Title :
A method of speed observation based on least-squares linear-fitting with weight factor
Author :
Qiu Wenbin ; Chai Jianyun ; Sun Xudong ; You Rui
Author_Institution :
State Key Lab. of Control & Simulation of Power Syst. & Generation Equipments, Tsinghua Univ., Beijing, China
Abstract :
In industry application, the speed usually has to be observed with the position signal. But the position signal noises have been analyzed and modeled rarely. In this paper, by analyzing the characteristics of the position noises, white noise of uniform distribution model and the triangle wave noise model are proposed. The two models can be used to evaluate the influence of position measurement noises on the observed speed. Among the speed observation methods, the methods based on model predicted error can be used to observe the speed faster, due to the use of some priori knowledge. But these methods cannot be suitable for the case when the accurate model parameters cannot be obtained. Though the IIR filter has better low-pass filtering characteristic, it does not have linear phase and the stability is also a potential problem. There are not such drawbacks mentioned above for the FIR filter. The least-squares linear-fitting with weight factor speed observer based on position signal, which is a FIR filter essentially, is proposed in this paper. Compared with the direct differentiator, the wider bandwidth and smaller the maximum amplitude of speed fluctuation are validated by simulation results and experimental results.
Keywords :
FIR filters; IIR filters; error analysis; least squares approximations; low-pass filters; position measurement; velocity control; white noise; FIR filter; IIR filter; accurate model parameters; industry application; least-squares linear-fitting; linear phase; low-pass filtering characteristic; model predicted error; position signal noise measurement; speed fluctuation; speed observation method; triangle wave noise model; uniform distribution model; weight factor; white noise; Finite impulse response filters; Fluctuations; IIR filters; Observers; Transfer functions; White noise;
Conference_Titel :
Electrical Machines and Systems (ICEMS), 2014 17th International Conference on
Conference_Location :
Hangzhou
DOI :
10.1109/ICEMS.2014.7013855