Showing papers on "Transfer function published in 1986"
TL;DR: In this paper, a model reference adaptive control algorithm is proposed to provide robust stability of the resulting closed-loop adaptive control system with respect to unmodeled plant uncertainties, which is achieved by using a relative error signal in combination with a dead zone and a projection in the adaptive law.
Abstract: We propose a new model reference adaptive control algorithm and show that it provides the robust stability of the resulting closed-loop adaptive control system with respect to unmodeled plant uncertainties. The robustness is achieved by using a relative error signal in combination with a dead zone and a projection in the adaptive law. The extra a priori information needed to design the adaptive law, are bounds on the plant parameters and an exponential bound on the impulse response of the inverse plant transfer function.
386 citations
TL;DR: The use of an auxiliary random noise generator for this modeling is described, which is easy to implement, provides continuous on‐line modeling, and has minimal effect on the final value of the error signal.
Abstract: Active sound attenuation systems may be described using a system identification framework in which an adaptive filter is used to model the performance of an unknown acoustical plant. An error signal may be obtained from a location following an acoustical summing junction where the undesired noise is combined with the output of a secondary sound source. In order for the model output to properly converge to a value that will minimize the error signal, it is frequently necessary to determine the transfer function of the secondary sound source and the path to the error signal measurement. Since these transfer functions are continuously changing in a real system, it is desirable to perform continuous on‐line modeling of the output transducer and error path. In this paper, the use of an auxiliary random noise generator for this modeling is described. Based on a Galois sequence, this technique is easy to implement, provides continuous on‐line modeling, and has minimal effect on the final value of the error signal.
304 citations
Book•
01 Jan 1986TL;DR: This book discusses linearized Dynamic Models, transfer function models of Physical Systems Modeling of Feedback Systems and Controllers, and Multivariable Systems in the Frequency Domain Nonlinear Control Systems.
Abstract: Introduction and Linearized Dynamic Models Transfer Function Models of Physical Systems Modeling of Feedback Systems and Controllers The Performance of Feedback Systems Introduction to Feedback System Design The Root Locus Method Frequency Response Analysis Frequency Response Design Digital Control Systems Digital Control System Analysis and Design State-Space Analysis Introduction to State-Space Design Multivariable Systems in the Frequency Domain Nonlinear Control Systems Appendix A: Vectors, Matrices, and Determinants Appendix B: Computer Aids for Analysis and Design References Index
221 citations
TL;DR: In this article, two efficient algorithms for frequency response and eigenvalue estimation are presented. But they are not suitable for the analysis of small signal stability of multimachine power systems.
Abstract: Frequency response and eigenvalue techniques are fundamental tools in the analysis of small signal stability of multimachine power systems. This paper describes two highly efficient algorithms which are expected to enhance the practical application of these techniques. One algorithm calculates exact eigenvalues and eigenvectors for a large power system, while the other produces the frequency response of the transfer functions between any two variables in the system. This paper also presents alternative computing procedures for the AESOPS eigenvalue estimation algorithm which are simpler and at least as efficient as those described in [1].
195 citations
TL;DR: In this article, the transfer function sensitivity of state-space systems with respect to value and parameter perturbations is defined and a general relation to the variance of the weighted output noise can be obtained in the case of a perturbed realization which is l 2 -scaled under a general non-white input process.
Abstract: This paper contains new measures to describe the transfer function sensitivity of state-space systems with respect to value and parameter perturbations. These measures are related to the newly defined generalized Gramian matrices. The value respecting the parameter variations contains the sensitivity at discrete frequency points, pole and zero sensitivities and the integral sensitivity as special cases. A general relation to the variance of the weighted output noise can be obtained in the case of a perturbed realization which is l_2 -scaled under a general non-white input process. The complete class of representations with minimum sensitivity and noise is given. The corresponding necessary and sufficient conditions lead to an analytic design of optimal state-space systems.
168 citations
TL;DR: A new implementation of an IIR digital filter transfer function is presented that is structurally passive and, hence, has extremely low pass-band sensitivity.
Abstract: A new implementation of an IIR digital filter transfer function is presented that is structurally passive and, hence, has extremely low pass-band sensitivity. The structure is based on a simple parallel interconnection of two all-pass sections, with each section implemented in a structurally lossless manner. The structure shares a number of properties in common with wave lattice digital filters. Computer simulation results verifying the low-sensitivity feature are included, along with results on roundoff noise/dynamic range interaction. A large number of alternatives is available for the implementation of the all-pass sections, giving rise to the well-known wave lattice digital filters as a specific instance of the implementation.
