title: Learning feedforward control using a dilated B-spline network: frequency domain analysis and design.
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.
authors.affiliation: 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
authors.forename: YangQuan
authors.initials: Y
authors.lastname: Chen
authors.forename: Kevin L
authors.initials: KL
authors.lastname: Moore
authors.forename: Vikas
authors.initials: V
authors.lastname: Bahl
mesh_terms: D001185:Artificial Intelligence; D016571:Neural Networks, Computer