DocumentCode :
1196968
Title :
Robust Output Feedback Tracking Control for Time-Delay Nonlinear Systems Using Neural Network
Author :
Hua, Changchun ; Guan, Xinping ; Shi, Peng
Author_Institution :
Inst. of Electr. Eng., Yanshan Univ., Qinhuangdao
Volume :
18
Issue :
2
fYear :
2007
fDate :
3/1/2007 12:00:00 AM
Firstpage :
495
Lastpage :
505
Abstract :
In this paper, the problem of robust output tracking control for a class of time-delay nonlinear systems is considered. The systems are in the form of triangular structure with unmodeled dynamics. First, we construct an observer whose gain matrix is scheduled via linear matrix inequality approach. For the case that the information of uncertainties bounds is not completely available, we design an observer-based neural network (NN) controller by employing the backstepping method. The resulting closed-loop system is ensured to be stable in the sense of semiglobal boundedness with the help of changing supplying function idea. The observer and the controller designed are both independent of the time delays. Finally, numerical simulations are conducted to verify the effectiveness of the main theoretic results obtained
Keywords :
closed loop systems; control system synthesis; delay systems; feedback; linear matrix inequalities; neurocontrollers; nonlinear control systems; observers; robust control; backstepping method; closed loop system; linear matrix inequality; neural network control; observer; robust output feedback tracking control; time-delay nonlinear system; Backstepping; Control systems; Linear matrix inequalities; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Output feedback; Robust control; Uncertainty; Backstepping method; neural network (NN); observer design; time-delay systems; Algorithms; Artificial Intelligence; Computer Simulation; Feedback; Information Storage and Retrieval; Models, Theoretical; Neural Networks (Computer); Nonlinear Dynamics; Pattern Recognition, Automated; Time Factors;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/TNN.2006.888368
Filename :
4118263
Link To Document :
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