The present work aims to introduce a nonlinear control scheme that combines intelligent
feedback linearization (FBL) and a model predictive control (MPC) for a pressurized water …

This paper presents the design of a neural network based feedback linearization (NNFBL)
controller for a two degree-offreedom (DOF), quarter-car, servo-hydraulic vehicle …

This paper proposes a nonlinear control approach using dynamic neural network-based
input–output feedback linearization to resolve the inherent conflicting performance criteria …

The combination of model predictive control based on linear models (MPC) with feedback
linearization (FL) has attracted interest for a number of years, giving rise to MPC+ FL control …

The core factors governing the performance of active vehicle suspension systems (AVSS)
are the inherent trade-offs involving suspension travel, ride comfort, road holding and power …

The study proposes a novel feedback linearization and almost disturbance decoupling
control of nonlinear multiple-input-multiple-output (MIMO) systems. The goal of cancer …

This paper presents a novel adaptive predictive proportional–integral–derivative (PID)
control using fuzzy wavelet neural networks (FWNN) for a kind of highly nonlinear discrete …

Dynamic neural networks (DNNs) have important properties that make them convenient to
be used together with nonlinear control approaches based on state space models and …

This study proposes an active nonlinear control strategy for effective vibration mitigation in
nonlinear dynamical systems characterized by uncertainty. The proposed scheme relies on …

An online learning neural network (NN) based adaptive scheme has been proposed for
tracking the power level of higher order point kinetic pressurized water reactor (PWR) with …