Title :
Kernel least mean square algorithm in control of nonlinear systems
Author :
Mazloomi, Zinat ; Shandiz, Heydar Tusian ; Faramarzpour, Hossein
Author_Institution :
Fac. of Electerical & Robotic Eng., Shahrood Univ. of Technol., Shahrood, Iran
Abstract :
Although some research has been presented about the application of Kernel Least Mean Square (KLMS) algorithm in the estimation and approximation of functions, this algorithm wasn´t applied to the control of nonlinear systems. In this paper, an efficient and novel adaptive Control strategy based on Kernel Least Mean Square is introduced to realize the control of a nonlinear aircraft system. Actually the KLMS algorithm is a growing radial basis function (GRBF) network, when Kernel function is a Gaussian function. In this research, based on Lyapunov theory, KLMS is used as an online method for tuning the kernel size to control nonlinear systems. This technique certifies the stability and provides an acceptable accuracy. Finally, we utilize this algorithm to control a nonlinear fighter aircraft by using a dynamic model of the F-18 aircraft.
Keywords :
Gaussian processes; Lyapunov methods; adaptive control; aircraft control; control system synthesis; function approximation; least mean squares methods; nonlinear control systems; radial basis function networks; stability; F-18 aircraft dynamic model; GRBF network; Gaussian function; KLMS algorithm; Lyapunov theory; adaptive control strategy; function approximation; function estimation; growing radial basis function network; kernel function; kernel least mean square algorithm; nonlinear aircraft system; nonlinear control systems; nonlinear fighter aircraft control; Aerospace control; Aircraft; Atmospheric modeling; Equations; Kernel; Mathematical model; Stability analysis; Kernel Least Mean Square; Lyapunov theory; Online learning; Tracking a maneuver;
Conference_Titel :
Electrical Engineering (ICEE), 2013 21st Iranian Conference on
Conference_Location :
Mashhad
DOI :
10.1109/IranianCEE.2013.6599541
