Fractional order system identification method based on Legendre wavelet multi-resolution analysis
A wavelet multi-resolution, fractional-order system technology, applied in the field of modeling and identification, can solve problems such as inability to accurately estimate system parameters, difficult engineering applications, and complex identification processes, and achieve reduced matrix dimensions, small calculations, and improved The effect of recognition speed
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Embodiment 1
[0044] The fractional order system can be described as
[0045]
[0046] Where β 2 =2.2, β 1 =1.2, a 2 = 1, a 1 = 2, a 0 =3, the system input f(t) is a sinusoidal signal.
[0047] Step 1: Select Legendre wavelet order on the interval [0,1]
[0048] 1.1 The definition of Legendre wavelet on the interval [0,1] is:
[0049]
[0050] Where k is any positive integer, m is the order of Legendre polynomial, m=0,1,...,M-1, n=1, 2,3,...,2 k -1 , t is the normalized time, Is the orthogonal coefficient, the expansion coefficient a=2 -k , Translation coefficient
[0051] 1.2 Choose Legendre wavelet order as 2, and initial scale space as 2 9 .
[0052] Step 2: Use the block impulse function integral matrix to derive the operation matrix of Legendre wavelet integral
[0053] Block impulse function integral operation matrix
[0054] (I α B N )(t)≈F α B N (t) (9)
[0055] Where B N (t)=[φ 1 (t),φ 2 (t),φ 3 (t),…φ N (t)] is the block pulse basis vector, F α It is the integral operation matrix of the blo...
Embodiment 2
[0117] Consider the following fractional order system
[0118]
[0119] Where β 2 =2.2, β 1 = 1.3, a 2 = 1.5, a 1 =1.4, a 0 = 1, the system input f(t) is a step signal,
[0120] Using the same method as Example 1, the difference is that the range of fractional differential order and the step length are β 2 =(1.5:0.1:2.5), β 1 =(0:0.1:1.5), add white Gaussian noise with a signal-to-noise ratio of 20dB, 30dB, and 40dB to the output signal. The number of decomposition layers and performance indicators of different signal-to-noise ratios such as image 3 Shown. From image 3 It can be seen that with the continuous increase of the number of decomposition layers, the IAE index is continuously decreasing, indicating that the multi-resolution analysis method has a good effect on noise suppression.
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