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.

Charge control: modeling, analysis and design

Abstract: There are many ways to use the inductor current of a PWM converter as part of its feedback control mechanism. A simple and widely used method is peak current-mode control which uses the instantaneous inductor current as part of the control signals. Charge control is a special type of current-mode control. It uses the integration of the on-time inductor current as the feedback control signal. The characteristics of charge control are studied. A complete small-signal analysis is performed for the control scheme. Subharmonic oscillation similar to that of peak current-mode control is found, and the relationship between subharmonic oscillation and the line/load condition of charge control is defined. Based on the analysis, design guidelines which guarantee the stability of the control system under given line and load ranges are proposed. The small-signal model was confirmed experimentally. >

Frequency response of sampled-data systems

Abstract: This paper introduces the concept of frequency response for sampled-data systems and explores some basic properties as well as its computational procedures. It is shown that 1) by making use of the lifting technique, the notion of frequency response can be naturally introduced to sampled-data systems in spite of their time-varying characteristics, 2) it represents a frequency domain steady-state behaviour, and 3) it is also closely related to the original transfer function representation via an integral formula. It is shown that the computation of the frequency response can be reduced to a finite-dimensional eigenvalue problem, and some examples are presented to illustrate the results.

An LED Model for Intensity-Modulated Optical Communication Systems

Abstract: Modulating the intensity of light-emitting diodes (LEDs) with analog signals, especially in the case of the bipolar optical orthogonal frequency-division-multiplexing (O-OFDM) signal, leads to significant signal degradation due to LED nonlinearity. The LED transfer function distorts the signal amplitude and forces the lower peaks to be clipped at the LED turn-on voltage. Additionally, the upper peaks are purposely clipped before modulating the LED to avoid chip overheating. The induced distortion can be controlled by optimizing the bias point or backing-off the average O-OFDM signal power. In this letter, a model that incorporates amplitude distortion and that provides a parameterized upper clipping is proposed. Through Monte Carlo simulations, the model can be used to determine the optimum bias point and to optimize the O-OFDM signal power. In this context, a novel concept of soft-clipping of the upper peaks is presented. It is shown that soft-clipping is an effective approach to reduce nonlinearity distortion and to enhance symbol error performance.

Deadtime compensation for nonlinear processes

Abstract: Many industrially important processes feature both nonlinear system dynamics and a process deadtime. Powerful deadtime compensation methods, such as the Smith predictor, are available for linear systems represented by transfer functions. A Smith predictor structure in state space for linear systems is presented first and then directly extended to nonlinear systems. When combined with input /output linearizing state feedback, this Smith-like predictor makes a nonlinear system with deadtime behave like a linear system with deadtime. The control structure is completed by adding an external linear controller, which provides integral action and compensates for the deadtime in the input/output linear system, and an open-loop state observer. Conditions for robust stability with respect to errors in the deadtime and more general linear unstructured multiplicative uncertainties are given. Computer simulations for an example system demonstrate the high controller performance that can be obtained using the proposed method.

Contributions to the model reduction problem

Abstract: A new method of model reduction is introduced based on the differentiation of polynomials. The reciprocals of the numerator and denominator polynomials of the high-order transfer function are differentiated suitably many times to yield the coefficients of the reduced order transfer function. An error analysis shows the accuracy of the method, and an eighth-order example illustrates it. The method is computationally very simple and is equally applicable to unstable and nonminimum phase systems.