Nonlinear Adaptive Model Following Control for a 3-DOF Model Helicopter
Nonlinear Adaptive Model Following Control for a 3-DOF Model Helicopter
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三自由度模型直升机的非线性自适应模型跟随控制
DOI：
10.5772/9131
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
M. Nishi
中科院分区：
文献类型：
--
作者：
M. Ishitobi;M. Nishi
由于这一研究领域的重要潜在应用，在过去十年左右的时间里，人们对设计直升机反馈控制器的兴趣有所增加。直升机稳定反馈控制器设计的主要困难来自于这些飞机动力学的非线性和耦合。到目前为止，已作出各种努力来制定有效的直升机非线性控制战略(Sira-Ramirez等人，1994年；Kaloust等人，1997年；Kutay等人，2005年；Avila等人，2003年)。Sira-Ramirez等人。将动态滑模控制应用于垂直飞行非线性直升机模型的高度稳定。Kaloust等人。针对直升机垂直飞行状态，提出了一种基于李亚普诺夫的非线性鲁棒控制方案。Avila等人。建立了7自由度直升机的非线性三自由度模型，并在实验系统中实现了线性化控制器。现有的大部分结果都与飞行监管有关。研究了三自由度模型直升机跟踪控制的双输入、双输出非线性模型。由于解耦矩阵是奇异的，采用了一种非线性结构算法(Shima等人，1997；Isurugi，1990)来设计控制器。此外，由于模型动态由未知系统参数线性描述，因此在闭环系统中引入了一种参数辨识方案。讨论了两种参数辨识方法：一种是基于微分方程模型的参数辨识方法。实验中发现，由于估计的速度和加速度信号不准确，该模型很难获得良好的跟踪控制性能。第二种参数辨识方法是基于将积分算子应用于表示系统动力学的微分方程导出的动力学模型。因此，该辨识算法既不需要速度信号，也不需要加速度信号。第二种方法的实验结果表明，在跟踪误差较大的情况下，该方法取得了较好的跟踪效果。最后，我们在运动方程中引入了表示模型不确定性和外部扰动的附加项。实验数据表明，包含这些附加项的方法具有最好的控制性能。9.
Interest in designing feedback controllers for helicopters has increased over the last ten years or so due to the important potential applications of this area of research. The main difficulties in designing stable feedback controllers for helicopters arise from the nonlinearities and couplings of the dynamics of these aircraft. To date, various efforts have been directed to the development of effective nonlinear control strategies for helicopters (Sira-Ramirez et al., 1994; Kaloust et al., 1997; Kutay et al., 2005; Avila et al., 2003). Sira-Ramirez et al. applied dynamical sliding mode control to the altitude stabilization of a nonlinear helicopter model in vertical flight. Kaloust et al. developed a Lyapunov-based nonlinear robust control scheme for application to helicopters in vertical flight mode. Avila et al. derived a nonlinear 3-DOF (degree-of-freedom) model as a reduced-order model for a 7-DOF helicopter, and implemented a linearizing controller in an experimental system. Most of the existing results have concerned flight regulation. This study considers the two-input, two-output nonlinear model following control of a 3-DOF model helicopter. Since the decoupling matrix is singular, a nonlinear structure algorithm (Shima et al., 1997; Isurugi, 1990) is used to design the controller. Furthermore, since the model dynamics are described linearly by unknown system parameters, a parameter identification scheme is introduced in the closed-loop system. Two parameter identification methods are discussed: The first method is based on the differential equation model. In experiments, it is found that this model has difficulties in obtaining a good tracking control performance, due to the inaccuracy of the estimated velocity and acceleration signals. The second parameter identification method is designed on the basis of a dynamics model derived by applying integral operators to the differential equations expressing the system dynamics. Hence this identification algorithm requires neither velocity nor acceleration signals. The experimental results for this second method show that it achieves better tracking objectives, although the results still suffer from tracking errors. Finally, we introduce additional terms into the equations of motion that express model uncertainties and external disturbances. The resultant experimental data show that the method constructed with the inclusion of these additional terms produces the best control performance. 9