Stable multi-model switching control of a class of nonlinear systems

2004 ◽  
Author(s):  
E. Franco ◽  
S. Sacone ◽  
T. Parisini
Keyword(s):  
Nonlinear Systems ◽  
Switching Control

Neural Network Direct Adaptive Control Strategy for a Class of Switched Nonlinear Systems

2016 ◽  
Vol 138 (8) ◽  
Author(s):  
Lei Yu ◽  
Xiefu Jiang ◽  
Shumin Fei ◽  
Jun Huang ◽  
Gang Yang ◽  
...  
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Control Method ◽  
Average Dwell Time ◽  
Switching Control ◽  
Network Control ◽  
Switched Nonlinear Systems ◽  
Output Tracking ◽  
Direct Adaptive Control ◽  
Adaptive Control Strategy

This paper deals with the adaptive neural network (NN) switching control problem for a class of switched nonlinear systems. Radial basis function (RBF) NNs are utilized to approximate the unknown switching control law term which includes a neural network control term, a supervisory control term, and a compensation control term. Also, based on the average dwell-time, a direct adaptive neural switching controller is designed to heighten the robustness of switching system. We can prove to ensure stability of the resulting closed-loop system such that the output tracking performance can be well obtained and all the signals are kept bounded. Simulation results validate the tracking control performance and investigate the effectiveness of the proposed switching control method.

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