Trajectory-tracking hybrid controller based on ADRC and adaptive control for unmanned helicopters
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摘要: 为满足无人直升机高精度轨迹跟踪的控制需求,并降低直升机动力学模型误差对飞行控制器飞行控制效果产生的影响,提出自抗扰自适应直升机混合控制.该控制器的内环控制采用模型跟随自适应控制,通过使用动量反向传播算法(MOBP)对该内环控制参数进行实时优化.通过使用自抗扰控制(ADRC)对直升机的水平速度进行控制.仿真结果表明,该混合控制器能够实现直升机对预定轨迹的跟踪.相对PID和级联ADRC控制,该控制器具有更好的抗扰性和鲁棒性.通过在200 kg级的专业植保无人直升机XV-2上搭载所提出的控制器,使其自主飞行轨迹跟踪控制的均方根误差在0.6 m以内.Abstract: To enable unmanned helicopters to fly autonomously in precise paths and to reduce the influence of helicopter dynamic model error, this paper proposes a hybrid controller with active disturbance rejection control (ADRC) and adaptive control for trajectory tracking. This paper proposes the model reference adaptive control strategy for the inner-loop controller. This paper uses the momentum back-propagation (MOBP) neural network algorithm to tune the parameters of the proposed inner-loop controller. This paper uses ADRC in the proposed controller for velocity control. The simulation results indicate that the proposed controller can achieve good trajectory tracking. Compared with the PID controller and cascade ADRC, the proposed hybrid controller is more robust and has better anti-disturbance capability. This paper uses the proposed hybrid controller for trajectory-tracking control of the XV-2, which is an unmanned helicopter with a gross take-off weight level of 200 kg. With the help of the hybrid controller in our flight test, the root mean square error of the XV-2 trajectory-tracking control is within 0.6 m.
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