Abstract:
This paper demonstrates the potency of evolution based optimization techniques in the
sense of enhancing the system’s performance. Teaching Learning Based Optimization (TLBO) is a
well-known evolutionary algorithm used to optimize the parameters of the PID controller so as to
improve the performance of the magnetic levitation system. The TLBO search algorithm is split into
two phases, the teacher phase and the learner phase. The teacher phase is comprised of having minimum performance index as compared to learner phase. The learners improve their knowledge on
the basis of teacher’s performance. The parameters are tuned while minimizing the performance
index of the system. The performance index incorporated in this paper is the integral time weighted
square error (ITSE). The corroboration of the above technique is ended by comparing it with the
conventional control techniques.
2017 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an
open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
