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The purpose of this paper is to investigate limit cycles in digitally Proportional, Integral and Derivative (PID) controlled buck regulators. Filtering is examined as a means of removing the limit cycles in digitally controlled buck regulators.

The paper explains why limit cycles occur in a digitally PID controlled buck converter. It then proceeds to propose two filters for their elimination. Results indicate the effectiveness of each of the filters.

The paper gives a mathematical analysis of the occurrence of limit cycles in digitally controlled PID buck regulators. It finds that notch and comb filters are effective for the purpose of eliminating limit cycles in buck regulators.

The paper employs a model of the buck regulator inclusive of the inductor loss – this was not done to date for this type of work. The paper analyses PID control. This was not done in the manner given. The paper addresses filtering as a means of removing limit cycles. It examines the effect of changing the digital controller parameters on the requirements of the filters.

Chaos theory—the science that discovers order in nature's seeming randomness—may have utility as a corporate analysis technique. While it's too soon to predict whether chaos theory mathematics will become a new tool for decision makers, these researchers have made some provocative discoveries by analyzing 20 years of data for 19 publicly traded companies.

Recently, star variables and the post-crisis nature of cyclical fluctuations have attracted a great deal of interest. In this chapter, the authors investigate different methods of assessing business cycles (BCs) for the European Union in general and the euro area in particular. First, the authors conduct a Monte Carlo (MC) experiment using a broad spectrum of univariate trend-cycle decomposition methods. The simulation aims to examine the ability of the analysed methods to find the observed simulated cycle with structural properties similar to actual macroeconomic data. For the simulation, the authors used the structural model’s parameters calibrated to the euro area’s real gross domestic product (GDP) and unemployment rate. The simulation outcomes indicate the sufficient composition of the suite of models (SoM) consisting of popular Hodrick–Prescott, Christiano–Fitzgerald and structural trend-cycle-seasonal filters, then used for the real application. The authors find that: (i) there is a high level of model uncertainty in comparing the estimates; (ii) growth rate (acceleration) cycles have often the worst performances, but they could be useful as early-warning predictors of turning points in growth and BCs; and (iii) the best-performing MC approaches provide a reasonable combination as the SoM. When swings last less time and/or are smaller, it is easier to pick a good alternative method to the suite to capture the BC for real GDP. Second, the authors estimate the BCs for real GDP and unemployment data varying from 1995Q1 to 2020Q4 (GDP) or 2020Q3 (unemployment), ending up with 28 cycles per country. This analysis also confirms that the BCs of euro area members are quite synchronized with the aggregate euro area. Some major differences can be found, however, especially in the case of periphery and new member states, with the latter improving in terms of coherency after the global financial crisis. The German cycles are among the cyclical movements least synchronized with the aggregate euro area.

The purpose of this paper is to present novel recursive expressions for modelling the replacement costs of aircraft engine life-limited parts during shop visits to assist engine operators in both evaluating their decisions regarding the applied life-limited parts management strategies and tracking the replacement costs consistently throughout the life of the engine.

The replacement costs of aircraft engine life-limited parts are modelled analytically in this research, which strives to quantify the costs of used and unused lives of the replaced parts, incurred during engine shop visit events. Inputs for this model include the list price of life-limited parts, the replacement decisions made on all previous shop visits and the number of cycles the engine has operated at different thrust ratings on all previous operating intervals.

The average annual escalation rate of life-limited parts list prices was shown to range from 5% to 7%. The presented model is not only suitable for calculating the costs of used and unused lives of life-limited parts during past engine shop visit events but also for application in the life-limited parts replacement cost forecasting and optimisation models.

Uniquely derived recursive expressions represent the final result of the developed model which, to the authors’ knowledge, had not been studied elsewhere in the academic literature. The analysis of aircraft engine life-limited part list prices carried out to account for the average annual escalation rate enables the prediction of replacement costs during subsequent shop visits.

The purpose of this paper is to investigate the fatigue crack growth (FCG) under random loading using analytical methods.

For this purpose, two methods of cycle-by-cycle technique and central limit theorem (CLT) were used. The Walker equation was used to consider the stress ratio effect on the FCG rate. In order to validate the results in three random loading group with different loading levels and bandwidths, the results of the analysis, such as the mean lifetime of the specimen and the average crack length were compared with the test results in terms of the number of loading cycles.

The comparison indicated a good agreement between the results of the analysis and the test. Further, the diagrams of reliability and the probability of failure of the specimen were obtained for each loading group and were compared together.

Applying the cycle-by-cycle and CLT methods for the calculation of fatigue reliability of a CT specimen under random loading by the Walker equation and comparing their results with each other is not observed in other researches. Also in this study, the effect of the loading frequency bandwidth on lifetime was studied.

The scope of the work is to provide an identification procedure for an hysteresis model based on nonlinear circuit cells.

An identification procedure for an hysteresis model based on nonlinear circuit cells is presented. The response of elementary cell is equal to a generalized play operator. The procedure allows the identification of the limit symmetric hysteresis loop and of minor loops. The identification procedure is based on the relationship between the circuit parameters and the discretization of the first derivative of the BH curve by means of a staircase function.

The model obtained is employed for the simulation of soft magnetic composite material cores under different supply voltage waveforms. The proposed identification procedure is able to define an accurate model of an hysteretic material with a low number of elemental network cells. The identification algorithm is simple and makes use of the limit hysteresis cycle only. Symmetric minor loops are used to tune “soft” operators for the correct reconstruction of cycles which do not reach saturation.

The model is limited to scalar and static hysteresis model.

The model obtained can be used in network simulator like SPICE in order to model circuits in which magnetic devices are involved.

The circuit hysteresis model has been presented in literature, while its identification is newly proposed by the authors.

This study uses parametric hazard models to investigate duration dependence in US stock market cycles over the January 1929 through December 1992 period. Market cycles are determined using the Beveridge‐Nelson (1981) approach to the decomposition of economic time series. The results show that both real and nominal cycles exhibit positive duration dependence. The implication of this finding is that actual prices revert to their permanent or trend level in a non‐random manner as the cyclical component dissipates over time. This process is consistent with mean reversion in price and suggests that predictable periodicity in market cycles may exist. Only limited evidence is obtained that discrete shifts or trends in mean cycle duration exist. The length of market cycles appears not to have changed over the 1929–92 period.

Decision makers and authorities largely ignore cycling when conceptualising and developing programmes to support older mobility and therefore, unsurprisingly, levels of cycling in the United Kingdom are low compared to other northern European nations. Cycling has the potential to play an important role in the active ageing agenda and provide older citizens with a form of independent mobility that enhances personal health and wellbeing. The chapter provides evidence of the important role cycling does and could play in older people’s mobility and outlines ways in which older cycling could be supported and promoted.

Campaign contributions are typically seen as a strategic investment for firms; recent empirical evidence, however, has shown few connections between firms’ contributions and regulatory or performance improvements, prompting researchers to explore agency-based explanations for corporate politics. By studying intrafirm campaign contributions of CEOs and political action committees (PACs), we investigate two hypotheses related to public politics and demonstrate that strategic and agency-based motivations may hold simultaneously. Exploiting transaction-level data, with over 6.8 million observations, we show that (i) when PACs give to specific candidates, executives give to the same candidates, especially those who are strategically important to the firm; and (ii) when executives give to candidates who are not strategically important, PACs give to the same candidates potentially due to agency problems within the firm.