... disturbances. Design/methodology/approach First, the tan-type barrier Lyapunov function (BLF) and neural network (NN) are constructed to deal with the full-state constraints and system uncertainties, respectively. Subsequently, the compound disturbances are estimated by FTDOs. Simultaneously, the FTDOs...

...Min Wan; Mou Chen; Mihai Lungu Purpose This paper aims to study a neural network-based fault-tolerant controller to improve the tracking control performance of an unmanned autonomous helicopter with system uncertainty, external disturbances and sensor faults, using the prescribed performance...

... on the engine measurable parameters. Design/methodology/approach The method is based on the implementation of an artificial neural network (ANN) trained with well-known cases referred to real conditions, able to recognize degradation because of two main gas turbine engine deterioration effects: erosion...

...Franciszek Dul Purpose The purpose of the paper is to analyze the active suppression of the aeroelastic vibrations of ailerons with strongly nonlinear characteristics by neural network/reinforcement learning (NN/RL) control method and comparing it with the classic robust methods of suppression...

...Hamid Asgari; Mohsen Fathi Jegarkandi; XiaoQi Chen; Raazesh Sainudiin Purpose The purpose of this paper is to develop and compare conventional and neural network-based controllers for gas turbines. Design/methodology/approach Design of two different controllers is considered. These controllers...

...Davood Afshari; M. Sedighi; M.R. Karimi; Z. Barsoum Purpose The purpose of this paper is to predict residual stresses in resistance spot weld of 2 mm thick aluminum 6061-T6 sheets. The joint use of finite element analysis and artificial neural networks can eliminate the high costs of residual...

...Shinan Chang; Mengyao Leng; Hongwei Wu; James Thompson Purpose – The purpose of this paper is to present a new technique based on the combination of wavelet packet transform (WPT) and artificial neural networks (ANNs) for predicting the ice accretion on the surface of an airfoil. Design...

... building block of the neuro‐controller is a nonlinear auto regressive exogenous (NARX) input neural network. For each neural controller, the parameter update rule is derived using Lyapunov‐like synthesis. An offline finite time training is used to provide asymptotic stability and on‐line learning strategy...

...Yihua Cao; Kungang Yuan; Guozhi Li Purpose The purpose of this paper is to describe a methodology for predicting the effects of glaze ice geometry on airfoil aerodynamic coefficients by using neural network (NN) prediction. Effects of icing on angle of attack stall are also discussed. Design...