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传统直升机动态逆控制器包含标称系统动态线性化部分,以及用于实现期望闭环动态的线性控制部分。针对其依赖于直升机精确非线性模型而鲁棒性较差的问题,提出了一种改进的黑鹰UH-60直升机动态逆控制方法,其中逆模型为基于悬停飞行条件下的线性模型。对模型简化、非线性和飞行条件差异所产生的逆误差,引入在线神经网络进行补偿并对系统稳定性进行了分析。非线性仿真结果表明,在不同飞行条件产生的扰动作用下,系统输出响应能够跟踪指定输入,进而说明控制器具有良好的鲁棒性。
The conventional helicopter dynamic inverse controller includes the nominal system dynamic linearization section and the linear control section for achieving the desired closed-loop dynamics. In order to solve the problem of poor robustness which depends on the accurate non-linear model of helicopter, an improved dynamic inverse control method of the Black Hawk UH-60 helicopter is proposed, in which the inverse model is a linear model based on hovering flight. The inverse error caused by the model simplification, nonlinearity and flight condition difference was introduced into online neural network to compensate and analyze the stability of the system. The nonlinear simulation results show that the system output response can track the specified input under the disturbance caused by different flight conditions, which shows that the controller has good robustness.