167 citations
TL;DR: In this article, the stabilization of a linear system modelled as (G + A) where G is a known rational transfer function and A is a perturbation satisfying |W,A2|∞ (G1) ≥σ or equivalently there does not exist G with fewer poles in C+ than G such that |W1(G −G)W2| ∞.
Abstract: The stabilization of a linear system modelled as (G + A) where G is a known rational transfer function and A is a perturbation satisfying |W,A2|∞ (G1) ≥σ or equivalently there does not exist G with fewer poles in C+ than G such that |W1(G −G)W2|∞.A simple characterization of all robustly stabilizing controllers is then derived and state-space formulae for maximally robust controllers are given. Finally reduced-order controllers are considered.
150 citations
TL;DR: In this paper, a statistical method for modeling the linear and quadratically nonlinear relationship between fluctuations monitored at two points in space or time in a turbulent medium is presented, which is valid for non-Gaussian "input" and "output" signals.
92 citations
TL;DR: This paper is concerned with the realization of a given arbitrary filter transfer function as a network of resistively interconnected integrators using a new technique called intermediate function (IF) synthesis, based on the selection of a set of functions to serve as either the transfer functions from the filter input to the integrator outputs or the transfer function from the Integrator inputs to the filter output.
Abstract: This paper is concerned with the realization of a given arbitrary filter transfer function as a network of resistively interconnected integrators. These state-space realizations are synthesized using a new technique called intermediate function (IF) synthesis. The technique is based on the selection of a set of functions to serve as either the transfer functions from the filter input to the integrator outputs or the transfer functions from the integrator inputs to the filter output. Relationships between the filter sensitivity and dynamic range and the intermediate functions are derived. A number of results are also given to aid in the selection of a set of IF's that yields structures with optimum performance.
89 citations
TL;DR: A class of nonrecursive cascaded-lattice structures is derived, for the implementation of finite-impulse response (FIR) digital filters, which have excellent passband sensitivity and are automatically internally scaled, in an L_2 sense.
Abstract: A class of nonrecursive cascaded-lattice structures is derived, for the implementation of finite-impulse response (FIR) digital filters. The building blocks are lossless and the transfer function can be implemented as a sequence of planar rotations. The structures can be used for the synthesis of any scalar FIR transfer function H(z) with no restriction on the location of zeros; at the same time, all the lattice coefficients have magnitude bounded above by unity. The structures have excellent passband sensitivity because of inherent passivity, and are automatically internally scaled, in an L_2 sense. The ideas are also extended for the realization of a bank of M FIR transfer functions as a cascaded lattice. Applications of these structures in subband coding and in multirate signal processing are outlined. Numerical design examples are included.
78 citations
TL;DR: In this paper, closed-form expressions for amplitude-oriented low-pass, high-pass and bandpass sampled-data transfer functions suitable for realization as 1) switched-capacitor lossless discrete integrator (LDI) ladder filters, or 2) wave digital filters.
Abstract: Closed-form expressions are presented for amplitude-oriented low-pass, high-pass, and bandpass sampled-data transfer functions suitable for realization as 1) switched-capacitor lossless discrete integrator (LDI) ladder filters, or 2) wave digital filters. Other types of realizations are also possible, such as those employing voltage inverter switches (VIS's), the recently introduced switched-capacitor "voltage wave" filters, and standard recursive digital realizations. The filters possess optimum equirippie (or maximally flat) passbands and monotonic stopbands with arbitrary selectivity. The low-pass and high-pass cases are derived from distributed passive prototype functions, but the more important bandpass functions are quite novel, appearing here for the first time.
TL;DR: The averaging process is modeled as a linear system whose low-pass filter characteristics are determined by the degree in temporal misalignment of signals, which demonstrates that alignment errors can both add and subtract signal components.
Abstract: The averaging process is modeled as a linear system whose low-pass filter characteristics are determined by the degree in temporal misalignment of signals. Assuming the errors in temporal alignment of successive cardiac cycles are random, then the model transfer function is equivalent to the probability density function. The response of the model to a step input is equivalent to the probability distribution function, which can be readily quantified. To validate the model, a high resolution ECG amplifier and QRS recognition system was constructed that synchronizes a step input with a point on the QRS. Design criteria for optimal amplification, filtering, and triggering of the ECG are determined. Test of the model reveals a close correspondence between observed and predicted step responses. From the average step response, the recording fidelity of any average can be determined-rapidly while the alignment is adjusted for optimal precision. Using ECG signals from patients, our model system demonstrates that alignment errors can both add and subtract signal components. Methods for estimating the extent of signal distortion induced by averaging as well as criteria for minimizing it are presented.
