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Model-based PI-fuzzy control of four-wheeled omni-directional mobile robots

机译:四轮全向移动机器人的基于模型的PI模糊控制

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The purpose of this study is to suggest and examine a PI-fuzzy path planner and associated low-level control system for a linear discrete dynamic model of omni-directional mobile robots to obtain optimal inputs for drivers. Velocity and acceleration filtering is also implemented in the path planner to satisfy planning prerequisites and prevent slippage. Regulated drivers rotational velocities and torques greatly affect the ability of these robots to perform trajectory planner tasks. These regulated values are examined in this research by setting up an optimal controller. Introducing optimal controllers such as linear quadratic tracking for multi-input-multi-output control systems in acceleration and deceleration is one of the essential subjects for motion control of omni-directional mobile robots. The main topics presented and discussed in this article are improvements in the presented discrete-time linear quadratic tracking approach such as the low-level controller and combined PI-fuzzy path planner with appropriate speed monitoring algorithm such as the high-level one in conditions both with and without external disturbance. The low-level tracking controller presented in this article provides an optimal solution to minimize the differences between the reference trajectory and the system output. The efficiency of this approach is also compared with that of previous PID controllers which employ kinematic modeling. Utilizing the new approach in trajectory-planning controller design results in more precise and appropriate outputs for the motion of four-wheeled omni-directional mobile robots, and the modeling and experimental results confirm this issue.
机译:这项研究的目的是为全向移动机器人的线性离散动态模型建议和检验PI模糊路径规划器和相关的低级控制系统,以获取驾驶员的最佳输入。路径规划器中还实现了速度和加速度过滤,以满足规划的先决条件并防止打滑。调节驾驶员的旋转速度和扭矩会极大地影响这些机器人执行轨迹计划任务的能力。在本研究中,通过设置最佳控制器来检查这些调节值。在全向移动机器人中,为加速和减速中的多输入多输出控制系统引入诸如线性二次跟踪之类的最优控制器是全向移动机器人运动控制的基本主题之一。本文提出和讨论的主要主题是对所提出的离散时间线性二次跟踪方法的改进,例如低层控制器和组合的PI-模糊路径规划器与适当的速度监视算法(例如在较高的情况下可以使用高水平的算法)有无外部干扰。本文介绍的低级别跟踪控制器提供了一种最佳解决方案,以最大程度地减小参考轨迹与系统输出之间的差异。还将该方法的效率与以前采用运动学建模的PID控制器的效率进行了比较。在轨迹规划控制器设计中使用新方法可为四轮全向移动机器人的运动提供更精确和合适的输出,并且建模和实验结果证实了这一问题。

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