State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, PR China; Department of Control Science and Engineering, Jilin University, Changchun, PR China; Nanjing Research Institute of Electronics Technology, Nanjing, PR China.
State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, PR China; Department of Control Science and Engineering, Jilin University, Changchun, PR China.
ISA Trans. 2019 Apr;87:116-128. doi: 10.1016/j.isatra.2018.11.019. Epub 2018 Nov 20.
With the development of the similarity calculation method, the orbital motion of space vehicle can be translated into a sequence of waypoints that reflect position and velocity on the ground. In this paper, a motion control system is proposed to make the mobile robot pass through the desired waypoints for reconstructing the orbital motion. First, the parameterized trajectory optimization method is applied to generate a curvature-continuous trajectory from the waypoints, the position and velocity demands are presented as the equality constraints. Virtual positions are introduced to reduce the oscillation, and the total execution time of the whole trajectory is selected as the optimization parameter to reduce the computational burden. Then, an equivalence transformation is provided to translate the error system into an affine form, which is beneficial for the feedback controller design. Based on this, a nonlinear trajectory tracking controller is proposed, which includes a feedforward controller and an error feedback controller, and its exponential stability is proved using Persistency of Excitation Lemma. In addition, a shunting neural dynamics model is employed to avoid sharp velocity jumps. Finally, the performed experiments verify the effectiveness of the proposed method.
随着相似度计算方法的发展,航天器的轨道运动可以转化为一系列反映地面位置和速度的航点。本文提出了一种运动控制系统,使移动机器人通过期望的航点来重构轨道运动。首先,应用参数化轨迹优化方法从航点生成曲率连续的轨迹,位置和速度需求作为等式约束。引入虚拟位置以减少振荡,并选择整个轨迹的总执行时间作为优化参数以减少计算负担。然后,提供等效变换将误差系统转换为仿射形式,这有利于反馈控制器设计。在此基础上,提出了一种非线性轨迹跟踪控制器,它包括前馈控制器和误差反馈控制器,并使用激励持续定理证明了其指数稳定性。此外,采用分流神经动力学模型来避免速度的急剧跳跃。最后,进行的实验验证了所提出方法的有效性。