Acceleration estimation method and system based on high-order sliding mode tracking differentiator, equipment and medium
A tracking differentiator, velocity estimation technology, applied in the direction of measurement of acceleration, velocity/acceleration/shock measurement, general control system, etc., can solve the problem of accurate differentiation that does not provide finite time convergence, unable to obtain acceleration value, etc.
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0088] Arie Levant proposed a high-order sliding mode tracking differentiator that can achieve precise robustness of any order. The differentiator is based on the theoretical proof that a signal containing noise has n-order derivatives, and the Lipschitz constant of the n-order derivatives is given When limited by the constant L of , the best differential accuracy of the i (i<=n) order derivative is positively correlated with the magnitude of the maximum measurement noise. The differentiator based on this theory can approach the real value with any order and any precision when obtaining the maximum measurement noise amplitude, that is, the maximum value of the real acceleration. value is very difficult. Therefore, the present invention adopts a compromise method, adopts least square identification to obtain an approximate value of the maximum measurement noise amplitude, and then fine-tunes parameters to achieve high-precision estimation of the differentiator.
[0089] Such a...
Embodiment 2
[0147] Such as figure 2 As shown, this embodiment provides an acceleration estimation system based on a high-order synovial film tracking differentiator, which includes a first parameter identification module 201, a first estimation module 202, a second parameter identification module 203 and a second estimation module 204, of which:
[0148] The first parameter identification module 201 is used to identify the parameters of the speed by using the augmented least squares method to obtain the maximum measurement noise amplitude of the speed estimation;
[0149] The first estimation module 202 is configured to use a first-order sliding film tracking differentiator to accurately estimate the speed of the target according to the maximum measurement noise magnitude of the speed estimate, to obtain an estimated value of the target speed;
[0150] The second parameter identification module 203 is configured to perform parameter identification on the acceleration by using the augmen...
Embodiment 3
[0154] This embodiment provides a computer device, which can be a computer, such as image 3 As shown, it connects processor 302, memory, input system 303, display 304 and network interface 305 through system bus 301, the processor is used to provide calculation and control capabilities, the memory includes non-volatile storage medium 306 and internal memory 307, the non-volatile storage medium 306 stores an operating system, computer programs, and databases, the internal memory 307 provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium, and the processor 302 executes the During computer program, realize the acceleration estimation method of above-mentioned embodiment 1, as follows:
[0155] Using the augmented least squares method to identify the parameters of the speed, the maximum measurement noise amplitude of the speed estimation is obtained;
[0156] Using a first-order synovial film tracking differenti...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More 


