Adaptive Neural Backstepping for a Class of Switched Nonlinear System Without Strict-Feedback Form

作者：Liu, Zhiliang; Chen, Bing^*; Lin, Chong

来源：IEEE Transactions on Systems, Man, and Cybernetics: Systems , 2017, 47(7): 1315-1320.

DOI：10.1109/TSMC.2016.2585664

• Adaptive neural control
• backstepping
• nonstrict feedback form
• switched nonlinear systems

This paper focuses on backstepping-based adaptive neural control for switched nonlinear systems in nonstrict-feedback form. A structural characteristic of radial basis function neural networks is first developed. With this structural characteristic, adaptive neural backstepping has been extended to the switched nonlinear systems with nonstrict-feedback structure. By using a common Lyapunov function method, an adaptive neural controller is constructed by backstepping technique. It is shown that under the action of the suggested controller, all the closed-loop signals are bounded and meanwhile the system output follows the desired reference signal well. Finally, a numerical simulation example is used to illustrate the effectiveness of our results.

• 出版日期2017-7
• 单位青岛大学