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Dynamical analysis and robust control for dive plane of supercavitating vehicles

机译：超透视车潜水平面的动态分析和鲁棒控制

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The high-speed supercavitating vehicle (HSSV) utilizes advanced technology that enables an underwater vehicle to reach its unprecedented high speed. The vertical motion control of the HSSV is challenging problem because of its complex dynamics with nonlinear planing force, parametric uncertainties, external disturbances, actuator saturation, and sensor noises. This paper deals with dynamical analysis and a robust H infinity loop-shaping synthesis with modified PID (proportional-integral-derivative) algorithm to control the dive plane maneuver of the HSSV. Typically, the control scheme has the low order structure and provides robustness against dynamic uncertainties, which can be implemented using the bilinear matrix inequality (BMI) optimization of an equivalent Schur formula. Simulation results show that the controlled vehicle system provides good performance and high robustness against uncertainties, ensuring no-overshoot and fast in time-domain responses. In addition, the control algorithm can decouple the dynamic interactions in the multi-input multi-output (MIMO) system, overcoming parametric uncertainty, planing force, and actuator saturation while minimizing the effect of the strong external disturbances and measurement noises.
机译：高速超级扫描车辆（HSSV）利用先进技术，使水下车辆能够达到其前所未有的高速。由于其具有非线性刨力，参数不确定性，外部干扰，致动器饱和度和传感器噪声的复杂动态，HSSV的垂直运动控制是具有挑战性的问题。本文涉及动态分析和具有修改的PID（比例 - 积分 - 衍生）算法的鲁棒H无限环形整形合成，以控制HSSV的潜水平面机动。通常，控制方案具有低阶结构，并提供对动态不确定性的鲁棒性，其可以使用等效氏族公式的双线性矩阵不等式（BMI）优化来实现。仿真结果表明，受控车辆系统对不确定性提供了良好的性能和高稳健性，确保无冲动和时域反应快速。此外，控制算法可以将多输入多输出（MIMO）系统中的动态相互作用分离，克服参数不确定度，刨力和致动器饱和，同时最小化强外部干扰和测量噪声的效果。

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