Comparative Analysis of Evolutionary Computation Based Gain Scheduling Control for Ball and Plate Stabilization System

Year 2019, Volume: 7 Issue: 1, 44 - 55, 31.01.2019

Haluk Gözde

https://doi.org/10.17694/bajece.466306

Cited By: 1

Abstract

The platform
stabilization systems used in marine, airborne or land vehicle applications are
controlled with very different control methods basically including linear,
nonlinear and artificial intelligence-based design techniques. Nowadays,
evolutionary computation based optimization algorithms also provide new
opportunities to engineers in order to design a gain scheduling controller. In
this study, an evolutionary computation based gain scheduling controller is
proposed for a ball and plate system so as to examine its control performances
on a stabilization system. For this purpose, the swarm intelligence based Particle
Swarm Optimization (PSO) and evolutionary algorithm based Differential
Evolution (DE) algorithms are chosen due to their better performance than the
other evolutionary computation algorithms. The results are comparatively
investigated by using time domain and frequency domain analysis methods.
Additionally, the robustness analysis is also applied to examine the tuning
performances of these controllers in case of changing system parameters in the
range of ±50%.

Keywords

Platform stabilization, Ball and plate system, Gain scheduling control, Evolutionary computation, Particle swarm optimization algorithm, Differential evolution algorithm

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