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Mendel, J. M.

Publications and source records attributed to Mendel, J. M..

A fast approach to identification using deconvolution

In this paper, we propose a fast approach to impulse response and noise-variance identification for a finite-order, linear, time-invariant, single-input/single-output system, whose input driving noise is white (stationary or nonstationary) and measurement noise is stationary, white and Gaussian. Our algorithm is an iterative block component method that includes two stages, deconvolution and prediction-error identification. Experiences with our method indicate that it works well and saves about an order of magnitude in computation. Analyses and examples are given in this paper to support this claim.

Chi, C.-Y.

Invariant poles feedback control of flexible highly variable spacecraft.

Description of a technique for single-axis control of a model of a highly flexible space station. Active damping of lower frequency flexibility modes is employed. In the control technique, referred to as invariant poles feedback control, feedback gains are adjusted so that the closed-loop system characteristic equation is matched to that of a reference model. Hence closed-loop system poles will not move; they will be invariant (provided that bending frequencies and parameters can be identified accurately). This is accomplished by obtaining the system characteristic equation in closed form; equating respective coefficients between terms of like powers in s in the system and reference model characteristic equations; and solving for the feedback gains. The feedback gains are explicit functions of system plant parameters and the coefficients of the reference model characteristic equation, and are easily programmed for the digital computer.

Mendel, J. M.

Invariant poles feedback control of flexible, highly variable spacecraft.

This paper describes a technique for single-axis control of a model of a highly flexible Space Station. Active damping of lower frequency flexibility modes is employed. In the control technique, referred to as invariant poles feedback control (IPFC), feedback gains are adjusted so that the closed-loop system's characteristic equation is matched to that of a reference model; hence, closed-loop system's poles will not move - they will be invariant (provided bending frequencies and parameters can be identified accurately). This is accomplished by obtaining the system's characteristic equation in closed form; equating respective coefficients between terms of like powers in s in the system and reference model characteristic equations; and, solving for the feedback gains. The feedback gains are explicit functions of system plant parameters and the coefficients of the reference model's characteristic equation, and are easily programmed for the digital computer.

Mendel, J. M.

Computational requirements for a discrete Kalman filter.

Computational requirements - i.e., computing time per cycle (iteration) and required storage - which determine minimum sampling rates and computer memory size, were obtained as functions of the dimensions of the important system matrices for a discrete Kalman filter. Two types of measurement processing are discussed: simultaneous and sequential. It is shown that it is often better to process statistically independent measurements in more than one batch and then use sequential processing than to process them together via simultaneous processing.

Mendel, J. M.