Learning feedforward control using a dilated B-spline network: frequency domain analysis and design.
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.
Chen
YangQuan
Y
Center for Self-Organizing and Intelligent Systems , Department of Electrical and Computer Engineering, Utah State University, Logan, UT 84322-4160, USA. yqchen@ece.usu.edu
Moore
Kevin L
KL
Bahl
Vikas
V
D001185:Artificial Intelligence; D016571:Neural Networks, Computer