A method of phase retrieval based on windowed Fourier transform has been proved to be one of the most effective
algorithms for carrier fringe patterns. The calculation speed of windowed Fourier transform ridge (WFTR) is time
consuming. The accuracy and calculation speed of phase retrieval using WFTR depend on the scanning frequency
interval, but how to determine a proper frequency interval is still a problem. In this paper we see WFTR as a response of
a linear time-invariant system. Then we calculate the system response function by means of numerical analysis, finding
that there is always an area of zero phase response near the local frequency and its width nearly equals to the width of the
main lobe of the amplitude response function. This means a system response function with bigger main lob width and
fast decay rate allows a bigger frequency interval and less calculation times. These operations only increase a little error
at the edge of the fringe pattern, but give a fast calculation speed. Finally we compare the carried fringe pattern phase
with a standard phase extracted by the four-step phase-shifting algorithm.
With the particle swarm optimal (PSO) algorithm, an adaptive fuzzy logic controller (AFC) based on interval fuzzy
membership functions is proposed for vehicle non-linear active suspension systems. The interval membership functions
(IMFs) are utilized in the AFC design to deal with not only non-linearity and uncertainty caused from irregular road
inputs and immeasurable disturbance, but also the potential uncertainty of expert's knowledge and experience. The
adaptive strategy is designed to self-tune the active force between the lower bounds and upper bounds of interval fuzzy
outputs. A case study based on a quarter active suspension model has demonstrated that the proposed adaptive fuzzy
controller significantly outperforms conventional fuzzy controllers of an active suspension and a passive suspension.
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