Optimal approximation of linear systems using a Teaching-Learning-Based Optimization algorithm

Abstract

In simulation of complex dynamic system or controller design, approximation of linear system models is one important task. In this paper, an optimization algorithm named Teaching-Learning-Based Optimization (TLBO) is presented for optimal approximating linear systems. The novel algorithm performance was tested on two linear systems, a stable linear system and an unstable one. Experimental results show that the proposed TLBO can effectively approximate stable and unstable linear systems.