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Robust Adaptive Controller Design for Missile with Three-tunnel Input Unmodeled Dynamics and Uncertainties

机译:具有三隧道的导弹的强大自适应控制器设计输入未刻度动态和不确定性

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For a missile system with both input unmodeled dynamics and uncertainties, a robust adaptive controller based on RBF neural networks and back-stepping technique is proposed. Two RBF neural networks are firstly designed to approximate the input unmodel ed dynamics and its inversion. By introducing adaptive control technique, uncertainties are estimated by adaptive law. Then, adaptive tuning law of weight matrices and uncertain parameters are designed using Lyapunov stability theory based back-stepping technique. The developed control scheme guarantees the global stability of the close-loop adaptive systems. Finally, 6DOF simulation results of missile are given to validate the correctness of the control scheme.
机译:对于导弹系统,具有输入的未拼件动态和不确定性,提出了一种基于RBF神经网络和后台技术的鲁棒自适应控制器。首先设计两个RBF神经网络,以近似输入未映像ED动力学及其反转。通过引入自适应控制技术,通过自适应法估算不确定性。然后,使用基于Lyapunov稳定性理论的基础技术设计了重量矩阵和不确定参数的自适应调整规律。开发的控制方案保证了闭环自适应系统的全局稳定性。最后,给出了导弹的6DOF仿真结果验证了控制方案的正确性。

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