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Comparative robustness study of multivariable controller of fixed wing Ultrastick25-e UAV

机译:固定翼Ultrastick25-E UAV多变量控制器的比较稳健性研究

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in this paper three PID based control techniques were designed for discrete time model of Ultra stick UAV in both lateral and longitudinal channels. The three techniques are designed to enhance the control response of Ultra stick UAV. The robustness of the autopilot system to model uncertainty, the rejection of wind disturbances, and dealing with noise effect of sensors are considered as basic items for comparative study of the different control techniques. In the first control technique, the PID is designed and tuned using a genetic algorithm optimization technique. This is to improve the performance and robustness of the system. Adaptive PID fuzzy tuned is considered as the second control technique. Fuzzy tuning is based on seven triangular membership functions for each input and output, where the if-then rules are established based on expert knowledge. The third control technique is PID controller tuned using local optimal control. Each controller technique is designed based on linearized model and SISO decoupled subsystems. The designed controllers are then applied to the real nonlinear and MIMO model. The main contribution in this paper is applying PID controller tuned using local optimal control for the first time on fixed wing UAV. In addition to its simplicity, the comparative simulation results confirm the effectiveness of this controller technique over the other two controller techniques.
机译:在本文中,设计了三种基于PID的控制技术,用于在横向和纵向通道中的超杆UAV的离散时间模型。这三种技术旨在增强超棒UAV的控制响应。自动驾驶系统对模型不确定性的鲁棒性,抑制风扰动,以及处理传感器的噪声效果被认为是不同控制技术的比较研究的基本项目。在第一控制技术中,使用遗传算法优化技术设计和调整PID。这是为了提高系统的性能和鲁棒性。自适应PID模糊调谐被认为是第二控制技术。模糊调谐基于每个输入和输出的七个三角形成员函数,其中IF-DEL规则是根据专家知识建立的。第三种控制技术是使用本地最优控制调谐的PID控制器。每个控制器技术都是基于线性化模型和SISO解耦子系统设计的。然后将设计的控制器应用于真正的非线性和MIMO模型。本文的主要贡献是应用PID控制器,在固定的翼UAV上首次使用本地最优控制进行调整。除了简单性之外,比较仿真结果还证实了该控制器技术对其他两个控制器技术的有效性。

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