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GA based design of fuzzy control law for hypersonic vehicle

机译:基于遗传算法的高超声速飞行器模糊控制律设计

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Considering the pitching channel of air breathing hypersonic vehicle X-43A as plant, flight control system was designed according to the 6 degree of freedom nonlinear model. The flight control system includes two loops, of which the structure is conventional mode. The guidance loop is a PD controller, while the control loop is composed of two fuzzy logic controllers. The guidance loop leads the vehicle to follow trajectory, when the control loop follows guidance command. Based on genetic algorithm, the optimization process of PD feedback parameters and fuzzy logic control rules was carried out automatically, which means expert knowledge and training data are not necessary in advance. This optimization process solved the problem of obtaining fuzzy logic control rules. Nonlinear dynamics, uncertainties and restrictions are contained in research on the control of trajectory, attitude and thrust. Simulations show that the method is able to satisfy both the robustness of flight control system and the convergence of optimization process on request.
机译:以呼吸高超音速飞行器X-43A的俯仰通道为植物,根据6自由度非线性模型设计了飞行控制系统。飞行控制系统包括两个回路,其结构为常规模式。引导回路是一个PD控制器,而控制回路则由两个模糊逻辑控制器组成。当控制环遵循引导命令时,引导环引导车辆遵循轨迹。基于遗传算法,PD反馈参数和模糊逻辑控制规则的优化过程是自动进行的,这意味着不需要专家知识和训练数据。该优化过程解决了获得模糊逻辑控制规则的问题。轨迹,姿态和推力的控制研究包含非线性动力学,不确定性和限制条件。仿真表明,该方法既能满足飞行控制系统的鲁棒性,又能满足优化过程的收敛要求。

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