Patent•
10 Jun 1986TL;DR: An SSB signal demodulator comprising an analog bandpass filter for band-limiting such signal, an analog-to-digital converter 20 for digitizing the band-limited signal, and a pair of quadrature related decimating filters (28, 29) are applied to a Hilbert transform pair (30, 31).
Abstract: An SSB signal demodulator comprising an analog bandpass filter for band-limiting such signal, an analog-to-digital converter 20 for digitizing the band-limited signal, and a pair of quadrature related decimating filters (28, 29) for deriving quadrature related decimated signals therefrom which are applied to a Hilbert transform pair (30, 31). The upper or lower sideband signal is obtained by taking the sum or difference of the outputs of the Hilbert transform pair, and the resulting digital signal is reconverted to an analog signal. By using a decimation factor which is an odd numbered integer greater than 1, the periodic transfer function of the demodulator has alternate passbands and stopbands. This relaxes the performance requirements of the analog filter and of the Hilbert transform pair, and greatly enhances the adjacent channel selectivity of the demodulator.
TL;DR: The sensitivity of state-space digital filters is shown to depend on the second-order modes thereby exhibiting certain robustness and immunity to filter bandwidth.
Abstract: In this paper, we examine the sensitivity of state-space digital filters to coefficient quantization errors. A cost function using an L p norm criteria is used to measure the deviation in frequency response of the filter. The cost function is used to indicate the connection between roundoff noise and filter sensitivity to coefficient quantization errors. Then based on this cost function it is shown that low roundoff noise state-space digital filters, filters in balanced coordinates, and filters based on polynomials orthogonal on the unit circle have low sensitivity to coefficient quantization errors. Furthermore, the sensitivity of the filters is shown to depend on the second-order modes thereby exhibiting certain robustness and immunity to filter bandwidth.
TL;DR: In this article, data takes on two ascending orbits of the Shuttle Imaging Radar-B (SIR-B) over an agricultural test site in west-central Illinois were used to establish end-to-end transfer functions for conversion of the digital numbers on the 8-bit image to values of the radar backscattering coefficient?0 (m2/m2) in dB.
Abstract: Data takes on two ascending orbits of the Shuttle Imaging Radar-B (SIR-B) over an agricultural test site in west-central Illinois were used to establish end-to-end transfer functions for conversion of the digital numbers on the 8-bit image to values of the radar backscattering coefficient ?0 (m2/m2) in dB. The transfer function for each data take was defined by the SIR-B response to an array of six calibrated point targets of known radar cross section (transponders) and to a large number of area-extended targets also with known radar cross section as measured by externally calibrated, truck-mounted scatterometers. The radar cross section of each transponder at the SIR-B center frequency was measured on an antenna range as a function of the local angle of incidence. Two truck-mounted scatterometers observed 20-80 agricultural fields daily at 1.6 GHz with HH-polarization and at azimuth viewing angles and incidence angles equivalent to those of the SIR-B. The form of the transfer function is completely defined by the SIR-B receiver and the incoherent averaging procedure incorporated into production of the standard SIR-B image product. Assuming that the processing properly accounts for the antenna gain, all transfer function coefficients are known except for the thermal noise power and a system " constant" that has been shown to vary as a function of uncommanded changes in the effective SIR-B transmit power.
01 Jan 1986
TL;DR: In this paper, the mean square error of transfer function estimates obtained by identification is studied, and model quality is related to the use of models in regulator design, and the properties of model properties.
Abstract: In this report we study the mean square error of transfer function estimates obtained by identification. The model quality is related to the use of models in regulator design, and the properties of ...
TL;DR: In this article, a comprehensive method for obtaining reduced-order models of a scalar linear time-invariant system described by the transfer function G(s) is proposed, which is a viable alternative to the Pade approximation technique for model order reduction.
