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.

Hysteresis switching adaptive control of linear multivariable systems

Abstract: This paper presents a model reference adaptive control scheme for deterministic continuous-time multivariable systems represented by square, strictly proper, minimum-phase transfer function matrices A typical requirement of existing algorithms is to assume that the zero structure at infinity and the high-frequency gain matrix are fully (or at least partially) known It is well known that these requirements may be very restrictive, since, in general, both the zero structure at infinity and the high-frequency gain matrix depend on plant parameters In this paper we show that these restrictive assumptions may be considerably weakened using Morse et al's hysteresis switching control strategy (1992) The strategy entails running a finite number of parameter estimators in parallel and using a switching algorithm to select between candidate estimators based on their associated prediction errors Hysteresis in the switching algorithm precludes switching arbitrarily rapidly between estimators, and all switching ceases within a finite time The results represent a significant step forward in understanding the minimal amount of prior knowledge necessary to design a stabilizing controller for a linear multivariable system >

System and method for transient response and accuracy enhancement for sensors with known transfer characteristics

Abstract: A parameter of interest being measured by a sensor is estimated from output response data from the sensor and the known transfer function of the sensor, allowing fast and accurate sensor data from sensors having a dynamic characteristic otherwise precluding assessment of the sensor input. A parameter of breathing gas from a ventilator is determined based upon the known transfer function and a plurality of the sensor output signals at predetermined intervals of time, to provide an estimation of the parameter of interest.

Review of inverse Laplace transform algorithms for Laplace-space numerical approaches

Abstract: A boundary element method (BEM) simulation is used to compare the efficiency of numerical inverse Laplace transform strategies, considering general requirements of Laplace-space numerical approaches. The two-dimensional BEM solution is used to solve the Laplace-transformed diffusion equation, producing a time-domain solution after a numerical Laplace transform inversion. Motivated by the needs of numerical methods posed in Laplace-transformed space, we compare five inverse Laplace transform algorithms and discuss implementation techniques to minimize the number of Laplace-space function evaluations. We investigate the ability to calculate a sequence of time domain values using the fewest Laplace-space model evaluations. We find Fourier-series based inversion algorithms work for common time behaviors, are the most robust with respect to free parameters, and allow for straightforward image function evaluation re-use across at least a log cycle of time.

Transfer function identification in power system applications

Abstract: The authors present an introduction to concepts and applications of transfer function identification in power systems. They begin with a brief introduction to transfer function identification methods using least-squares approaches and then discuss applications which include static VAR compensators, model validation applications, and software validation. A comparison is also made between eigenvalues obtained from transfer function identification and small signal analysis. Methods for testing the validity of identified transfer functions are also discussed. >