DocumentCode :
960727
Title :
Learning feedforward control using a Dilated B-spline network: frequency Domain Analysis and design
Author :
Chen, YangQuan ; Moore, Kevin L. ; Bahl, Vikas
Author_Institution :
Dept. of Electr. & Comput. Eng., Utah State Univ., Logan, UT, USA
Volume :
15
Issue :
2
fYear :
2004
fDate :
3/1/2004 12:00:00 AM
Firstpage :
355
Lastpage :
366
Abstract :
This paper presents a frequency-domain analysis and design approach for a learning feedforward controller (LFFC) using a dilated B-spline network. The LFFC acts as an add-on element to the existing feedback controller (FBC). The LFFC signal is updated iteratively based on the FBC signal of the previous iteration as the task repeats. Similar to proportional-integral-derivative controller tuning, there are only two parameters to adjust: The B-spline support width and the learning gain. The effect of dilation in the B-spline network is discussed. Detailed design formulae are given based on a stability analysis. As an illustration, simulation results on the path tracking control of a wheeled mobile robot are presented.
Keywords :
control system synthesis; feedback; feedforward; frequency-domain analysis; learning (artificial intelligence); mobile robots; neurocontrollers; path planning; position control; splines (mathematics); stability; three-term control; dilated B-spline network; feedback controller; frequency domain analysis; frequency domain design; learning feedforward control; path tracking control; proportional-integral-derivative controller tuning; stability analysis; wheeled mobile robot; Adaptive control; Feedback control; Filters; Frequency domain analysis; Industrial control; Mobile robots; PD control; Proportional control; Spline; Stability analysis; Artificial Intelligence; Neural Networks (Computer);
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/TNN.2004.824268
Filename :
1288240
Link To Document :
بازگشت