebra: the disturbance rejection LQ control or minimax control (as extension of the classical LQ control) and the robust H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">¿</sub> control. It is shown the minimax control has limitations in practice, but employing reduced Gro¿bner basis on rational field, it is possible to approximate the theoretical solution and so getting a better solution than LQ does. The symbolic and numeric computations were carried out with Mathematica 5.2 and with its CSPS Application, as well as with MATLAB 6.5. In case of H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">¿</sub> control, the graphical method in frequency domain- implemented under Mathematica by-is extended with a disturbance rejection constraint and the robustness of the resulted highorder linear controller is demonstrated by nonlinear closed loop simulation in state-space, in case of standard meal disturbances.

The effects of electrical vestibular stimulation upon movement and perception suggest two evoked sensations: head roll and inter-aural linear acceleration. The head roll vector causes walking subjects to turn in a direction dependent on head pitch, requiring generation of torque around a vertical axis. Here the effect of vestibular stimulation upon vertical torque (T(z)) was investigated during quiet stance. With the head tilted forward, square-wave stimuli applied to the mastoid processes evoked a polarity-specific T(z) response accompanied by trunk yaw. Stochastic vestibular stimulation (SVS) was used to investigate the effect of head pitch with greater precision; the SVS–T(z) cross-correlation displayed a modulation pattern consistent with the head roll vector and this was also reflected by changes in coherence at 2–3 Hz. However, a separate response at 7–8 Hz was unaffected by head pitch. Head translation (rather than rotation) had no effect upon this high frequency response either, suggesting it is not caused by a sense of body rotation induced by an inter-aural acceleration vector offset from the body. Instead, high coherence between medio-lateral shear force and T(z) at the same frequency range suggests it is caused by mechanical coupling to evoked medio-lateral sway. Consistent with this explanation, the 7–8 Hz response was attenuated by 90 deg head roll or yaw, both of which uncouple the inter-aural axis from the medio-lateral sway axis. These results demonstrate two vertical torque responses to electrical vestibular stimulation in standing subjects. The high frequency response can be attributed to mechanical coupling to evoked medio-lateral sway. The low frequency response is consistent with a reaction to a sensation of head roll, and provides a novel method for investigating proprioceptive-vestibular interactions during stance.

Differential mode delay and modal bandwidth measurements of multimode fibers using frequency-domain method

Optical imaging systems are often limited in resolution, not by the imaging optics, but by the light intensity sensors on the image formation plane. When the sensor size is larger than the optical spot size, the effect is to smooth the image with a rectangular convolving kernel with one sample at each non-overlapping kernel position, resulting in aliasing. In some such imaging systems, there is the possibility of collecting multiple images of the same scene. The process of reconstructing a de-aliased high-resolution image from multiple images of this kind is referred to as "super-resolution image reconstruction." We apply the POCS method to this problem in the frequency domain. Generally, frequency domain methods have been used when component images were related by subpixel shifts only, because rotations of a sampled image do not correspond to a simple operation in the frequency domain. This algorithm is structured to accommodate rotations of the source relative to the imaging device, which we believe helps in producing a well-conditioned image synthesis problem. A finely sampled test image is repeatedly resampled to align with each observed image. Once aligned, the test and observed images are readily related in the frequency domain and a projection operation is defined.

A two-steps implementation of 3D ultrasound imaging in frequency domain with 1D array transducer

Spectrum sensing is the key and premise of cognitive radio. The current spectrum sensing methods have some failures and limitations, such as sensitivity to noise uncertainty and failure in some special modulation types. In order to cope with these problems and improve the detection performance, we propose a blind spectrum sensing method based on Petrosian's algorithm in frequency domain. It calculates the fractal dimension by Petrosian's method in frequency domain, and compares the fractal dimension with the threshold to determine whether the primary users exist or not. Monte Carlo simulations show that the proposed method can blind sense spectrum effectively. It outperforms energy detection, box dimension method and Higuchi dimension method with about 1 dB, 25 dB and 25 dB improvements respectively, and consumes much shorter detection times than them. Furthermore, it can overcome some failures and limitations of some other spectrum sensing methods, such as sensitivity to noise uncertainty and failure in some special modulation types, and can be applied to fast blind spectrum sensing in situations of noise uncertain.

Two previously proposed training sequence optimization techniques for channel estimation are compared. One method is based on a frequency-domain (FD) based channel estimation method and the other is based on a time-domain (TD) channel estimation technique. The FD method produces a lower complexity search strategy, but does not always result in the optimal training sequences in terms of the mean-squared channel estimation error. A proof of the superiority of the TD method over the FD method is presented. Based on the proof, an alternative search criterion is proposed, which, in general, provides equivalent or better performance than the FD method while still enjoying the low search complexity.

Time-resolved fluorescence determinations on biochemical samples are often complicated by contributions from background. In the time-correlated single-photon counting method, background subtraction is a routine procedure. A limitation of frequency domain fluorometry, however, arises from the difficulty of performing this operation. This limitation has become increasingly significant as frequency domain methods are being applied to evermore complex biological systems using the higher-frequency capabilities of modern instrumentation. We have devised a method for such a correction in the frequency domain, regardless of the complexity of the background decay, based on measurement of the background phasor and subsequent subtraction from the sample phasor. This method is applicable to both lifetime and dynamic polarization measurements, and it can be readily implemented on commercially available frequency domain fluorometers. Decay curves may be accurately recovered from samples containing background contributions ranging from less than 5% to greater than 90% of the total signal intensity.

Spectral Analysis of Block Structured Nonlinear Systems

BackgroundIn investigations of the human motor system, two approaches are generally employed toward the identification of common modulating drives from motor unit recordings. One is a frequency domain method and uses the coherence function to determine the degree of linear correlation between each frequency component of the signals. The other is a time domain method that has been developed to determine the strength of low frequency common modulations between motor unit spike trains, often referred to in the literature as 'common drive'.MethodsThe relationships between these methods are systematically explored using both mathematical and experimental procedures. A mathematical derivation is presented that shows the theoretical relationship between both time and frequency domain techniques. Multiple recordings from concurrent activities of pairs of motor units are studied and linear regressions are performed between time and frequency domain estimates (for different time domain window sizes) to assess their equivalence.ResultsAnalytically, it may be demonstrated that under the theoretical condition of a narrowband point frequency, the two relations are equivalent. However practical situations deviate from this ideal condition. The correlation between the two techniques varies with time domain moving average window length and for window lengths of 200 ms, 400 ms and 800 ms, the r2 regression statistics (p < 0.05) are 0.56, 0.81 and 0.80 respectively.ConclusionsAlthough theoretically equivalent and experimentally well correlated there are a number of minor discrepancies between the two techniques that are explored. The time domain technique is preferred for short data segments and is better able to quantify the strength of a broad band drive into a single index. The frequency domain measures are more encompassing, providing a complete description of all oscillatory inputs and are better suited to quantifying narrow ranges of descending input into a single index. In general the physiological question at hand should dictate which technique is best suited.