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基于动态事件触发策略的模块化机器人操纵器最优控制:多人非零和博弈视角

Dynamic Event-Triggered Strategy-Based Optimal Control of Modular Robot Manipulator: A Multiplayer Nonzero-Sum Game Perspective.

作者信息

An Tianjiao, Dong Bo, Yan Haoyu, Liu Lei, Ma Bing

出版信息

IEEE Trans Cybern. 2024 Dec;54(12):7514-7526. doi: 10.1109/TCYB.2024.3468875. Epub 2024 Nov 27.

Abstract

Due to the limited computing and processing ability of modular robot manipulator (MRM) components, such as sensors and controllers, event-triggered mechanisms are considered a crucial communication paradigm shift in resource constrained applications. Dynamic event-triggered mechanism is developing into a new technology by reason of its higher resource utilization efficiency and more flexible system design requirements than traditional event-triggered. Therefore, an optimal control scheme of multiplayer nonzero-sum game based on dynamic event-triggered is developed for MRM systems with uncertain disturbances. First, dynamic model of the MRM is established according to joint torque feedback technique and model uncertainty is estimated by data-driven-based neural network identifier. In the framework of differential game, the tracking control problem of MRM system is transformed into the optimal control problem for multiplayer nonzero-sum game with the control input of each joint module as the player. Then, the static event-triggered control problem of MRM system is studied based on adaptive dynamic programming algorithm. On this basis, the internal dynamic variable describing the previous state of the system is introduced, and the characteristics of dynamic trigger rule and its relationship with static rule are revealed theoretically. By designing an exponential attenuation signal, the minimum sampling interval of the system is always positive, so that Zeno behavior is excluded. Lyapunov theory proves that the system is asymptotically stable and the experimental results verify the validity of the proposed method.

摘要

由于模块化机器人操纵器(MRM)组件(如传感器和控制器)的计算和处理能力有限,事件触发机制被认为是资源受限应用中至关重要的通信范式转变。动态事件触发机制因其比传统事件触发具有更高的资源利用效率和更灵活的系统设计要求,正在发展成为一项新技术。因此,针对具有不确定干扰的MRM系统,开发了一种基于动态事件触发的多玩家非零和博弈最优控制方案。首先,根据关节扭矩反馈技术建立MRM的动态模型,并通过基于数据驱动的神经网络标识符估计模型不确定性。在微分博弈框架下,将MRM系统的跟踪控制问题转化为以各关节模块控制输入为玩家的多玩家非零和博弈的最优控制问题。然后,基于自适应动态规划算法研究MRM系统的静态事件触发控制问题。在此基础上,引入描述系统先前状态的内部动态变量,从理论上揭示了动态触发规则的特性及其与静态规则的关系。通过设计指数衰减信号,使系统的最小采样间隔始终为正,从而排除芝诺行为。李雅普诺夫理论证明系统是渐近稳定的,实验结果验证了所提方法的有效性。

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