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A Novel Backstepping Adaptive Control Approach Based on Fuzzy Neural Network Disturbance Observer

机译:一种基于模糊神经网络障碍观察者的新型反静电自适应控制方法

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A fuzzy neural network disturbance observer (FNNDO) is developed and a backstepping adaptive control approach combined with FNNDO is presented for a general class of strict-feedback nonlinear systems with a wide class of uncertainties that are not linearly parameterized and do not have any prior knowledge of the bounding functions. FNNDO is used to approximate the unknown uncertainties online, and the systematic framework for adaptive controller design is given by backstepping control approach. All signals in the closed loop system can be guaranteed uniformly ultimately bounded by Lyapunov approach. We show in our analysis and simulation that FNNDO has strong approximation ability and fuzzy linguistic interpretation. High control precision for the control system can be achieved.
机译:开发了一种模糊神经网络扰动观察者(FNNDO),并呈现与FNNDO相结合的反向梗自适应控制方法,用于一般的严格反馈非线性系统,具有广泛的不确定性,这些不确定因素没有线性参数化,并且没有任何先前的知识边界功能。 FNNDO用于近似于在线未知的不确定性,通过反向控制方法给出自适应控制器设计的系统框架。闭环系统中的所有信号都可以通过Lyapunov方法均匀地限制。我们在我们的分析和模拟中展示了FNNDO具有强烈的近似能力和模糊语言解释。可以实现对控制系统的高控制精度。

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