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New robust control analysis methodology for Lynx helicopter and Cessna Citation X aircraft using Guardian Maps, Genetic Algorithms and LQR theories combinations

机译:使用Guardian Maps,遗传算法和LQR理论组合为Lynx直升机和Cessna Citation X飞机提供新的鲁棒控制分析方法

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Autopilot analysis is a very complex stage in the design of an airplane or a helicopter. In addition to providing maneuverability criteria, the autopilot must be robust to uncertainties or changes in physical parameters changes. Using the LQR (Linear Quadratic Regulator) theory, a genetic algorithm and the guardian map theory, a methodology is described for designing an internal controller to be used by an the autopilot which satisfies accurate handling qualities while remaining robust. The algorithms were developed in Matlab® and the simulations were realized with Simulink®. A full nonlinear model of the Cessna Citation X and six linear models of the Lynx Helicopter for different speeds are used to show the results and evaluate the efficiency of the methodology.
机译:自动驾驶分析是飞机或直升机设计中非常复杂的阶段。除了提供机动性标准之外,自动驾驶仪还必须对不确定性或物理参数变化的变化具有鲁棒性。使用LQR(线性二次调节器)理论,遗传算法和监护人图论,描述了一种方法,用于设计自动驾驶仪使用的内部控制器,该控制器可满足精确的操纵质量,同时保持鲁棒性。算法是在Matlab®中开发的,并且仿真是通过Simulink®实现的。使用塞斯纳Citation X的完整非线性模型和Lynx直升机的六个线性模型(针对不同速度)来显示结果并评估该方法的效率。

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