scholarly journals Model-Following Control for Nonlinear Plants with Time Delay Using RBF Neural Networks

2007 ◽  
Vol 38 (4) ◽  
pp. 49-53
Author(s):  
Yoichi ISHIKAWA ◽  
Yoshihisa ISHIDA
Keyword(s):  
Neural Networks ◽  
Time Delay ◽  
Rbf Neural Networks ◽  
Model Following Control ◽  
Model Following ◽  
Nonlinear Plants

scholarly journals Design of the State Predictive Model Following Control System with Time-Delay

2009 ◽  
Vol 19 (2) ◽  
pp. 247-254 ◽  
Author(s):  
Dazhong Wang ◽  
Shujing Wu ◽  
Shigenori Okubo
Keyword(s):  
Control System ◽  
Time Delay ◽  
Predictive Model ◽  
The State ◽  
Delay Systems ◽  
Control Synthesis ◽  
Time Delay Systems ◽  
Model Following Control ◽  
Model Following ◽  
System With Time Delay

Design of the State Predictive Model Following Control System with Time-DelayTime-delay systems exist in many engineering fields such as transportation systems, communication systems, process engineering and, more recently, networked control systems. It usually results in unsatisfactory performance and is frequently a source of instability, so the control of time-delay systems is practically important. In this paper, a design of the state predictive model following control system (PMFCS) with time-delay is discussed. The bounded property of the internal states for the control is given, and the utility of this control design is guaranteed. Finally, examples are given to illustrate the effectiveness of the proposed method, and state predictive control techniques are applied to congestion control synthesis problems for a TCP/AQM network.

Adaptive RBF neural-networks control for a class of time-delay nonlinear systems

2008 ◽  
Vol 71 (16-18) ◽  
pp. 3617-3624 ◽  
Author(s):  
Qing Zhu ◽  
Shumin Fei ◽  
Tianping Zhang ◽  
Tao Li
Keyword(s):  
Neural Networks ◽  
Time Delay ◽  
Nonlinear Systems ◽  
Rbf Neural Networks

scholarly journals Adaptive Neural Control for a Class of Outputs Time-Delay Nonlinear Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Ruliang Wang ◽  
Jie Li
Keyword(s):  
Neural Networks ◽  
Time Delay ◽  
Nonlinear Systems ◽  
Neural Control ◽  
Closed Loop ◽  
Continuous Functions ◽  
Rbf Neural Networks ◽  
Adaptive Neural Control ◽  
Control Scheme ◽  
Simulation Results

This paper considers an adaptive neural control for a class of outputs time-delay nonlinear systems with perturbed or no. Based on RBF neural networks, the radius basis function (RBF) neural networks is employed to estimate the unknown continuous functions. The proposed control guarantees that all closed-loop signals remain bounded. The simulation results demonstrate the effectiveness of the proposed control scheme.

scholarly journals Time-Delay LPV System Control and Its Application in Chatter Suppression of the Milling Process

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Dazhong Wang ◽  
Shujing Wu ◽  
Lei Wan
Keyword(s):  
Time Delay ◽  
Milling Process ◽  
System Control ◽  
State Control ◽  
Chatter Suppression ◽  
Model Following Control ◽  
Model Following ◽  
Internal States ◽  
Lpv System ◽  
Control Methodology

This paper proposed a methodology for the control of model following control system (MFCS) approach to time-delay linear parameter-varying (LPV) system. The method incorporates a state control law which makes the output error zero, the bounded property of the internal states for the control is given, and the utility of this control design is guaranteed. Numerical example is given to demonstrate the effectiveness and less conservativeness of the proposed methods. The proposed control methodology is demonstrated on chatter suppression in the milling process.

Hyperstable adaptive model following control of nonlinear plants

1982 ◽  
Vol 1 (4) ◽  
pp. 232-236 ◽  
Author(s):  
A. Balestrino ◽  
G. De Maria ◽  
L. Sciavicco
Keyword(s):  
Adaptive Model ◽  
Model Following Control ◽  
Model Following ◽  
Nonlinear Plants
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