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Adaptive fractional PID control of biped robots with time-delayed feedback

机译:具有时滞反馈的两足机器人的自适应分数PID控制

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This paper presents the application of Fractional Order Time- Delay adaptive neural networks to the trajectory tracking for chaos synchronization between Fractional Order delayed plant, reference and Fractional Order Time-Delay adaptive neural networks. The proposed new control scheme is applied via simulations to control of a 4-DOF Biped Robot [1]. The main methodologies, on which the approach is based, are Fractional Order PID the Fractional Order Lyapunov-Krasovskii functions methodology. The structure of the biped robot is designed with two degrees of freedom per leg, corresponding to the knee and hip joints. Since torso and ankle are not considered, it is obtained a 4-DOF system, and each leg, we try to force this biped robot to track a reference signal given by undamped Duffing equation. The tracking error is globally asymptotically stabilized by two control laws derived based on a Lyapunov-Krasovski functional.
机译:本文提出了分数阶时延自适应神经网络在轨迹跟踪中的应用,分数阶时滞植物,参考和分数阶时延自适应神经网络之间的混沌同步。拟议的新控制方案通过仿真应用于4自由度Biped机器人的控制[1]。该方法所基于的主要方法是分数阶PID,分数阶Lyapunov-Krasovskii函数方法。两足动物机器人的结构设计为每条腿有两个自由度,分别对应于膝盖和髋关节。由于未考虑躯干和脚踝,因此获得了一个4-DOF系统,并且每条腿都试图迫使此Biped机器人跟踪未阻尼Duffing方程给出的参考信号。跟踪误差通过基于Lyapunov-Krasovski泛函的两个控制定律全局渐近稳定。

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