Self-tuning algorithm for dsp-based motion control in cnc applications
Document Type
Thesis
Degree
Master of Science (MS)
Major/Program
Electrical Engineering
First Advisor's Name
Armando Barreto
First Advisor's Committee Title
Committee Chair
Second Advisor's Name
Mauricio Salinas
Third Advisor's Name
Kang Yen
Date of Defense
7-22-1997
Abstract
This thesis describes the development of an adaptive control algorithm for Computerized Numerical Control (CNC) machines implemented in a multi-axis motion control board based on the TMS320C31 DSP chip.
The adaptive process involves two stages: Plant Modeling and Inverse Control Application. The first stage builds a non-recursive model of the CNC system (plant) using the Least-Mean-Square (LMS) algorithm. The second stage consists of the definition of a recursive structure (the controller) that implements an inverse model of the plant by using the coefficients of the model in an algorithm called Forward-Time Calculation (FTC).
In this way, when the inverse controller is implemented in series with the plant, it will pre-compensate for the modification that the original plant introduces in the input signal. The performance of this solution was verified at three different levels: Software simulation, implementation in a set of isolated motor-encoder pairs and implementation in a real CNC machine. The use of the adaptive inverse controller effectively improved the step response of the system in all three levels. In the simulation, an ideal response was obtained. In the motor-encoder test, the rise time was reduced by as much as 80%, without overshoot, in some cases. Even with the larger mass of the actual CNC machine, decrease of the rise time and elimination of the overshoot were obtained in most cases. These results lead to the conclusion that the adaptive inverse controller is a viable approach to position control in CNC machinery.
Identifier
FI13101541
Recommended Citation
Aguilar, Cesar David, "Self-tuning algorithm for dsp-based motion control in cnc applications" (1997). FIU Electronic Theses and Dissertations. 1145.
https://digitalcommons.fiu.edu/etd/1145
Rights Statement
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).