Wheeled mobile robots(WMRs) encounter unavoidable slippage especially on the low adhesion terrain such that the robots stability and accuracy are reduced greatly.To overcome this drawback,this article presents a neura...Wheeled mobile robots(WMRs) encounter unavoidable slippage especially on the low adhesion terrain such that the robots stability and accuracy are reduced greatly.To overcome this drawback,this article presents a neural network(NN) based terminal sliding mode control(TSMC) for WMRs where an augmented ground friction model is reported by which the uncertain friction can be estimated and compensated according to the required performance.In contrast to the existing friction models,the developed augmented ground friction model corresponds to actual fact because not only the effects associated with the mobile platform velocity but also the slippage related to the wheel slip rate are concerned simultaneously.Besides,the presented control approach can combine the merits of both TSMC and radial basis function(RBF) neural networks techniques,thereby providing numerous excellent performances for the closed-loop system,such as finite time convergence and faster friction estimation property.Simulation results validate the proposed friction model and robustness of controller;these research results will improve the autonomy and intelligence of WMRs,particularly when the mobile platform suffers from the sophisticated unstructured environment.展开更多
Good understanding of relationship between parameters of vehicle, terrain and interaction at the interface is required to develop effective navigation and motion control algorithms for autonomous wheeled mobile robots...Good understanding of relationship between parameters of vehicle, terrain and interaction at the interface is required to develop effective navigation and motion control algorithms for autonomous wheeled mobile robots （AWMR） in rough terrain. A model and analysis of relationship among wheel slippage （S）, rotation angle （0）, sinkage （z） and wheel radius （r） are presented. It is found that wheel rotation angle, sinkage and radius have some influence on wheel slippage. A multi-objective optimization problem with slippage as utility function was formulated and solved in MATLAB. The results reveal the optimal values of wheel-terrain parameters required to achieve optimum slippage on dry sandy terrain. A method of slippage estimation for a five-wheeled mobile robot was presented through comparing the odometric measurements of the powered wheels with those of the fifth non-powered wheel. The experimental result shows that this method is feasible and can be used for online slippage estimation in a sandy terrain.展开更多
对轮式移动机器人(Wheeled Mobile Robot,WMR)发生执行器故障和输入饱和时容错控制问题进行研究,设计了一种自适应容错控制器(Adaptive FaultTolerant Controller,AFTC),可在故障信息未知的情况下解决上述问题。首先,设计了线性扩张观测...对轮式移动机器人(Wheeled Mobile Robot,WMR)发生执行器故障和输入饱和时容错控制问题进行研究,设计了一种自适应容错控制器(Adaptive FaultTolerant Controller,AFTC),可在故障信息未知的情况下解决上述问题。首先,设计了线性扩张观测器(Linear Extended State Observer,LESO)对偏置故障和干扰进行在线估计;然后,基于积分滑模设计了一种自适应控制律来补偿部分失效控制,并结合指数和变速趋近律来削弱滑模抖振;最后,设计了一种饱和辅助系统,利用其辅助变量对自适应控制律在线调整,使控制量在限幅范围内。利用李雅普诺夫稳定性理论,证明了在执行器故障和输入饱和的情况下,WMR的前进速度和方位角可以渐近地跟踪参考轨迹,并通过对比数值仿真验证了所设计的容错控制策略的有效性。展开更多
针对轮式移动机器人(wheeled mobile robot,WMR)轨迹跟踪中存在的速度跳变和未知系统扰动,提出一种新型轨迹跟踪控制策略。该策略基于反演技术,分别设计WMR系统的运动学控制器和动力学控制器。在运动学控制器中,采用分流技术克服了轨迹...针对轮式移动机器人(wheeled mobile robot,WMR)轨迹跟踪中存在的速度跳变和未知系统扰动,提出一种新型轨迹跟踪控制策略。该策略基于反演技术,分别设计WMR系统的运动学控制器和动力学控制器。在运动学控制器中,采用分流技术克服了轨迹跟踪初期的速度跳变问题;在动力学控制器中,将模糊干扰观测器与自适应滑模控制结合,有效解决了未知系统扰动对控制性能的影响,并且消除了传统滑模控制的抖振现象。通过Lyapunov稳定性理论,证明了该控制策略的稳定性。仿真研究表明:该控制策略具有较小的速度跳变,控制信号抖振较小,并对系统扰动具有强鲁棒性。展开更多
