Smith Prediction and Compensation Method Based on Sixth Order b-spline Wavelet Neural Network
A spline wavelet and neural network technology, applied in the direction of instruments, adaptive control, control/regulation systems, etc., can solve problems such as control quality deterioration and system instability, and achieve the effect of improving accuracy and ideal suppression effect.
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[0056] The Smith estimation compensation method based on the sixth-order B-spline wavelet neural network, its steps are as follows:
[0057] (1) Let the actual controlled object be:
[0058]
[0059] Where x represents the system state quantity, u represents the input quantity,
[0060] (2) Discretize formula (1) to get:
[0061]
[0062] where T n is the sampling time, T n+1 -T n is the sampling interval of the system state quantity x, n=0, 1, 2, 3...,
[0063] (3) Determine the value of u according to the actual situation, and determine a constant value Δx according to the model accuracy requirements,
[0064] (4) When x increases by Δx, that is, x(T n+1 )-x(T n )=Δx, record ΔT n=T n+1 -T n value,
[0065] (5) ΔT recorded by n value, calculate y n =Δx / ΔT n , get the learning sample y n , record the total number of learning samples,
[0066] (6) Arrange the obtained learning samples into a vector Y:
[0067]
[0068] (7) Sixth-order B-spline wavelet ...
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