Teaching Learning Based Optimization for Designing Control Strategies in Complex Systems

In this study, teaching learning-based optimization algorithm (TLBO) has been explored in order abatement (OA) and controller design of the linear time-invariant (LTI) systems. Motivated by various optimization approaches available in the literature, with TLBO’s unique computational abilities like fast convergence, simple mathematical steps and gradient free approach, the study aims to determine the unknown coefficients of the abated system (AS) by minimizing the integral square error (ISE) between the higher order system (HOS) and the AS. The efficacy and supremacy of the suggested approach has been demonstrated using six distinct control systems of high order. In order to assess the performance of the proposed method, the obtained results are compared with HOS and lower order system already available in the literature. It reveals that the proposed AS maintains stability and the steady state conditions of the HOS. To further illustrate the practical application of TLBO, a 4th order system has been considered and a proportional-integral (PI) controller is designed using the proposed 2nd order AS.