Robust adaptive tracking of stochastic nonlinear systems with uncertain noises
具有不确定噪声的随机非线性系统的鲁棒自适应跟踪

Robust adaptive tracking problems for a class of stochastic nonlinear systems were investigated. A stochastic Lyapunov design method was applied for systems in the form of parametric-strict-feedback driven by Wiener noises of unknown covariance. A parameter adaptive law and a control law were obtained to ensure that the tracking error could converge to a small residual set around the origin in the sense of mean quartic value.