英文文档

Neural Network-based Correction and

Interpolation of Encoder Signals for Precision

Motion Control

Kok-Zuea Tang*, Kok-Kiong Tant , Tong-Heng Leet and Chek-Sing Teos

*t@ Department of Electrical and Computer Engineering Faculty of Engineering,

National University of Singapore

Email:*eletkz@nus.edu.sg, teletankk@nus.edu.sg, teleleeth@nus.edu.sg, ~g0301472@nns.edu.sg

Abstract-Precision control is the core of many ap plications in the industry, particularly robotics and drive control. To achieve it, precise measurement of the signals generated by incremental encoder 6ensors is essential. High precision and resolution motion control relies critically on the precision and resolution achievable from the encoders. In this paper, a dynamic neural network-based approach for the correction and interpolation of quadrature encoder signals is developed. In this work, the radial basis functions (RBF) neural network is employed to carry out concurrently the correction and interpolation of encoder signals in real- time. The effectiveness of the proposed approach is verified in the simulation results provided.

I. INTRODUCTION

In precision control, it is desirable to improve the

resolution and accuracy of the overall control system.

One way to achieve this aim is to improve the precision

of the encoders used. However, the current state of the

manufacturing technology of the encoders limits the

achievable precision of encoders. Specifically, the scale

grating on linear optical encoders can be manufactured

to less than four micrometers in pitch, but clearly,

further reduction in pitch will be greatly constrained

by physical considerations. This implies an optical resolution of one micrometer can be currently achiev-

able. Interpolation using soft techniques provides an

interesting possibility to further improve on the encoder

resolution, by processing the analog encoder signals

online to derive the small intermediate positions.

The error sources associated with positional in-

formation obtained this way can he classified under

pitch and interpolation errors. Pitch errors arise mainly

due to scale manufacturing tolerances and mounting

distortion. They can be compensated via the same prc+

cedures which are carried out for general geometrical

error compensation. Interpolation errors, on the other

hand, are associated with the accuracy of subdivision

within a pitch. Ideal signals from encoders are a pair of

sinusoids with a quadrature phase difference between

them. Interpolation operates on the relative difference

in the amplitudes and phases of these paired sinusoids.

Therefore, interpolation errors will occur if the pair-

periodic signals deviate from the ideal waveforms on

which the interpolation computations are based. These deviations must be corrected before interpolation.

One possible approach to compensate the mean

value offset, phase and amplitude errors for two quadra-

ture sinusoidal signals was introduced by Heydemann

[l]. He used least squares fitting to compute these

error components efficiently and made correction for

two non-ideal sinusoidal signals. Using this method,

Birch (21 was able to calculate optical fringe fractions to

nanometric accuracy. By making use of the amplitude

variation with angle, Birch divided one period of sinu-

soidal signal into N equiangular segments to increase

the effective electrical angle resolution. A micro step

controller [3] and encoder code compensation technol- ogy [4] have been developed based on this method.

Relevant applications can also be found in [5] and [6].

To increase the resolution of optical encoders, Cheung

171 used logic gates, comparators and digital filters to perform the sinelcosine interpolation. This method

employed hardware, complemented with some software

programming to achieve its results. An absolute high

performance, self calibrating optical rotary positioning

system was designed by Madni et al. [E]. In this

approach, a series of sinelcosine signals from the en-

coders are digitised by high precision analog-tedigital

converters (ADCs) and interpolation and calibration is

performed by the digital signal processing programs.

Servostar’s [9] motor drives offers the ability to accept

signals from various feedback devices and encoders. These encoders provide analog-encoded motor position

data to the drive amplier. The advantage of these

analog signals is that they can be resolved to extremely

small intervals, providing a lot of data about the

motor shaft position while maintaining reasonable data

transmission rates. The disadvantage is that analog

signals are notably susceptible to noise pickup and