IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 51, NO. 5, OCTOBER 2004 981
Neural-Network-Based Waveform Processing and
Delayless Filtering in Power Electronics
and AC Drives
Jin Zhao and Bimal K. Bose, Life Fellow, IEEE
Abstract—This paper systematically explores the static non-
linear mapping property of feedforward neural networks for
various waveform processing and delayless filtering that are
applicable to power electronics and ac drives area. Neural-net-
work-based processing of waves gives considerable simplification
of hardware and/or software that are traditionally used for such
applications. Two general cases have been investigated: The
voltage or current waveforms which have constant frequency but
variable magnitudes, and the other case is variable-frequency
variable-magnitude voltage or current waves. The former case is
mainly important for power electronics that operate on a utility
system and general-purpose constant-frequency converter power
supplies, and the latter is important for the adjustable-speed
ac drives area. In both cases, the performance of neural-net-
work-based waveform processing and delayless filtering with
offline training was found to be excellent. The results of this study
are also applicable to other areas of electrical engineering.
Index Terms—AC drives, delayless filtering, neural network,
power electronics, waveform processing.
I. INTRODUCTION
P
OWER electronics and variable-frequency drive systems
often deal with complex voltage and current waves that are
rich in harmonics. These waveforms often require complex pro-
cessing for control, monitoring, diagnostics, and protection of
the system. Normally, analog/digital hardware, software, or a
combination of both is required for processing these waves. One
of the important processing functions is predictive or delayless
filtering in order to retrieve the fundamental (sine wave) compo-
nent of the wave. For example, a diode or thyristor phase-con-
trolled bridge converter, operating on a 60-Hz utility line, can
generate square or six-stepped line current wave, and this wave-
form becomes multistepped (more than six steps) with multiple
phase-shifted bridge converters on a three-phase line [1]. Sim-
ilar waveforms are also generated, respectively, in the output
voltage of a square-wave voltage-fed inverter with single bridge
or phase-shifted multibridge configuration. The harmonic-rich
line current and output voltage waves can again cause distor-
tion in the line voltage and load current waves, respectively.
Manuscript received January 12, 2004; revised June 22, 2004. Abstract pub-
lished on the Internet July 15, 2004.
J. Zhao was with the Department of Electrical Engineering, The University
of Tennessee, Knoxville, TN 37996-2100 USA, on leave from the Department
of Automatic Control Engineering, Huazhong University of Science and Tech-
nology, Wuhan 430074, China (e-mail: zhao2000617@yahoo.com.cn).
B. K. Bose is with the Department of Electrical Engineering, The University
of Tennessee, Knoxville, TN 37996-2100 USA (e-mail: bbose@utk.edu).
Digital Object Identifier 10.1109/TIE.2004.834949
It is often necessary to retrieve the fundamental component of
these waves in order to calculate, for example, the displacement
power factor (DPF), fundamental frequency active (P) and reac-
tive power (Q), and energy measured by a kilowatthour meter. In
photovoltaic and wind generation systems coupled to the grid,
the distorted line voltage (due to converter harmonics) waves
require delayless filtering in order to generate inverter sine ref-
erence voltage waves for controlling the line DPF to unity [2],
[3]. The distorted line voltage waves also create problems in
the comparator (or zero-crossing detector) which is often es-
sential for control of the converter (e.g., cosine-wave-crossing
control of a phase-controlled converter). Generally, an active-
or passive-type low-pass filter (LPF) with narrow bandwidth is
used to filter out the harmonic components. However, an LPF
causes phase lag and amplitude attenuation that vary with fun-
damental frequency. For a utility system, the fundamental fre-
quency is essentially constant and, therefore, these phase and
amplitude errors can be compensated without much difficulty
[2]. However, for variable-frequency drive applications, the in-
verter usually operates in pulsewidth-modulation (PWM) mode
with wide frequency variation generating machine voltage and
current waves that are complex with harmonics. If a simple LPF
with narrow bandwidth is used in these applications, the vari-
able phase delay and amplitude attenuation for the fundamental
may not be acceptable, particularly at higher fundamental fre-
quency. The phase error is particularly harmful in a vector-con-
trolled drive where it creates the coupling problem and, thus,
deteriorates the drive performance. In the past, complex dig-
ital adaptive filters, such a finite-impulse response (FIR), infi-
nite-impulse response (IIR), or a combination of both have been
proposed [3]–[5] to obtain delayless filtering of the fundamental
component.
In this paper, we propose the neural network solution for
waveform processing and delayless filtering problems. The arti-
ficial neural network (ANN), or neural network, a generic form
of artificial intelligence (AI), is recently offering a new frontier
in solving many control, estimation, and diagnostic problems in
power electronics and motor drives. Between the two classes of
ANN, i.e., the feedforward and feedback or recurrent types, the
former provides static nonlinear input–output mapping or pat-
tern recognition property with precision interpolation capability.
With appropriate training, this property permits a feedforward
ANN to recognize a waveshape and retrieve the desired compo-
nent of the wave. Since the shape or pattern of the wave remains
constant or goes through deterministic variation, simple offline
training of the network has been used in the project. The advan-
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