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The Implementation and Lateral Control Optimization of a UAV Based on Phase Lead Compensator and Signal Constraint Controller

机译:基于相位引线补偿器和信号约束控制器的无人机的实现与横向控制优化

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摘要

Unmanned Aero Vehicles (UAV) has become a useful entity for quite a good number of industries and facilities. It is an agile, cost effective and reliable solution for communication, defense, security, delivery, surveillance and surveying etc. However, their reliability is dependent on the resilient and stabilizes performance based on control systems embedded behind the body. Therefore, the UAV is majorly dependent upon controller design and the requirement of particular performance parameters. Nevertheless, in modern technologies there is always a room for improvement. In the similar manner a UAV lateral control system was implemented and researched in this study, which has been optimized using Proportional, Integral and Derivative (PID) controller, phase lead compensator and signal constraint controller. The significance of this study is the optimization of the existing UAV controller plant for improving lateral performance and stability. With this UAV community will benefit from designing robust controls using the optimized method utilized in this paper and moreover this will provide sophisticated control to operate in unpredictable environments. It is observed that results obtained for optimized lateral control dynamics using phase lead compensator (PLC) are efficacious than the simple PID feedback gains. However, for optimizing unwanted signals of lateral velocity, yaw rate, and yaw angle modes, PLC were integrated with PID to achieve dynamical stability.
机译:无人驾驶航空公司(UAV)已成为一个有用的实体,以获得相当多的行业和设施。它是一种敏捷,成本效益和可靠的沟通,防御,安全,交付,监控等解决方案,但其可靠性取决于基于嵌入式后面的控制系统的弹性和稳定性能。因此,UAV主要取决于控制器设计和特定性能参数的要求。尽管如此,在现代技术中,总有一个改进的空间。以类似的方式在本研究中实现和研究了UAV横向控制系统,其已经使用比例,积分和导数(PID)控制器,相位引线补偿器和信号约束控制器进行了优化。本研究的重要性是优化现有的UAV控制器工厂,用于提高横向性能和稳定性。通过这种UAV社区将使用本文中使用的优化方法来利用设计强大的控制,此外,这将提供复杂的控制在不可预测的环境中运行。观察到使用相位引线补偿器(PLC)获得优化的横向控制动态的结果是有效的,而不是简单的PID反馈增益。然而,为了优化横向速度,横摆率和偏航角度模式的不需要的信号,PLC与PID集成以实现动力学稳定性。

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