The robust control law for gas tungsten arc welding dynamic process, which is a typical sampled-data system and full of uncertainties, is presented. By using the Lyapunov, second method, the robust control and robust ...The robust control law for gas tungsten arc welding dynamic process, which is a typical sampled-data system and full of uncertainties, is presented. By using the Lyapunov, second method, the robust control and robust optimal control for a class of sampled-data systems whose underlying continuous-time systems are subjected to structured uncertainties are discussed in time-domain. As a result, some sufficient conditions of robust stability and the corresponding robust control laws are derived. All these results are designed by solving a class of linear matrix inequalities （LMIs） and a class of dynamic optimization problem with LMIs constraints respectively. An example adapted under some experimental conditions in the dynamic process of gas tungsten arc welding system in which the controlled variable is the backside width of weld pool and controlling variable pulse duty ratio, is worked out to illustrate the proposed results, it is shown that the sampling period is the crucial design oarameter.展开更多
针对标准快速扩展随机树(Rapidly Exploring Random Tree,RRT)算法在复杂环境下存在盲目扩展、陷入局部搜索易导致规划失败、采样成功率低、路径冗长等问题,提出一种自适应目标导向策略结合区域采样备选策略以及贪婪剪枝策略的改进RRT...针对标准快速扩展随机树(Rapidly Exploring Random Tree,RRT)算法在复杂环境下存在盲目扩展、陷入局部搜索易导致规划失败、采样成功率低、路径冗长等问题,提出一种自适应目标导向策略结合区域采样备选策略以及贪婪剪枝策略的改进RRT算法。在机械臂运动学基础上,用包络简化机械臂模型来提高碰撞检测的效率;自适应目标导向策略解决了复杂环境中RRT算法盲目搜索、搜索成功率低、不易收敛的问题;区域采样备选策略解决了RRT算法易陷入局部搜索、采样成功率低以及采样时间长的问题;贪婪剪枝策略剔除了冗余节点,缩短了路径,提升了路径质量,增强了算法的鲁棒性。在Matlab软件和机器人操作系统(Robot Operating System,ROS)中对不同场景进行了避障仿真规划。结果表明,改进RRT算法平均搜索成功率提高了82.4%,平均采样成功率提高了67.5%,平均路径规划成功率提高了70%,平均时间效率提高了81.9%,平均路径长度缩短了63.05%。最后,对实体机械臂进行轨迹规划,进一步验证了算法的实用性与有效性。展开更多
基金This project is supported by Doctor's Research Fund of Science Education Ministry of China(No.20060214004)Scientific Research Fund Education Ministry of China(No.206041)Scientific Research Fund of Harbin Sci-ence Bureau China(No.20051AAICG037).
文摘The robust control law for gas tungsten arc welding dynamic process, which is a typical sampled-data system and full of uncertainties, is presented. By using the Lyapunov, second method, the robust control and robust optimal control for a class of sampled-data systems whose underlying continuous-time systems are subjected to structured uncertainties are discussed in time-domain. As a result, some sufficient conditions of robust stability and the corresponding robust control laws are derived. All these results are designed by solving a class of linear matrix inequalities （LMIs） and a class of dynamic optimization problem with LMIs constraints respectively. An example adapted under some experimental conditions in the dynamic process of gas tungsten arc welding system in which the controlled variable is the backside width of weld pool and controlling variable pulse duty ratio, is worked out to illustrate the proposed results, it is shown that the sampling period is the crucial design oarameter.
