超高速飞行器自适应模糊超螺旋控制律设计OACSTPCD
Adaptive Fuzzy Super-Twisting Control Law for Ultra-high-speed Vehicle
针对超高速飞行器多源扰动下高精强鲁棒控制需求,提出了一种自适应模糊超螺旋控制律.首先,给出控制导向的超高速飞行器姿态模型;其次,采用广义超螺旋算法设计控制器,实现滑模变量与跟踪误差的高精收敛;同时,引入高阶齐次观测器估计飞行器复杂扰动,并在控制律中做前馈补偿以提高算法鲁棒性.针对控制增益选取问题,基于模糊算法,通过融合专家经验,建立控制增益与滑模变量直接关联.相较传统自适应方法,该自适应律可实现控制增益快速调节整定,同时兼顾系统响应速度、鲁棒性与抖振抑制需求.最后,以考虑复杂多源干扰的超高速飞行器为对象进行仿真,结果证明了自适应模糊超螺旋控制律的有效性.
An adaptive fuzzy super-twisting control law is proposed to meet the high-precision and robust control requirements for ultra-high speed vehicle under multi-source disturbances.First,a control-oriented dynamic model for ultra-high speed vehicle is established.Second,the controller is designed by the generalized super-twisting algorithm to achieve the high-precision convergence of sliding mode variables and tracking errors.Meanwhile,a high-order homogeneous observer is introduced into the controller to estimate the complex disturbances of the vehicle,and feedforward compensation is done in the control law,which can improve the robustness of the controller.Subsequently,a direct correlation between the control gain and the sliding mode variables is established based on the adaptive fuzzy law and expert experience.Compared with traditional adaptive laws,the proposed adaptive law can achieve the control gain adjustment quickly,while balancing the control requirements such as response speed,robustness,and chattering suppression.Finally,an ultra-high speed vehicle considering complex multi-source disturbances is simulated,and the obtained results demonstrate that the adaptive fuzzy super-twisting control law is effective.
岳晓奎;郭容義;丁一波;王玉浩
西北工业大学 航天学院,陕西 西安 710072||西北工业大学 深圳研究院,广东 深圳,518063||西北工业大学 航天飞行动力学技术重点实验室,陕西 西安 710072北京机电工程研究所,北京 100074
电子信息工程
超高速飞行器广义超螺旋算法高阶齐次观测器模糊算法自适应控制
ultra-high speed vehiclegeneralized super-twisting algorithmhigh-order homogeneous observerfuzzy algorithmadaptive control
《上海航天(中英文)》 2024 (003)
17-24,36 / 9
国家自然科学基金(12372048,12102343,U2013206);中国博士后科学基金资助项目(2023M742835);航空科学基金资助项目(2022Z004053001);陕西省科学技术协会青年人才托举计划项目(20220509);航天飞行动力学技术重点实验室基金(KJW6142210210304);广东省基础与应用基础研究基金(2023A1515011421);中央高校基本科研业务费专项资金(D5000210833)
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