Improving the performance indices of a dynamic system using adaptive learning controllers

Abstract

In this paper, the angle of attack of an aircraft is controlled by using soft computing techniques like Genetic Algorithm (GA), Fuzzy Model Reference Learning Controller (FMRLC) and Radial Basis Function Neural Controller (RBFNC) and the performance indices like Mean Square Error (MSE), Integral Square Error (ISE), and Integral Absolute Time Error (IATE) etc. of the dynamic system is improved. The result is compared with the conventional techniques like Tyreus-Luyben (TL), Ziegler-Nichols (ZN) and Interpolation Rule (IR) for tuning the PID controller. It was established that the errors by using soft computing techniques are very less as compared to the conventional techniques thereby improving the performance indices of the dynamic system.