This thesis focuses on developing robust online training and pruning algorithms for a class of neural network tracking control systems. In particular, a complete convergence analysis is presented for all the algorithms with different learning schemes, respectively.DOCTOR OF PHILOSOPHY (EEE
Abstract—We are interested in training neurocontrollers for robustness on discrete-time models of ph...
The modern stage of development of science and technology is characterized by a rapid increase in th...
Abstract—In this paper, a stabilization method based on the input–output conicity criterion is prese...
67 p.Neural networks are widely used in industry fields, like robotic and process controllers. Exten...
Abstract. It is normally difficult to determine the optimal size of neural networks, particularly, i...
It is difficult to determine the number of nodes that should be used in a neural network. An adaptiv...
In this project, the robust adaptive controller has been surveyed to evaluate the guaranteed converg...
This thesis presents some new schemes controlling a class of nonlinear systems by using neural netwo...
University of Technology, Sydney. Faculty of Engineering.This thesis presents the research undertake...
The ever increasingly tight control performance requirement of modern mechanical systems often force...
In this paper, Neural networks (NNs) and adaptive robust control (ARC) design philosophy are integra...
This thesis focuses on the study of the neural network (NN) and its application to robot tracking co...
[[abstract]]This paper presents a stability method which is based on the stability condition of slid...
The control of nonlinear system is the hotspot in the control field. The paper proposes an algorithm...
Nowadays, in the field of information processing, neural networks (NNs) are very used, because they ...
Abstract—We are interested in training neurocontrollers for robustness on discrete-time models of ph...
The modern stage of development of science and technology is characterized by a rapid increase in th...
Abstract—In this paper, a stabilization method based on the input–output conicity criterion is prese...
67 p.Neural networks are widely used in industry fields, like robotic and process controllers. Exten...
Abstract. It is normally difficult to determine the optimal size of neural networks, particularly, i...
It is difficult to determine the number of nodes that should be used in a neural network. An adaptiv...
In this project, the robust adaptive controller has been surveyed to evaluate the guaranteed converg...
This thesis presents some new schemes controlling a class of nonlinear systems by using neural netwo...
University of Technology, Sydney. Faculty of Engineering.This thesis presents the research undertake...
The ever increasingly tight control performance requirement of modern mechanical systems often force...
In this paper, Neural networks (NNs) and adaptive robust control (ARC) design philosophy are integra...
This thesis focuses on the study of the neural network (NN) and its application to robot tracking co...
[[abstract]]This paper presents a stability method which is based on the stability condition of slid...
The control of nonlinear system is the hotspot in the control field. The paper proposes an algorithm...
Nowadays, in the field of information processing, neural networks (NNs) are very used, because they ...
Abstract—We are interested in training neurocontrollers for robustness on discrete-time models of ph...
The modern stage of development of science and technology is characterized by a rapid increase in th...
Abstract—In this paper, a stabilization method based on the input–output conicity criterion is prese...
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