期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS
卷 21, 期 2, 页码 345-351出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2009.2038999
关键词
Backstepping; dynamic surface control (DSC); Fourier series expansion (FSE); integral-type Lyapunov function (ILF); multilayer neural network (MNN); nonlinearly parameterized systems; periodically time-varying disturbances
类别
资金
- National Natural Science Foundation of China [60804021, 60703107, 60703108, 60803098]
This brief addresses the problem of designing adaptive neural network tracking control for a class of strict-feedback systems with unknown time-varying disturbances of known periods which nonlinearly appear in unknown functions. Multilayer neural network (MNN) and Fourier series expansion (FSE) are combined into a novel approximator to model each uncertainty in systems. Dynamic surface control (DSC) approach and integral-type Lyapunov function (ILF) technique are combined to design the control algorithm. The ultimate uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. Two simulation examples are provided to illustrate the feasibility of control scheme proposed in this brief.
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