A MULTILAYER RECURRENT NEURAL NETWORK FOR REAL-TIME ROBUST POLE ASSIGNMENT IN SYNTHESIZING OUTPUT FEEDBACK CONTROL SYSTEMS

2002 ◽  
Vol 35 (1) ◽  
pp. 271-276
Author(s):  
Sanqing Hu ◽  
Jun Wang
Keyword(s):  
Neural Network ◽  
Feedback Control ◽  
Control Systems ◽  
Real Time ◽  
Recurrent Neural Network ◽  
Output Feedback ◽  
Output Feedback Control ◽  
Pole Assignment ◽  
Feedback Control Systems

scholarly journals H∞Output-Feedback Tracking Control for Networked Control Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Sung Hyun Kim
Keyword(s):  
Feedback Control ◽  
Control Systems ◽  
Output Feedback ◽  
Networked Control Systems ◽  
Output Feedback Control ◽  
Single Step ◽  
Linear Matrix ◽  
Tracking Problem ◽  
Transmission Delays ◽  
Feedback Control Systems

This paper investigates the observer-basedH∞tracking problem of networked output-feedback control systems with consideration of data transmission delays, data-packet dropouts, and sampling effects. Different from other approaches, this paper offers a single-step procedure to handle nonconvex terms that appear in the process of designing observer-based output-feedback control, and then establishes a set of linear matrix inequality conditions for the solvability of the tracking problem. Finally, two numerical examples are given to illustrate the effectiveness of our result.

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