四旋翼飞行仿真器的多变量控制器设计与研究
发布时间：2018-11-22 14:44
【摘要】：针对目前工程领域中的多输入、多输出(MIMO)系统,以四旋翼飞行仿真器为研究平台,设计了两套控制器,分别采用线性二次型(LQ-Linear Quadratic)最优控制方法和一种类似于规则分解的多变量模糊控制法。在Matlab/Simulink中建立其控制模型,并利用实时工具箱(Real-Time-Workshop)实现实时控制。实际控制结果表明,线性二次型最优控制器在合理选择加权矩阵Q、R基础上,所设计的控制器对于系统从初始状态至零位的阶跃响应和给定输入的轨迹跟踪有良好的控制性能。采用多组二维模糊控制器,通过分析被控对象机理特性,对输出进行整合多变量模糊控制器,其控制性能与线性二次型控制器相近,两者对于线性、定常、具有强耦合的多变量控制系统都具有良好的控制效果。
[Abstract]:Aiming at the multi-input and multi-output (MIMO) systems in the engineering field, two sets of controllers are designed based on the four-rotor flight simulator. The linear quadratic form (LQ-Linear Quadratic) optimal control method and a multivariable fuzzy control method similar to rule decomposition are used respectively. The control model is established in Matlab/Simulink, and the real-time control is realized by real-time toolbox (Real-Time-Workshop). The actual control results show that the linear quadratic optimal controller is based on the rational selection of the weighting matrix QR. The designed controller has good control performance for the step response from the initial state to the zero position and the trajectory tracking of the given input. By analyzing the mechanism characteristics of the controlled object, the output is integrated with the multi-variable fuzzy controller. The control performance of the fuzzy controller is similar to that of the linear quadratic controller. The multivariable control system with strong coupling has good control effect.
【作者单位】： 江西理工大学机电工程学院;
【分类号】：V249.1
本文编号：2349665
[Abstract]:Aiming at the multi-input and multi-output (MIMO) systems in the engineering field, two sets of controllers are designed based on the four-rotor flight simulator. The linear quadratic form (LQ-Linear Quadratic) optimal control method and a multivariable fuzzy control method similar to rule decomposition are used respectively. The control model is established in Matlab/Simulink, and the real-time control is realized by real-time toolbox (Real-Time-Workshop). The actual control results show that the linear quadratic optimal controller is based on the rational selection of the weighting matrix QR. The designed controller has good control performance for the step response from the initial state to the zero position and the trajectory tracking of the given input. By analyzing the mechanism characteristics of the controlled object, the output is integrated with the multi-variable fuzzy controller. The control performance of the fuzzy controller is similar to that of the linear quadratic controller. The multivariable control system with strong coupling has good control effect.
【作者单位】： 江西理工大学机电工程学院;
【分类号】：V249.1
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