A Kernel-Based Identification Approach to LPV Feedforward: With Application to Motion Systems

被引：3

作者：

van Haren, M. ^{[1
]}

Blanken, L. ^{[1
,2
]}

Oomen, T. ^{[1
,3
]}

机构：

[1] Eindhoven Univ Technol, Control Syst Technol Sect, Eindhoven, Netherlands

[2] Sioux Technol, Eindhoven, Netherlands

[3] Delft Univ Technol, Delft Ctr Syst & Control, Delft, Netherlands

来源：

IFAC PAPERSONLINE | 2023年 / 56卷 / 02期

关键词：

Mechatronics; Motion control systems; Linear parameter-varying systems; Bayesian methods; data-driven control; DESIGN;

D O I：

10.1016/j.ifacol.2023.10.662

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The increasing demands for motion control result in a situation where Linear Parameter-Varying (LPV) dynamics have to be taken into account. Inverse- model feedforward control for LPV motion systems is challenging, since the inverse of an LPV system is often dynamically dependent on the scheduling sequence. The aim of this paper is to develop an identification approach that directly identifies dynamically scheduled feedforward controllers for LPV motion systems from data. In this paper, the feedforward controller is parameterized in basis functions, similar to, e.g., mass-acceleration feedforward, and is identified by a kernel-based approach such that the parameter dependency for LPV motion systems is addressed. The resulting feedforward includes dynamic dependence and is learned accurately. The developed framework is validated on an example.

引用

页码：6063 / 6068

页数：6

共 25 条

[1] Linear, parameter-varying control and its application to a turbofan engine [J].