In this paper, an adaptive proportional-integral-derivative (PID) controller based on a
quantum neural network (APIDC-QNN) is introduced. In the proposed neural network …

In this study, a control system was designed to control the robot's movement (The Mitsubishi
RM-501 robot manipulator) based on the quantum neural network (QNN). A proposed …

This paper introduces a novel structure of a polynomial weighted output recurrent neural
network (PWORNN) for designing an adaptive proportional—integral—derivative (PID) …

An adaptive controller of nonlinear PID-based analog neural networks is developed for the
velocity-and orientation-tracking control of a nonholonomic mobile robot. A superb mixture of …

An adaptive controller of nonlinear PID-based analog neural networks is developed for the
point to point and orientation-tracking control of a two link rigid robot manipulator. In each …

This article proposes a novel prescribed performance-based neural adaptive control
scheme for robot manipulators including motor dynamics under model uncertainties without …

Nonlinear, time-varying and uncertainty matter is an important issue in order to improve
conventional PID control technology due to the rapid development of control technologies …

In this work, an Adaptive Neural Networks PID controller structure, called Adaptive Fourier
Series Neural Networks PID controller (AFSNNPID), is developed. The main objective is to …

Robotic manipulators are nonlinear systems, multi-input multi-output, highly coupled and
complicated whose performance is negatively impacted by external disturbances and …

Motivated by the demand of intelligent control that applicable to real industrial systems, this
brief develops an innovative neuro controller for remotely operated robotic manipulators …