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Robust tracking enhancement of robot systems including motor dynamics: a fuzzy-based dynamic game approach

机译:机器人系统(包括电机动力学)的鲁棒跟踪增强:基于模糊的动态博弈方法

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A robust tracking control design of robot systems including motor dynamics with parameter perturbation and external disturbance is proposed in this study via adaptive fuzzy cancellation technique. A minimax controller equipped with a fuzzy-based scheme is used to enhance the tracking performance in spite of system uncertainties and external disturbance. The design procedure is divided into three steps. At first, a linear nominal robotic control design is obtained via model reference tracking with desired eigenvalue assignment. Next, a fuzzy logic system is constructed and then tuned to eliminate the nonlinear uncertainties as possibly as it can to enhance the tracking robustness. Finally, a minimax control scheme is specified to optimally attenuate the worst-case effect of both the residue due to fuzzy cancellation and external disturbance to achieve a minimax tracking performance. In addition, an adaptive fuzzy-based dynamic game theory is introduced to solve the minimax tracking problem. The proposed method is appropriate for the robust tracking design of robotic systems with large parameter perturbation and external disturbance. A simulation example of a two-link robotic manipulator driven by DC motors is also given to demonstrate the effectiveness of proposed design method's tracking performance.
机译:通过自适应模糊抵消技术,提出了一种鲁棒的机器人系统跟踪控制设计,包括带有参数摄动和外部干扰的电机动力学。尽管系统存在不确定性和外部干扰,但配备基于模糊方案的minimax控制器仍可用于增强跟踪性能。设计过程分为三个步骤。首先,通过具有期望特征值分配的模型参考跟踪获得线性标称机器人控制设计。接下来,构建一个模糊逻辑系统,然后对其进行调整以尽可能消除非线性不确定性,以增强跟踪的鲁棒性。最后,指定了一个minimax控制方案,以最佳地衰减由于模糊消除和外部干扰而导致的残差的最坏情况影响,从而实现minimax跟踪性能。另外,引入了基于自适应模糊的动态博弈理论来解决最小极大跟踪问题。所提出的方法适用于具有大参数扰动和外部干扰的机器人系统的鲁棒跟踪设计。还给出了一个由直流电动机驱动的两连杆机械手的仿真示例,以证明所提出的设计方法的跟踪性能的有效性。

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