Adaptive Neural Tracking Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis

作者：Wang, Huanqing^*; Chen, Bing; Liu, Kefu; Liu, Xiaoping; Lin, Chong

来源：IEEE Transactions on Neural Networks and Learning Systems, 2014, 25(5): 947-958.

DOI：10.1109/TNNLS.2013.2283879

• Adaptive neural control
• backlash-like hysteresis
• backstepping
• nonstrict-feedback structure
• stochastic nonlinear systems

This paper considers the problem of adaptive neural control of stochastic nonlinear systems in nonstrict-feedback form with unknown backlash-like hysteresis nonlinearities. To overcome the design difficulty of nonstrict-feedback structure, variable separation technique is used to decompose the unknown functions of all state variables into a sum of smooth functions of each error dynamic. By combining radial basis function neural networks' universal approximation capability with an adaptive backstepping technique, an adaptive neural control algorithm is proposed. It is shown that the proposed controller guarantees that all the signals in the closed-loop system are four-moment semiglobally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood of the origin in the sense of mean quartic value. Simulation results further show the effectiveness of the presented control scheme.

• 出版日期2014-5
• 单位青岛大学; 渤海大学