James Duncan McPherson

Topic

Model Parameter Identification for Feed Drive Dynamics using Kernel-Based Methods

Department of Mechanical Engineering

Date & location

• Wednesday, May 15, 2024

• 1:30 P.M.

• Engineering Office Wing

• Room 502

Reviewers

Supervisory Committee

• Dr. Keivan Ahmadi, Department of Mechanical Engineering, University of Victoria (Supervisor)

• Dr. Daniela Constantinescu, Department of Mechanical Engineering, UVic (Member) 

External Examiner

• Dr. Lin Cai, Department of Electrical and Computer Engineering, University of Victoria

Chair of Oral Examination

• Dr. Dante Canil, School of Earth and Ocean Sciences, UVic

   

Abstract

This thesis presents an application of kernel-based methods for identification of the feed drive’s dynamics model parameters and prediction of the disturbances affecting feed drives during operation from the cutting forces. To this purpose, the Partially Linear- Least Squares Support Vector Machine (PL-LSSVM) and Kernel Recursive Least Squares- Tracker (KRLS-T) algorithms were utilized for batch identification and online prediction of disturbances. Two experimental case studies were performed with two ball screw feed drives under simulated and real cutting forces to verify the identification and in-operation prediction of cutting forces.