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Adaptive Control with Neural Networks-based Disturbance Observer for a Spherical UAV

机译:基于神经网络的扰动观测器对球形无人机的自适应控制

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This paper develops a control scheme for a Spherical Unmanned Aerial Vehicle (UAV) which can be used in complex scenarios where traditional navigation and communications systems would not succeed. The proposed scheme is based on the nonlinear control theory combined with Adaptive Neural-Networks Disturbance Observer (NN-DOB) and controls the attitude and altitude of the UAV in presence of model uncertainties and external disturbances. The NN-DOB can effectively estimate the uncertainties without the knowledge of their bounds and the control system stability is proven using Lyapunov’s stability theorems. Numerical simulation results demonstrate the validity of the proposed method on the UAV under model uncertainties and external disturbances.
机译:本文开发了一种球形无人飞行器(UAV)的控制方案,该方案可用于传统导航和通信系统无法获得成功的复杂场景。该方案基于非线性控制理论和自适应神经网络扰动观测器(NN-DOB)的组合,并在存在模型不确定性和外部干扰的情况下控制无人机的姿态和高度。 NN-DOB可以在不知道不确定性边界的情况下有效地估计不确定性,并且使用Lyapunov的稳定性定理证明了控制系统的稳定性。数值仿真结果验证了该方法在模型不确定性和外界干扰条件下的有效性。

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