Abstract: A comprehensive method is proposed for obtaining reduced-order models of a scalar linear time-invariant system described by the transfer function G(s). The method is a viable alternative to the Pade approximation technique for model order reduction. It approximates the differential operations d i G(s)/dsi (proportional to the time moments) by the divided-difference equivalents and finally leads to linear equations in the unknown coefficients of the reduced model R(s). It is shown that a parameter δ governs the stability and the low-frequency matching quality of the model. Heuristic criteria are given for selecting a proper δ. The method is illustrated by some examples from the literature.
TL;DR: Use of certain types of pseudorandom input stimuli to identify linear transfer function models of biological or physiological systems can lead to bias errors if the system is nonlinear, and use of the coherence function to assess the linearity of the system may yield misleading results.
Abstract: Use of certain types of pseudorandom input stimuli to identify linear transfer function models of biological or physiological systems can lead to bias errors if the system is nonlinear. Moreover, use of the coherence function to assess the linearity of the system may yield misleading results. Results from a computer simulation are presented, along with example experimental data.
TL;DR: In this paper, the authors derived the transfer function of a frequency-domain system, and the step and impulse response functions of ideal time-domain EM systems (TEM) in terms of a single set of target-specific parameters.
Abstract: Electromagnetic (EM) exploration systems fall into three distinct classes, (1) frequency domain, (2) impulse response, and (3) step response, and have overall frequency responses that approximate f+1, f0, and f-1. To examine further these three classes, the transfer function of a frequency‐domain system, and the step and impulse response functions of ideal time‐domain EM systems (TEM), are derived in terms of a single set of target‐specific parameters. The inductive time constants of practical exploration targets extend over three orders of magnitude, imposing severe constraints on practical exploration systems. Field data demonstrate that the impulse TEM response from a conductive half‐space may show a 100‐fold spatial variability at early times (≲1 ms) and then will decrease to a two‐fold variability at late times ( ⩾4 ms). This differential variability influences the ability of an EM system to detect an exploration target. For a half‐space where the impulse response varies as t-k, an inductive target o...
01 Jan 1986
TL;DR: It has been observed that the quality of synthesized speech can be improved, if a more detailed model than an impulse train is used for the pitch pulses, and it is here shown how the method presented can be used to estimate the system parameters of the speech production and the parameters ofThe glottal pulse simultaneously.
Abstract: Part IA new approach to identification of time varying systems is presented, and evaluated using computer simulations. The new approach is built upon the similarities between recursive least squares identification and Kalman filtering.The parameter variations are modelled as process noise in a state space model and then identified using adaptive Kalman filtering. A method for adaptive Kalman filtering is derived and analysed. The simulations indicate that this new approach is superior to previous methods based on adjusting the forgetting factor. This improvement is however gained at the price of a signification increase in computational complexity.Part IIIn this part we apply parameter estimation to the problem of transmission line protection.One approach based on recursive least squares identification is presented. The method has ben tested using simulated data generated by the program EMTP.Another approach based on the theory of travelling waves is also discussed.Part IIIIn this part a method for input estimation or deconvolution is presented. The basis of the method is to use a parametrized model the input signal. To use the method we should thus be able to express the input signal as a function of some unknown parameters and time. The algorithms simultaneously estimates the parameters of the input signal and the parameters of the system transfer function. The presentation here is restricted to transfer functions of all pole type, i.e. ARX-models. The method can be extended to handle zeros in the transfer function. The computational burden would however increase significantly. The algorithm uses efficient numerical methods, as for instance QR-factorization thorugh Householder transformation.The algorithm is in this paper applied to a problem in speech coding. It has been observed that the quality of synthesized speech can be improved, if a more detailed model than an impulse train is used for the pitch pulses, see Fant (1980). It is here shown how the method presented in this paper can be used to estimate the system parameters of the speech production and the parameters of the glottal pulse simultaneously.
01 Jan 1986
TL;DR: The simplest methods of determining J, given G, or vice versa, are based on the use of Laplace transforms as discussed by the authors, which find a variety of other applications in connection with viscoelasticity theory.
Abstract: The simplest methods of determining J, given G, or vice versa, are based on the use of Laplace transforms. Fourier and Laplace transforms also find a variety of other applications in connection with viscoelasticity theory. Let us briefly review these transform methods.
TL;DR: In this paper, the classic technology of the saturable core may be combined with the microcomputer to yield an improved version of the magnetic flux-gate compass, with application to mass-produced automobiles.
