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Nonlinear optimization-based motion planning and robust control of mechanical systems with nonholonomic constraints.

机译:基于非线性优化的运动规划和具有非完整约束的机械系统的鲁棒控制。

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摘要

This research consists of developing numerical approaches for nonholonomic motion planning using nonlinear optimization and robust control for nonholonomic systems using sliding mode. For motion planning, two nonlinear optimization-based schemes are developed for the motion planning of nonholonomic systems. First, an iterative algorithm is proposed to solve for a feasible path satisfying nonholonomic constraints and necessary optimality conditions. Multi-point shooting is used to convert the motion planning problem into the problem of finding the solution of nonlinear equations. Modified Newton's method with line search is then used to ensure the global convergence of the numerical algorithm. Second, by parametrizing the control input, one can transform an infinite-dimensional optimal control problem to a finite-dimensional one and use Quasi-Newton method to solve for a feasible trajectory which satisfies nonholonomic constraints and state/input constraints. For robust control, a sliding mode control scheme is used to improve the performance of nonholonomic systems in terms of robustness and tracking errors. Based on Lyapunov theory, a robust control law is derived to stabilize the nonholonomic systems in reduced configuration space. The proposed scheme for motion planing and robust control is applied to an one-leg hopping robot, a two-wheeled mobile robot, and a free-floating robot. The results of numerical simulation clearly demonstrate the effectiveness of the proposed methods. A three-link planar floating robot was designed and built to verify the proposed motion planning and control scheme. From the experimental results, the proposed optimal motion planning scheme controls the robot from initial state to final state along the planned path within {dollar}pm{dollar}0.1 rad final position error and the slide mode control can increase the robustness to parametric uncertainties and reduce trajectory tracking errors.
机译:这项研究包括开发使用非线性优化的非完整运动计划的数值方法以及使用滑模的非完整系统的鲁棒控制。对于运动规划,针对非完整系统的运动规划,开发了两种基于非线性优化的方案。首先,提出了一种迭代算法来求解满足非完整约束和必要最优性条件的可行路径。多点射击用于将运动计划问题转化为寻找非线性方程解的问题。然后使用带有线搜索的改进牛顿法来确保数值算法的全局收敛性。其次,通过对控制输入进行参数化,可以将无限维的最优控制问题转换为有限维的问题,并使用拟牛顿法来求解满足非完整约束和状态/输入约束的可行轨迹。对于鲁棒控制,滑模控制方案用于在鲁棒性和跟踪误差方面改善非完整系统的性能。基于李雅普诺夫理论,推导了鲁棒的控制律,以使非完整系统稳定在减小的配置空间中。所提出的运动计划和鲁棒控制方案被应用于单腿跳跃机器人,两轮移动机器人和自由漂浮机器人。数值模拟结果清楚地证明了所提出方法的有效性。设计并制造了三连杆平面漂浮机器人,以验证所提出的运动计划和控制方案。根据实验结果,提出的最佳运动计划方案将机器人沿初始路径从初始状态控制到最终状态,并使其在最终位置误差范围内为{rad} pm {dollar} pm rad {rad}} rad,并且滑模控制可以提高对参数不确定性的鲁棒性。减少轨迹跟踪错误。

著录项

  • 作者

    Yih, Chih-Chen.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 1997
  • 页码 118 p.
  • 总页数 118
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;
  • 关键词

  • 入库时间 2022-08-17 11:49:08

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