EOTs Based Fixed Order Controller Design and Performance Analysis

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.

A Novel HSPICS for Industrial Robotic Controller Based on FPGA_SoC: Modelling and Fabrication

“…To engage the maximum performance for designing robotic controller, several criteria should be accurately evaluated in simulation parts such as the accuracy of TF form, besides studying a new modification to improve GA performance in case of the basic operating mode in classical GA is not always well suited to any constraint treatment [55] . The aim is to design high speed controller for a robotic applications to accomplish highest reduction response time to be measured experimentally in microsecond unit, where the most significant related works were obtained the results in millisecond unit [56][57][58][59][60][61][62][63][64][65][66][67][68], further decreasing the deviation of between experiment and simulation, and reducing the average error step response (AESR) bellow 10%. The contribution of this work could be concluded in four points:…”