不确定性下扑翼飞行器的自适应滑模控制  

Adaptive Sliding Mode Control of Flapping Wing Aerial Vehicle with Uncertainties

作　　者：韩建福 杜昌平[1] 郑耀[1] HAN Jian-fu;DU Chang-ping;ZHENG Yao(School of Aeronautics and Astronautics,Zhejiang University,Hangzhou 310027,China)

机构地区：[1]浙江大学航空航天学院,浙江杭州310027

出　　处：《控制工程》2022年第11期2090-2096,共7页Control Engineering of China

基　　金：装备预研教育部联合基金(重点)项目(6141A02011803)。

摘　　要：针对扑翼飞行器空气动力学模型难以建立、存在复杂扰动等导致无法对其进行精确控制的问题,提出一种基于扩张状态观测器和在线学习的自适应滑模控制器设计方案。该方案首先建立扩张状态观测器以降低系统未建模动态及外界扰动的不确定性对系统控制性能的影响,同时设计自适应非线性滑模趋近律,在传统滑模控制器基础上结合强化学习思想,随扑翼飞行器工作过程在线优化趋近律参数,降低控制器对精确参数及扰动信息的依赖程度,提高系统响应速度及飞行稳定性。仿真结果表明,相对于传统滑模控制器优化方法,该自适应控制器框架能够平衡抖振与响应速度的冲突,提高系统鲁棒性和控制精度,可解决扑翼飞行器等存在模型不确定性及复杂扰动下的控制问题。Due to the difficulty to establish an aerodynamic model and the complex disturbances, the flapping wing aerial vehicle(FWAV) cannot be accurately controlled at present. A framework of adaptive sliding mode controller based on an extended state observer and online learning is proposed in this paper. First, the extended state observer is established to reduce the impact of the system with unmodeled dynamics and external disturbances on the system control performance. Meanwhile, an adaptive nonlinear sliding mode approaching law is designed for the traditional sliding mode controller. Combined with the reinforcement learning method,the parameters of this approaching law are optimized online with the flight process of the FWAV. The dependence of the controller on precise parameters and disturbances is reduced, and the response speed and flight stability of the system are improved. The simulation results show that, compared with the traditional optimization methods of sliding mode controller, the proposed framework of adaptive controller can balance chattering and response speed. It improves the robustness and control accuracy of the system, and can solve the control problems of the FWAV with model uncertainties and complex disturbances.

关 键 词：扑翼飞行器 自适应控制 Sarsa算法 强化学习 扩张状态观测器 

分 类 号：V249.1[航空宇航科学与技术—飞行器设计]