Variable Fractional Order (VFO) PID Control for Precision Positioning

Variable Fractional Order (VFO) PID Control for Precision Positioning: A Frequency Domain Approach

Nagda, Neel (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Delft Center for Systems and Control; TU Delft Precision and Microsystems Engineering)

van Wingerden, Jan-Willem (graduation committee)
Giordano, Giulia (mentor)
Hossein Nia Kani, Hassan (mentor)
Saikumar, Niranjan (mentor)

Delft University of Technology

Mechanical Engineering | Systems and Control

2019-08-26

Stringent control demands from the high-tech mechatronics industry have warranted the need to explore potentially advantageous non-linear controllers. Variable Fractional Order (VFO) calculus provides one such avenue to build non-linear PID-like controllers. VFO calculus is the generalization of integer order differentiation and integration, where, in addition to the possibility of orders being real or even complex, the orders can vary as a function of a variable like time, temperature, etc. However, in this nascent field of VFO control, the focus has mainly been on controller tuning by time domain optimization of the performance for certain specific trajectories or cost functions. On the other hand, Frequency domain tools allow for analysis and tuning of controllers for performance over a wide range of exogenous inputs. For smooth adoption into industry, it is important to develop a frequency domain framework for working with VFO control. Describing function (DF) analysis is a method to obtain an approximate Frequency Response Function (FRF)-like function for non-linear systems. In this thesis, DF analysis is used for developing VFO PID controllers in the frequency domain from an industry compatibility point of view and the closed loop performance of these controllers in controlling a precision positioning stage is examined.

PID
Variable Fractional Order calculus
Describing Function analysis
SIDF
HOSIDFs
Precision positioning

http://resolver.tudelft.nl/uuid:99998698-7287-47e9-acd0-9d7cc1d78670

Student theses

master thesis

© 2019 Neel Nagda