Dynamic Data Correction and System Control Performance Optimization for Non-Gaussian Systems
A technology of system dynamics and data correction, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problems of not being close enough to the real value, the control strategy optimization effect is not obvious, etc., and achieve the effect of high computing efficiency
Active Publication Date: 2021-07-27
TAIYUAN UNIV OF TECH
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Problems solved by technology
[0006] The technical problem solved by the present invention is: in the case of the wind power generation process being affected by non-Gaussian process noise (random wind speed) and non-Gaussian measurement noise, the data measurement correction is not close enough to the real value, and the control strategy optimization effect is not obvious. Provide a non-Gaussian system dynamic data correction and system control performance optimization method
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[0077] The method of the present invention is described below in conjunction with specific examples: for a typical wind energy conversion system, the equivalent load of the permanent magnet synchronous generator is determined by the constant inductance L s and variable resistor R s Composed in parallel. In this application example, the non-Gaussian system dynamic data correction and system control performance optimization method includes the following steps:
[0078] Step 1. The permanent magnet synchronous generator model can be described as:
[0079]
[0080] where R is the stator resistance, u d and u q are the voltages of the d component and q component of the stator respectively, L d and L q are the inductances of the d and q components of the stator, respectively, i d and i q are the currents of the d component and q component of the stator respectively, φ m is the magnetic flux (it is a constant), p is the number of pole pairs, Ω G is the rotational speed of...
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The invention relates to a system control performance optimization method, specifically a non-Gaussian system dynamic data correction and system control performance optimization method, which solves the problem that the data measurement and correction are not close enough when the wind power generation process is affected by non-Gaussian process noise and non-Gaussian measurement noise The real value, the problem that the optimization effect of the control strategy is not obvious, steps: 1. Describe the system model under non-Gaussian disturbance; 2. Use the EM algorithm to deduce the iterative formula in the problem description; 3. Use the iterative formula to solve the corrected output y r ; 4. Select the performance index based on statistical information to obtain the optimal control law. Advantages: 1. Consider the impact of non-Gaussian random noise on the system; 2. Consider the dynamic characteristics of the process, and better express the actual process; 3. Have high calculation efficiency and meet the requirements of the actual industrial process; 4. Adopt Entropy statistics fully describe the random characteristics of non-Gaussian random quantities, and establish tracking control indicators.
Description
technical field [0001] The invention relates to a system control performance optimization method, in particular to a non-Gaussian system dynamic data correction and system control performance optimization method. Background technique [0002] In practical systems, random disturbances exist widely, especially in industrial processes, such as random factors of wind speed changes in wind power systems, and random factors of measurement errors in sensor measurement data. [0003] At present, the correction of the measurement noise of the control system is based on the assumption that it is Gaussian, and is optimized by controlling the mean value and variance of the corrected data. However, the actual industrial process measurement error is often non-Gaussian. If the traditional method under the Gaussian assumption is used for correction, the effect of optimal control is not obvious. [0004] For a control strategy to achieve a good control effect, it is very important to obtain...
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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 任密蜂张雯陈荣辉张旭霞梁艳
Owner TAIYUAN UNIV OF TECH