Abstract—Evolutionary optimizations techniques (EOTs) are stochastic search techniques that direct a population of solutions towards best possible results by using the natural principles. In recent years, these algorithms have grown to be an accepted optimization tool for many areas of scientific and engineering research, together with control system engineering design. Significant research exists concerning evolutionary algorithms to control system design and robustness performance analysis of controller. But, little work has been done with evolutionary optimization algorithms because of the problems related with robustness performance in early period of the evolution of controllers. Moreover, until recently the robustness performance of controllers based on evolutionary algorithms has not been researched in stipulate. The scope of this research covers generalized robustness performance condition and detailed analysis of the resultant control system.
Index Terms—Evolutionary algorithm, optimization, robustness, performance and controller.
F. Mahar, A. Hussain and Z. Bhutto are with the Balochistan University of Engineering and Technology, Khuzdar, Pakistan (e-mail:ch_it2001@yahoo.cm; engr_ayaz@yahoo.com;zuhaib_bhutto@hotmail.com).
S. A. Ali is with the Electronic Engineering Department, Iqra University (email: saadazhar@gmail.com)
Cite: Faizullah Mahar, Saad Azhar Ali, Ayaz Hussain, and Zohaibdin Bhutto, "EOTs Based Fixed Order Controller Design and Performance Analysis," International Journal of Machine Learning and Computing vol. 2, no. 3, pp. 345-350, 2012.