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Robust output feedback control for the trajectory tracking of robotic wheelchairs

机译:机器人轮椅轨迹跟踪的鲁棒输出反馈控制

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This paper addresses the trajectory tracking control problem of robotic wheelchairs in the presence of modeling uncertainties. The controller has been designed using position and angular measurements. A global ultra-model, or simplified model achieved from flatness considerations is proposed first. This model highly reduces the design complexity of the state estimation and the output feedback control tasks since it groups, as an unknown time-varying disturbance, both the combined effects of all uncertain state-dependent (i.e., endogenous) nonlinearities and those of external (i.e., exogenous) perturbation inputs which are present in the input-to-flat output model of the system. An extended linear high-gain observer, or Generalized Proportional Integral (GPI) observer, is then developed for the simultaneous, though approximate, state and disturbance estimation. The proposed feedback controller combines the global ultra-model and the GPI observers to conform an active disturbance rejection, or disturbance accommodation, control scheme. The simulation results presented in the paper show that the proposed method has a very good tracking performance and robustness in the presence of system uncertainties, external disturbances and noisy corruptions.
机译:本文解决了存在模型不确定性的机器人轮椅的轨迹跟踪控制问题。使用位置和角度测量来设计控制器。首先提出了从平面度考虑因素获得的全局超模型或简化模型。该模型极大地降低了状态估计和输出反馈控制任务的设计复杂性,因为它将未知状态相关的(即内生的)非线性与外部(外部)不确定性的组合效应作为未知的时变扰动进行分组即,外生的扰动输入,它们存在于系统的输入到单位输出模型中。然后开发一个扩展的线性高增益观测器,或广义比例积分(GPI)观测器,用于同时(尽管是近似)状态和扰动估计。所提出的反馈控制器结合了全局超模型和GPI观测器,以建立主动的干扰抑制或干扰调节控制方案。仿真结果表明,该方法在存在系统不确定性,外部干扰和噪声干扰的情况下具有很好的跟踪性能和鲁棒性。

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