移动机器人同步定位与建图问题(Simultaneous localization and mapping,SLAM)是机器人能否在未知环境中实现完全自主的关键问题之一.其中,机器人定位估计对于保持地图的一致性非常重要.本文分析了SLAM问题中机器人定位误差的收敛特性....移动机器人同步定位与建图问题(Simultaneous localization and mapping,SLAM)是机器人能否在未知环境中实现完全自主的关键问题之一.其中,机器人定位估计对于保持地图的一致性非常重要.本文分析了SLAM问题中机器人定位误差的收敛特性.分析表明随着机器人的运动,机器人定位误差总体上逐渐增大;在完全未知环境中无法预测机器人定位误差的上限.根据理论分析,本文提出了一种控制机器人定位误差在单位距离上增长速度的算法.该算法通过搜索获得满足定位误差限制的最佳的机器人运动速度,从而控制机器人定位误差的增长.展开更多
Directing to the strong position coupling problem of electro-hydraulic load simulator (EHLS), this article presents an adaptive nonlinear optimal compensation control strategy based on two estimated nonlinear paramete...Directing to the strong position coupling problem of electro-hydraulic load simulator (EHLS), this article presents an adaptive nonlinear optimal compensation control strategy based on two estimated nonlinear parameters, viz. the flow gain coefficient of servo valve and total factors of flow-pressure coefficient. Taking trace error of torque control system to zero as control object, this article designs the adaptive nonlinear optimal compensation control strategy, which regards torque control output of closed-loop controller converging to zero as the control target, to optimize torque tracking performance. Electro-hydraulic load simulator is a typical case of the torque system which is strongly coupled with a hydraulic positioning system. This article firstly builds and analyzes the mathematical models of hydraulic torque and positioning system, then designs an adaptive nonlinear optimal compensation controller, proves the validity of parameters estimation, and shows the comparison data among three control structures with various typical operating conditions, including proportion-integral-derivative (PID) controller only, the velocity synchronizing controller plus P1D controller and the proposed adaptive nonlinear optimal compensation controller plus PID controller. Experimental results show that systems' nonlinear parameters are estimated exactly using the proposed method, and the trace accuracy of the torque system is greatly enhanced by adaptive nonlinear optimal compensation control, and the torque servo system capability against sudden disturbance can be greatly improved.展开更多
文摘移动机器人同步定位与建图问题(Simultaneous localization and mapping,SLAM)是机器人能否在未知环境中实现完全自主的关键问题之一.其中,机器人定位估计对于保持地图的一致性非常重要.本文分析了SLAM问题中机器人定位误差的收敛特性.分析表明随着机器人的运动,机器人定位误差总体上逐渐增大;在完全未知环境中无法预测机器人定位误差的上限.根据理论分析,本文提出了一种控制机器人定位误差在单位距离上增长速度的算法.该算法通过搜索获得满足定位误差限制的最佳的机器人运动速度,从而控制机器人定位误差的增长.
基金National Natural Science Foundation of China (50825502)
文摘Directing to the strong position coupling problem of electro-hydraulic load simulator (EHLS), this article presents an adaptive nonlinear optimal compensation control strategy based on two estimated nonlinear parameters, viz. the flow gain coefficient of servo valve and total factors of flow-pressure coefficient. Taking trace error of torque control system to zero as control object, this article designs the adaptive nonlinear optimal compensation control strategy, which regards torque control output of closed-loop controller converging to zero as the control target, to optimize torque tracking performance. Electro-hydraulic load simulator is a typical case of the torque system which is strongly coupled with a hydraulic positioning system. This article firstly builds and analyzes the mathematical models of hydraulic torque and positioning system, then designs an adaptive nonlinear optimal compensation controller, proves the validity of parameters estimation, and shows the comparison data among three control structures with various typical operating conditions, including proportion-integral-derivative (PID) controller only, the velocity synchronizing controller plus P1D controller and the proposed adaptive nonlinear optimal compensation controller plus PID controller. Experimental results show that systems' nonlinear parameters are estimated exactly using the proposed method, and the trace accuracy of the torque system is greatly enhanced by adaptive nonlinear optimal compensation control, and the torque servo system capability against sudden disturbance can be greatly improved.
