一类非线性输入时滞系统自适应控制——无源化方法

摘要

针对一类含输入时滞的不确定严反馈非线性系统,设计了有记忆时滞依赖型γ-无源自适应控制器.首先,在局部线性化的基础上设计了有记忆时滞依赖型γ-无源控制器.针对严反馈非线性系统各个子系统中的非线性,利用Back-stepping方法将局部.γ-无源控制律进行分解,得到线性的中间虚拟控制律,在此基础上,利用神经网络补偿各子系统的非线性部分,将上述过程整合即得到系统的最终控制律.控制器的特点是针对系统中的输入时滞,反馈控制律采用有记忆的时滞依赖型控制策略,即系统的反馈控制律不仅与当前的系统状态有关,还与系统的时滞过程中的控制作用有关.这种控制方法比无记忆时滞独立型控制保守性更小.稳定性分析中,证明了闭环系统是一致终态有界稳定的.%The γ/-passivity delay-dependent control approach was presented for uncertain strict-feedback nonlinear systems with input-delay. First, the delay-dependent γ-passivity controller for the local linearization section of the nonlinear model was designed. Then, a γ-passivity control law of a local linear model was decomposed as the virtual control of sub-systems by the backstepping approach. In order to compensate for the nonlinear dynamics, an adaptive neural model was proposed. The design procedure of whole systems was regarded as a combination of a local γ-passivity control and adaptive neural network compensation techniques. One important feature of the presented scheme is that the controller with input history feedback had a lower conservation level than the ones without memory. Stability analysis implies that the closed-loop system is ultimately uniformly bounded.