Add to ORKGThis article proposes an RBFNN (Radial Basis Function Neural Network) and sliding mode based controller to manipulate the robot manipulator. The technique used has been based on a sliding mode control approach that can drive the system towards a sliding surface by Gaussian radial basis function neural network based tuned-controller
[[abstract]]A sliding mode controller (SMC) design method based on radial basis function network (RB...
To achieve robust finite-time trajectory tracking control, this paper proposes a novel neural-networ...
The use of Neural Networks in solving nonlinear control problem is studied. A comparative study of v...
A fuzzy sliding mode controller based on radial basis function neural network (RBFNN) is proposed in...
This paper proposes a fuzzy sliding mode controller with radial basis function neural network (RBFNN...
This paper presents a radial basis function (RBF) neural network control scheme for manipulators wit...
This paper briefly discusses about the Robust Controller based on Adaptive Sliding Mode Technique wi...
Abstract: In this paper a New RBF Neural Network based Sliding Mode Adaptive Controller (NNNSMAC) fo...
One of the main problems associated with Sliding Mode Control (SMC) is that a whole knowledge of the...
Abstract — In this paper, an Evolutionary Optimized Neural Network (EONN) based control scheme is pr...
This paper presents an approach of cooperative control that is based on the concept of combining neu...
Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need f...
Radial Basis Function-Neural Networks are well-established function approximators. This paper presen...
This article presents the design of super twisting sliding mode control (STSMC) based on radial basi...
Abstract: This paper describes experimental results applying artificial neural net-works to perform ...
[[abstract]]A sliding mode controller (SMC) design method based on radial basis function network (RB...
To achieve robust finite-time trajectory tracking control, this paper proposes a novel neural-networ...
The use of Neural Networks in solving nonlinear control problem is studied. A comparative study of v...
A fuzzy sliding mode controller based on radial basis function neural network (RBFNN) is proposed in...
This paper proposes a fuzzy sliding mode controller with radial basis function neural network (RBFNN...
This paper presents a radial basis function (RBF) neural network control scheme for manipulators wit...
This paper briefly discusses about the Robust Controller based on Adaptive Sliding Mode Technique wi...
Abstract: In this paper a New RBF Neural Network based Sliding Mode Adaptive Controller (NNNSMAC) fo...
One of the main problems associated with Sliding Mode Control (SMC) is that a whole knowledge of the...
Abstract — In this paper, an Evolutionary Optimized Neural Network (EONN) based control scheme is pr...
This paper presents an approach of cooperative control that is based on the concept of combining neu...
Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need f...
Radial Basis Function-Neural Networks are well-established function approximators. This paper presen...
This article presents the design of super twisting sliding mode control (STSMC) based on radial basi...
Abstract: This paper describes experimental results applying artificial neural net-works to perform ...
[[abstract]]A sliding mode controller (SMC) design method based on radial basis function network (RB...
To achieve robust finite-time trajectory tracking control, this paper proposes a novel neural-networ...
The use of Neural Networks in solving nonlinear control problem is studied. A comparative study of v...