Direct adaptive neural control for strict-feedback stochastic nonlinear systems

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

来源：Nonlinear Dynamics, 2012, 67(4): 2703-2718.

DOI：10.1007/s11071-011-0182-4

• Direct adaptive control
• Neural network
• Backstepping
• Separation technique
• Stochastic nonlinear systems

This note considers the problem of direct adaptive neural control for a class of nonlinear single-input/single-output (SISO) strict-feedback stochastic systems. The variable separation technique is introduced to decompose the coefficient functions of the diffusion term. Radical basis RBF) neural networks are used to approximate unknown and desired control signals, then a novel direct adaptive neural controller is constructed via backstepping. The proposed adaptive neural controller guarantees that all the signals in the closed-loop system remain bounded in probability. A main advantage of the proposed controller is that it contains only one adaptive parameter needed to be updated online. Simulation results demonstrate the effectiveness of the proposed approach.

• 出版日期2012-3
• 单位青岛大学; 渤海大学