This paper proposes an adaptive controller for chaos synchronization using quantum neural
networks (QNN). The main purpose is to design a communication system for transmission of …

This paper proposes an adaptive fuzzy-neural inference system (ANFIS)-based control
approach for a six degrees of freedom (6-DoF) robotic manipulator. Its main objective is to …

This paper presents a model-free controller for robot manipulators driven by permanent
magnet synchronous motors (PMSM). The contribution of this paper is merging the electrical …

采用普通PID 控制的复杂电液伺服控制系统(液压驱动的控制系统) 存在控制柔顺性不佳的问题,
达不到理想的控制效果, 为了提高电液伺服系统的控制特性, 提出了一种基于径向基神经网络 …

In this paper, a new method for secure communication based on chaos synchronization is
proposed. It is consisted of a state feedback controller and a robust control term using the …

Purpose This paper aims to present an adaptive robust sliding mode tracking controller for a
6 degree-of-freedom industrial assembly robot with parametric uncertainties and external …

An uncertainty estimation and compensation can improve the performance of control
systems due to structured and unstructured uncertainty. This paper presents a robust task …

In this paper, a novel optimal adaptive radial basis function neural network (RBFNN) control
has been investigated for a class of multiple-input-multiple-output (MIMO) nonlinear robot …

In this study, a new controller for chaos synchronization is proposed. It consists of a state
feedback controller and a robust control term using Legendre polynomials to compensate for …

This paper presents an intelligent controller for voltage tracking control of DC-DC boost
converters. The control law is a brain emotional learning based intelligent controller …