| Adaptive Neural Tracking Control for Unknown Output Feedback Nonlinear Time-delay Systems |
| |
| 引用本文： | CHEN Wei-Sheng LI Jun-Min (Department of Applied Mathematics,Xidian University,Xi'an 710071). Adaptive Neural Tracking Control for Unknown Output Feedback Nonlinear Time-delay Systems[J]. 自动化学报, 2005, 0(5) |
| |
| 作者姓名： | CHEN Wei-Sheng LI Jun-Min (Department of Applied Mathematics Xidian University Xi'an 710071) |
| |
| 作者单位： | Department of Applied Mathematics，Xidian University，Xi'an 710071 |
| |
| 基金项目： | Supported by National Natural Science Foundation of P.R.China (60374015) and Natural Science Foundation of Shanxi Province (2003A15) |
| |
| 摘 要： | An adaptive output feedback neural network tracking controller is designed for a class of unknown output feedback nonlinear time-delay systems by using backstepping technique.Neural networks are used to approximate unknown time-delay functions.Delay-dependent filters are intro- duced for state estimation.The domination method is used to deal with the smooth time-delay basis functions.The adaptive bounding technique is employed to estimate the upper bound of the neural network reconstruction error.Based on Lyapunov-Krasoviskii functional,the semi-global uniform ultimate boundedness(SGUUB)of all the signals in the closed-loop system is proved.The arbitrary output tracking accuracy is achieved by tuning the design parameters and the neural node number. The feasibility is investigated by an illustrative simulation example.
|
Adaptive Neural Tracking Control for Unknown Output Feedback Nonlinear Time-delay Systems |
| |
| CHEN Wei-Sheng LI Jun-Min. Adaptive Neural Tracking Control for Unknown Output Feedback Nonlinear Time-delay Systems[J]. Acta Automatica Sinica, 2005, 0(5) |
| |
| Authors: | CHEN Wei-Sheng LI Jun-Min |
| |
| Abstract: | An adaptive output feedback neural network tracking controller is designed for a class of unknown output feedback nonlinear time-delay systems by using backstepping technique.Neural networks are used to approximate unknown time-delay functions.Delay-dependent filters are intro- duced for state estimation.The domination method is used to deal with the smooth time-delay basis functions.The adaptive bounding technique is employed to estimate the upper bound of the neural network reconstruction error.Based on Lyapunov-Krasoviskii functional,the semi-global uniform ultimate boundedness(SGUUB)of all the signals in the closed-loop system is proved.The arbitrary output tracking accuracy is achieved by tuning the design parameters and the neural node number. The feasibility is investigated by an illustrative simulation example. |
| |
| Keywords: | Nonlinear time-delay systems neural network backstepping |
| 本文献已被 CNKI 等数据库收录！ |
