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Fuzzy-Genetic Autopilot Design for Nonminimum Phase and Nonlinear Unmanned Aerial Vehicles

机译:非最小相位和非线性无人机的模糊遗传自动驾驶仪设计

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摘要

In this paper, the authors tried to design the altitude hold mode autopilot for unmanned aerial vehicles. This case presents an interesting challenge attributable to the nonminimum phase characteristic, nonlinearities, and uncertainties of the altitude to elevator relationship. A fuzzy logic autopilot in a single-loop scheme is proposed for the design of this autopilot. The multiobjective genetic algorithm is used to mechanize the optimal determination of fuzzy logic autopilot parameters on the basis of an efficient cost function that comprises undershoot, overshoot, rise time, settling time, steady state error, and stability. Simulation results show that the proposed strategy not only has a simple structure, but also has desirable performances in time response characteristics, robustness (against the unmodeled nonlinear terms and parametric uncertainties), and the adaptation of itself than the large commands.
机译:在本文中,作者试图设计用于无人机的高度保持模式自动驾驶仪。这种情况提出了一个有趣的挑战,这归因于非最小相位特性,非线性和高度与电梯之间关系的不确定性。针对该自动驾驶仪的设计,提出了单回路方案中的模糊逻辑自动驾驶仪。多目标遗传算法用于基于包括下冲,上冲,上升时间,建立时间,稳态误差和稳定性的有效成本函数,机械化模糊逻辑自动驾驶仪参数的最佳确定。仿真结果表明,所提出的策略不仅结构简单,而且在时间响应特性,鲁棒性(针对未建模的非线性项和参数不确定性)以及自身的适应性等方面均具有优于大型命令的性能。

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