Abstract: The classic technology of the saturable core may be combined with the microcomputer to yield an improved version of the magnetic flux-gate compass. General description and fundamental principles are discussed with application to mass-produced automobiles. A transfer function between the earth's magnetic field and the fluxgate output voltages is developed. The introduction of the microcomputer allows a faster calibration which does not require any type of nulling or feedback circuit.
01 Jul 1986
TL;DR: In this article, a solution to the problem of detecting and identifying control system component failures in linear time-invariant systems is given using the geometric concept of an unobservability subspace.
Abstract: : A solution to the problem of detecting and identifying control system component failures in linear time-invariant systems is given using the geometric concept of an unobservability subspace. Conditions are developed under which it is possible to design a causal linear processor that can be used to detect and uniquely identify a component failure in a linear time-invariant system, assuming either i) the components can fail simultaneously, or ii) the components can fail only one at a time. Explicit design algorithms are provided when those conditions are satisfied. In addition to the time domain solvability conditions, the frequency domain interpretation of the results are given, and connection is drawn with the results already available in the literature.
TL;DR: A multi-DSP hardware system is outlined which is specifically designed for implementing the multipath structures discussed here, which are specifically suitable for implementation using a number of Digital Signal Processors (DSP).
Abstract: A multipath signal processing scheme is proposed to overcome the limitation on the throughput rate of present day available LSI devices which is specifically suitable for implementation using a number of Digital Signal Processors (DSP). Two methods are proposed to realize a given transfer function H(z) of digital filter, with a throughput rate speed up factor of N , over the conventional methods. The first method, called Delayed Multipath Approach here, uses an N -path structure as a building element. These N elements are connected successively with increasing delay units to realize a given transfer function. The second method preprocesses the input signal sequence by an FFT processor and follows it up by N of constituent transfer functions derived from H(z) having real coefficients. The output of these N constituent transfer functions are finally postprocessed by inverse FFT processor to obtain the desired output signal. The number of the constituent transfer functions are double for a special case when the transfer function to be implemented has complex valued coefficients. These two methods serve as complementary approaches, because the first method is better suited for small values of the speed-up factor N and the second one has distinct advantage for larger values of N . The discussion of the first design method is organized in two parts: FIR filter design and IIR filter design, for each of which 2-path and N -path structures are separately explained. The second design method is discussed under the headings of real transfer function and complex transfer function. Design examples are also given to illustrate both of these two methods. Finally, a multi-DSP hardware system is outlined which is specifically designed for implementing the multipath structures discussed here.
TL;DR: In this article, the necessary conditions of structural classification are developed by the Volterra and Wiener theories and correlation analysis, and some formulae for discriminating the feedback non-linear system's structure are newly developed.
Abstract: It is desirable to know the internal structure of a non-linear system that is regarded as a 'black box'. The structural classification of the 'black box' is made from input and output relations. In this paper, the necessary conditions of structural classification are developed by the Volterra and Wiener theories and correlation analysis. A class of non-linear models in cascade is described by cross-correlation functions and Volterra and Wiener kernels. These conditions are first discussed in the frequency domain. Then the formulae of the conditions for structural identification in the time domain are obtained. Further, relations between structural information and the kernels are developed. Simulations are carried out that verify the authors' methods of structural testing. Next, some formulae for discriminating the feedback non-linear system's structure are newly developed. Furthermore, it is shown that the linear subsystem transfer functions and the non-linear subsystem parameters for these feedback non-l...
TL;DR: This new text is a substantially enlarged and revised version of Professor Chen's earlier book on linear systems, which is a balanced and comprehensive treatment of all the useful concepts from both state space and frequency domain approaches for the analysis and design of linear control systems.
TL;DR: A structure to realize a first-order two-dimensional all-pass transfer function with five multipliers and two delays with real multipliers is proposed and the multipliers of the proposed structure are shown to be real for stable filters.
Abstract: A structure to realize a first-order two-dimensional all-pass transfer function with five multipliers and two delays has been proposed This has been achieved by modifying the signal flowgraph of an existing structure which uses six multipliers and two delays The multipliers of the proposed structure are shown to be real for stable filters
TL;DR: In this article, the class of all stabilizing controllers for a two-degree-of-freedom control system which achieve a prescribed achievable transfer function is characterized, and robust model matching is formulated as a standard Hm-optimization problem.
TL;DR: The modeling principles used in NUFREQ-NP to describe the transient two-phase flow and heat transfer phenomena are presented and comparisons indicate very good agreement between the calculated and measured system transfer functions.