SUMMARYThe 3 degree-of-freedom Gantry-Tau manipulator with the addition of the spherical wrist mechanism which is called Gantry-Tau-3R is designed as a high-G simulation-based motion platform (SBMP) with the capability of generating the large linear and angular displacement. The combination of both parallel and serial manipulator in newly designed Gantry-Tau-3R mechanism improves the ability of the mechanism to regenerate larger motion signals with higher linear acceleration and angular velocity. The high-frequency signals are reproduced using the parallel part of the mechanism, and sustainable low-frequency accelerations are regenerated via the serial part due to the larger rotational motion capability, which will be used through motion cueing algorithm tilt coordination channel. The proportional integral derivative (PID) and fuzzy incremental controller (FIC) are developed for the proposed mechanism to show the high path tracking performance as a motion platform. FIC reduces the motion tracking error of the newly designed Gantry-Tau-3R and increases the motion fidelity for the users of the proposed SBMP. The proposed method is implemented using Matlab/Simulink software. Finally, the results demonstrate the accurate motion signal generation using linear model predictive motion cues with a fuzzy controller, which is not possible using the common parallel and serial manipulators.

中文翻译：

---

一种使用球形手腕和基于模型预测控制的运动提示算法的基于龙门 Tau 的新机制

概要3自由度Gantry-Tau机械手，增加了球形手腕机构，称为Gantry-Tau-3R，被设计为一种基于高G仿真的运动平台（SBMP），具有生成大线性的能力和角位移。新设计的Gantry-Tau-3R机构中并联和串联机械手的结合提高了该机构再生更大运动信号的能力，具有更高的线性加速度和角速度。高频信号利用机构的并联部分再现，而可持续的低频加速度由于较大的旋转运动能力通过串行部分再生，将通过运动提示算法倾斜协调通道使用。为所提出的机制开发了比例积分微分 (PID) 和模糊增量控制器 (FIC)，以显示作为运动平台的高路径跟踪性能。FIC 降低了新设计的 Gantry-Tau-3R 的运动跟踪误差，并提高了所提议 SBMP 用户的运动保真度。所提出的方法是使用 Matlab/Simulink 软件实现的。最后，结果证明了使用带有模糊控制器的线性模型预测运动线索生成准确的运动信号，这是使用常见的并行和串行机械手无法实现的。FIC 降低了新设计的 Gantry-Tau-3R 的运动跟踪误差，并提高了所提议 SBMP 用户的运动保真度。所提出的方法是使用 Matlab/Simulink 软件实现的。最后，结果表明使用带有模糊控制器的线性模型预测运动线索生成准确的运动信号，这是使用常见的并行和串行机械手无法实现的。FIC 降低了新设计的 Gantry-Tau-3R 的运动跟踪误差，并提高了所提议 SBMP 用户的运动保真度。所提出的方法是使用 Matlab/Simulink 软件实现的。最后，结果表明使用带有模糊控制器的线性模型预测运动线索生成准确的运动信号，这是使用常见的并行和串行机械手无法实现的。