基金supported by the National Natural Science Foundation of China(61573078,61573147)the International S&T Cooperation Program of China(2014DFB70120)the State Key Laboratory of Robotics and System(SKLRS2015ZD06)
文摘Wheeled mobile robots(WMRs) encounter unavoidable slippage especially on the low adhesion terrain such that the robots stability and accuracy are reduced greatly.To overcome this drawback,this article presents a neural network(NN) based terminal sliding mode control(TSMC) for WMRs where an augmented ground friction model is reported by which the uncertain friction can be estimated and compensated according to the required performance.In contrast to the existing friction models,the developed augmented ground friction model corresponds to actual fact because not only the effects associated with the mobile platform velocity but also the slippage related to the wheel slip rate are concerned simultaneously.Besides,the presented control approach can combine the merits of both TSMC and radial basis function(RBF) neural networks techniques,thereby providing numerous excellent performances for the closed-loop system,such as finite time convergence and faster friction estimation property.Simulation results validate the proposed friction model and robustness of controller;these research results will improve the autonomy and intelligence of WMRs,particularly when the mobile platform suffers from the sophisticated unstructured environment.
基金Project(60775060) supported by the National Natural Science Foundation of ChinaProject(F200801) supported by the Natural Science Foundation of Heilongjiang Province,China+1 种基金Project(200802171053,20102304110006) supported by the Specialized Research Fund for the Doctoral Program of Higher Education of ChinaProject(2012RFXXG059) supported by Harbin Science and Technology Innovation Talents Special Fund,China
文摘Good understanding of relationship between parameters of vehicle, terrain and interaction at the interface is required to develop effective navigation and motion control algorithms for autonomous wheeled mobile robots （AWMR） in rough terrain. A model and analysis of relationship among wheel slippage （S）, rotation angle （0）, sinkage （z） and wheel radius （r） are presented. It is found that wheel rotation angle, sinkage and radius have some influence on wheel slippage. A multi-objective optimization problem with slippage as utility function was formulated and solved in MATLAB. The results reveal the optimal values of wheel-terrain parameters required to achieve optimum slippage on dry sandy terrain. A method of slippage estimation for a five-wheeled mobile robot was presented through comparing the odometric measurements of the powered wheels with those of the fifth non-powered wheel. The experimental result shows that this method is feasible and can be used for online slippage estimation in a sandy terrain.
文摘对轮式移动机器人(Wheeled Mobile Robot,WMR)发生执行器故障和输入饱和时容错控制问题进行研究,设计了一种自适应容错控制器(Adaptive FaultTolerant Controller,AFTC),可在故障信息未知的情况下解决上述问题。首先,设计了线性扩张观测器(Linear Extended State Observer,LESO)对偏置故障和干扰进行在线估计;然后,基于积分滑模设计了一种自适应控制律来补偿部分失效控制,并结合指数和变速趋近律来削弱滑模抖振;最后,设计了一种饱和辅助系统,利用其辅助变量对自适应控制律在线调整,使控制量在限幅范围内。利用李雅普诺夫稳定性理论,证明了在执行器故障和输入饱和的情况下,WMR的前进速度和方位角可以渐近地跟踪参考轨迹,并通过对比数值仿真验证了所设计的容错控制策略的有效性。
文摘针对轮式移动机器人(wheeled mobile robot,WMR)轨迹跟踪中存在的速度跳变和未知系统扰动,提出一种新型轨迹跟踪控制策略。该策略基于反演技术,分别设计WMR系统的运动学控制器和动力学控制器。在运动学控制器中,采用分流技术克服了轨迹跟踪初期的速度跳变问题;在动力学控制器中,将模糊干扰观测器与自适应滑模控制结合,有效解决了未知系统扰动对控制性能的影响,并且消除了传统滑模控制的抖振现象。通过Lyapunov稳定性理论,证明了该控制策略的稳定性。仿真研究表明:该控制策略具有较小的速度跳变,控制信号抖振较小,并对系统扰动具有强鲁棒性。
