Compensation of Interpolation Error for Look-Up Table-Based PMSM Control Method in Maximum Power Control

This paper proposes a compensation method for interpolation error of the maximum power control of a PMSM control system that generates current commands through a look-up table. A torque control system using a look-up table created through experiments has superior characteristics, such as control stability and torque accuracy, compared to a system that executes torque control via a linear controller based on modeling. However, it is impossible to generate information on all the currents for the output torque in the table. Therefore, because the data stored in the look-up table have a discrete characteristic, they are linearly interpolated to generate a current command for the torque command. However, the PMSM current trajectory is generally elliptical, which causes an error owing to linear interpolation, reducing the maximum output power. In particular, when the table data are insufficient, such as in the high-speed operation range, the reduced maximum output cannot be ignored. This paper proposes a compensation method for the interpolation error using two feedforward compensators and a PI controller, which was verified through experiments.

Oversampling Errors in Multimodal Medical Imaging Are Due to the Gibbs Effect

To analyze multimodal three-dimensional medical images, interpolation is required for resampling which—unavoidably—introduces an interpolation error. In this work we describe the interpolation method used for imaging and neuroimaging and we characterize the Gibbs effect occurring when using such methods. In the experimental section we consider three segmented three-dimensional images resampled with three different neuroimaging software tools for comparing undersampling and oversampling strategies and to identify where the oversampling error lies. The experimental results indicate that undersampling to the lowest image size is advantageous in terms of mean value per segment errors and that the oversampling error is larger where the gradient is steeper, showing a Gibbs effect.

Interpolation with Specified Error of a Point Series Belonging to a Monotone Curve

The paper addresses the problem of modeling a smooth contour interpolating a point series belonging to a curve containing no special points, which represents the original curve with specified accuracy. The contour is formed within the area of possible location of the parts of the interpolated curve along which the curvature values are monotonously increased or decreased. The absolute interpolation error of the point series is estimated by the width of the area of possible location of the curve. As a result of assigning each intermediate point, the location of two new sections of the curve that lie within the area of the corresponding output section is obtained. When the interpolation error becomes less than the given value, the area of location of the curve is considered to be formed, and the resulting point series is interpolated by a contour that lies within the area. The possibility to shape the contours with arcs of circles specified by characteristics is investigated.

Parameterized interpolation for fusion of multidimensional signals of various resolutions

Parameterized interpolation algorithms are adapted to fusion of multidimensional signals of various resolutions. Interpolating functions, switching rules for them and local features are specified, based on which the interpolating function is selected at each point of the signal. Parameterized interpolation algorithms are optimized based on minimizing the interpolation error. The recurrent interpolator optimization scheme is considered for the situation of inaccessibility of interpolated samples at the stage of setting up the interpolation procedure. Computational experiments are carried out to study the proposed interpolators for fusion of real multidimensional signals of various types. It is experimentally confirmed that the use of parameterized interpolators allows one to increase the accuracy of signal fusion.