Adaptive neural control and learning of affine nonlinear systems

作者：Wu, Yuxiang; Wang, Cong^*

来源：Neural Computing & Applications, 2014, 25(2): 309-319.

DOI：10.1007/s00521-013-1488-6

• Deterministic learning
• Adaptive NN control
• Affine nonlinear systems
• PE

This paper presents deterministic learning from adaptive neural network control of affine nonlinear systems with completely unknown system dynamics. Thanks to the learning capability of radial basis function, neural network (NN), stable adaptive NN controller is designed for the unknown affine nonlinear systems. The designed adaptive NN controller is rigorously shown that learning of the unknown closed-loop system dynamics can be achieved during the stable control process because partial persistent excitation condition of some internal signals in the closed-loop system is satisfied. Subsequently, neural learning controller using the knowledge obtained from deterministic learning is constructed to achieve closed-loop stability and improve control performance. Numerical simulation is provided to show the effectiveness of the proposed control scheme.

• 出版日期2014-8
• 单位华南理工大学