This survey paper explores advanced nonlinear control strategies for Unmanned Aerial
Vehicles (UAVs), including systems such as the Twin Rotor MIMO system (TRMS) and …

To maintain the vibrations of the gyroscope proof mass, a trajectory tracking control system
using a neural network estimator is proposed. The proposed control system incorporates a …

A novel higher-order context-layered recurrent pi-sigma neural network (CLRPSNN) is
presented for the identification of nonlinear dynamical systems. The proposed model is the …

This article summarizes the authors' experiences in the development and application of the
General Dynamical Model Approach related to adaptive linearizing control of …

Establishing the balance between slurry supporting pressure and expected water-earth
pressure is an important criterion to ensure excavating face stability in shield tunneling. To …

In this paper, event-triggered reinforcement learning-based adaptive tracking control is
developed for the continuous-time nonlinear system with unknown dynamics and external …

In this paper, a comparative study is performed to test the approximation ability of different
neural network structures. It involves three neural networks multilayer feedforward neural …

Tasmanian devil optimization (TDO) algorithm represents one of the most recent
optimization algorithms that were introduced based on the nature behavior of Tasmanian …

This paper presents an identification model based on quantum neural network for
engineering systems. Quantum neural network (QNN) is a superior strategy to improve the …

For the purpose of identifying nonlinear dynamic systems, a compound recurrent feed-
forward neural network based on the combination of feed-forward neural network (FFNN) …