| Summary: | 碩士 === 國立交通大學 === 控制工程系 === 84 === In recent years, with the widespread use of the digital
computers,the main control techniques and system identification
methods for the continuous-time systems have been
discretized. Moreover, we may raise the sampling rate to
achieve a better control performance. However, since of the
finite word length effect in practical computation, high
sampling rate and/or a large number of estimation parameters
will result in numerical errors for the usual least squares
estimation based on shift model. On the other hand,if the pure
time-lag occurs in the identification process and that is
not taken into consideration at estimation model,the influence
on the estimated results will be serious as the sampling rate
increases. In this thesis, we take the delta operator to
formulate discrete-time model. From hardware experiments, the
results show that the delta model is numerically superior to
the usual shift model under high sampling rate and/or for a
large number of estimation parameters. Also, we have shown
that the accuracy of estimated delta model improves as
sampling rate increases. Moreover, we propose a new
identification method to estimate the continuous-time system
with unknown time-lag which is shorter than one sampling
interval. The simulation and experimental results conform that
our algorithm. Our identification methods are valuable in
adaptive control, system monitoring, etc.
|
|---|
