改进了非线性PMDC电机死区和摩擦模型的噪声降低,使用了扩展卡尔曼波器的变种,并进行了实际验证
Shafiq Haider1, Sadaqat Ali1, Muhammad Saqlain1
1Department of Electronics Engineering, University of Engineering and Technology, Taxila, Pakistan.
本研究引入了一种适应式扩展卡尔曼波器 (AEKF),用于减少非线性恒磁直流电机 (PMDC) 的测量噪声. 与传统的EKF相比,AEKF显著提高了状态估计的准确性和稳定性.
科学领域:
- 控制系统工程 控制系统工程
- 机器人和自动化机器人与自动化
- 电气工程 电气工程
背景情况:
- 常磁直流 (PMDC) 电机中的非线性,如硬死区和摩擦,使准确的状态估计变得复杂.
- 传统的扩展卡尔曼波器 (EKF) 方法可能会产生不准确的估计,因为它们处理系统和测量噪声.
研究的目的:
- 开发和验证一个改进的框架来测量非线性PMDC电机的降噪.
- 为了提高PMDC电机应用的状态估计的准确性和可靠性.
主要方法:
- 将非线性 (硬死区,摩擦) 纳入PMDC电机模型.
- 标准扩展卡尔曼波器 (EKF) 的应用,用于降低噪音.
- 引入并使用EKF (AEKF) 的适应变体,其中包含加权系数和忘记因子,用于准确设置共变量参数.
主要成果:
- 适应式AEKF表现出与传统EKF相比显著的定量改进.
- AEKF可自适应地调整噪声协变矩阵,从而更准确地测量降噪和状态估计.
- AEKF实现了较小的根平均平方误差,增强的收速度,以及更大的对干扰的耐受性.
结论:
- 与标准EKF相比,自适应式AEKF在非线性PMDC电机中的状态估计提供了卓越的性能.
- 由于AEKF的适应能力,它对PMDC机器,导航系统,机器人和传感器融合等关键应用非常有价值.
- 精确可靠的状态估计对于成功实施这些先进技术至关重要.
更多相关视频
11:44Real-Time DC-dynamic Biasing Method for Switching Time Improvement in Severely Underdamped Fringing-field Electrostatic MEMS Actuators
Published on: August 15, 2014
09:01Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
Published on: April 4, 2017
相关概念视频
Time-Domain Interpretation of PD Control
Consider the example of control of motor torque. Initially, a positive...
Frequency-Domain Interpretation of PD Control
The proportional control gain, combined with the...
PD Controller: Design
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
Time and frequency -Domain Interpretation of PI Control
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
PI Controller: Design
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
