胡伟伟, 赵文龙, 蒋沅. 八旋翼动力学建模及RBF神经网络PID控制研究[J]. 南昌航空大学学报(自然科学版), 2018, 32(1): 29-34. DOI: 10.3969/j.issn.1001-4926.2018.01.005
引用本文: 胡伟伟, 赵文龙, 蒋沅. 八旋翼动力学建模及RBF神经网络PID控制研究[J]. 南昌航空大学学报(自然科学版), 2018, 32(1): 29-34. DOI: 10.3969/j.issn.1001-4926.2018.01.005
HU Wei-wei, ZHAO Wen-long, JIANG Yuan. Research on Eight-Rotor Modeling and RBF Neural Network PID Control[J]. Journal of nanchang hangkong university(Natural science edition), 2018, 32(1): 29-34. DOI: 10.3969/j.issn.1001-4926.2018.01.005
Citation: HU Wei-wei, ZHAO Wen-long, JIANG Yuan. Research on Eight-Rotor Modeling and RBF Neural Network PID Control[J]. Journal of nanchang hangkong university(Natural science edition), 2018, 32(1): 29-34. DOI: 10.3969/j.issn.1001-4926.2018.01.005

八旋翼动力学建模及RBF神经网络PID控制研究

Research on Eight-Rotor Modeling and RBF Neural Network PID Control

  • 摘要: 针对八旋翼飞行器非线性、强耦合、欠驱动、多输入多输出的系统特点,综合八旋翼动力学特性进行数学公式推导,建立数学模型。利用模型解耦八旋翼各通道输入量与输出量之间的关系。提出RBF神经网络自适应PID控制策略,该策略能够根据控制效果在线自适应整定PID参数,具有自主学习和自适应能力。通过matlab搭建八旋翼仿真模型并对其仿真,对比分析RBF神经网络自适应PID和传统PID控制效果。结果表明:前者控制效果明显优于后者,系统快速性、鲁棒性和稳定性得到了很大改善。

     

    Abstract: Aiming at the characteristics of non-linear, strong coupling, under-drive and multi-input multi-output of eight-rotor aircraft, the mathematic model is deduced by combining the eight-rotor dynamic characteristics. The relationship between the input and the output of each channel is decoupled by using the model. The RBF neural network adaptive PID control strategy is proposed, which can adaptively adjust the PID parameters according to the control effect, and has the ability of autonomous learning and self-adaptability. Through the matlab simulation model of eight-rotor and its simulation, the RBF neural network adaptive PID and traditional PID control effect are compared and analyzed. The results show that the former control effect is better than the latter, the system fastness, robustness and stability has been greatly improved.

     

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