Optimizing a One DOF Robot Without a Mathematical Model Using a Genetic Algorithm
Is this project an undergraduate, graduate, or faculty project?
Undergraduate
individual
Authors' Class Standing
Daniel Wilczak - Sophmore
Lead Presenter's Name
Daniel Wilczak
Faculty Mentor Name
Dr Matthew Verleger
Abstract
The purpose of the present study was to design a flight control system with no pre-determined mathematical model, but instead using a genetic algorithm to maintain the optimal altitude. The study is done through a quantitative empirical research method. Five phases of the genetic algorithm were used to test the one DOF device. An initial population of 10 chromosomes and 5 generations were used during the trial. The throttle value of the device had an associated gene value of 1 second. When the trial of five generations was completed, the total increase percentage was 171%. Preliminary results showed that optimizing a one DOF device, in real-time, is possible without using a pre-determined mathematical model.
Did this research project receive funding support from the Office of Undergraduate Research.
No
Optimizing a One DOF Robot Without a Mathematical Model Using a Genetic Algorithm
The purpose of the present study was to design a flight control system with no pre-determined mathematical model, but instead using a genetic algorithm to maintain the optimal altitude. The study is done through a quantitative empirical research method. Five phases of the genetic algorithm were used to test the one DOF device. An initial population of 10 chromosomes and 5 generations were used during the trial. The throttle value of the device had an associated gene value of 1 second. When the trial of five generations was completed, the total increase percentage was 171%. Preliminary results showed that optimizing a one DOF device, in real-time, is possible without using a pre-determined mathematical model.