Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics,random disturbances and load variations.To account for uncertain disturbances in the operation of manipulators,we ...Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics,random disturbances and load variations.To account for uncertain disturbances in the operation of manipulators,we propose an adaptive manipulator control method based on a multi-joint fuzzy system,in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable.The control algorithm of the system is a MIMO(multi-input-multi-output)fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error.It can ensure the stability of complex manipulator control systems and reduce the number of fuzzy rules required.Comparison of experimental and simulation data shows that the controller designed using this algorithm has highly-precise trajectory-tracking control and can control robotic systems with complex characteristics of non-linearity,coupling and uncertainty.Therefore,the proposed algorithm has good practical application prospects and promotes the development of complex control systems.展开更多
随着分布式电源渗透率不断上升,多扰动耦合效应持续增强,新型配电网稳定性分析以及优化运行面临着巨大的挑战。对此,该文依据新型配电网节点电压方程建立多扰动耦合等值电路,并基于多扰动耦合等值电路的潮流可解性提出耦合电压稳定约束(...随着分布式电源渗透率不断上升,多扰动耦合效应持续增强,新型配电网稳定性分析以及优化运行面临着巨大的挑战。对此,该文依据新型配电网节点电压方程建立多扰动耦合等值电路,并基于多扰动耦合等值电路的潮流可解性提出耦合电压稳定约束(coupling voltage stability constraint,CVSC),以实现多扰动耦合影响下的电压稳定性量化约束;同时,通过Bonferroni不等式将CVSC和联合机会约束结合,提出耦合电压稳定联合机会约束(coupling voltage stability joint chance constraint,CVS-JCC);进一步,对CVS-JCC进行确定性转化,得到CVS-JCC的解析表达式,并提出考虑CVS-JCC的配电网优化运行方法,以提高配电网安全、稳定、经济运行能力;最后,通过浙江台州某配电网模型进行仿真实验,证明CVS-JCC的有效性以及不同场景下优化运行方法的先进性。展开更多
在多无人机协同突防过程中,针对无人机需完成目标分配与探干侦动作选择的任务决策存在模型构建难,对模型求解方法复杂度高的问题,提出一种蒙特卡罗树搜索(Monte Carlo tree search,MCTS)的改进方法实现多无人机多任务联合决策。首先,考...在多无人机协同突防过程中,针对无人机需完成目标分配与探干侦动作选择的任务决策存在模型构建难,对模型求解方法复杂度高的问题,提出一种蒙特卡罗树搜索(Monte Carlo tree search,MCTS)的改进方法实现多无人机多任务联合决策。首先,考虑无人机与雷达对抗中的角度、距离等态势要素,以及当前无人机动作执行成功概率和雷达状态有效概率,构建多无人机目标分配与探干侦动作统一决策数学模型。其次,提出搜索次数自适应调整的改进MCTS算法对模型求解,实现大规模解空间在线快速寻优。仿真结果表明,改进算法使多雷达系统对无人机的威胁程度下降约16.8%,相比多臂赌博机算法效果提升约5.08%,决策时间约0.23 s,比传统MCTS缩短约45.7%,有助于提升无人机战场生存率。展开更多
基金the project of science and technology of Henan province under Grant No.14210221036.
文摘Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics,random disturbances and load variations.To account for uncertain disturbances in the operation of manipulators,we propose an adaptive manipulator control method based on a multi-joint fuzzy system,in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable.The control algorithm of the system is a MIMO(multi-input-multi-output)fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error.It can ensure the stability of complex manipulator control systems and reduce the number of fuzzy rules required.Comparison of experimental and simulation data shows that the controller designed using this algorithm has highly-precise trajectory-tracking control and can control robotic systems with complex characteristics of non-linearity,coupling and uncertainty.Therefore,the proposed algorithm has good practical application prospects and promotes the development of complex control systems.
文摘随着分布式电源渗透率不断上升,多扰动耦合效应持续增强,新型配电网稳定性分析以及优化运行面临着巨大的挑战。对此,该文依据新型配电网节点电压方程建立多扰动耦合等值电路,并基于多扰动耦合等值电路的潮流可解性提出耦合电压稳定约束(coupling voltage stability constraint,CVSC),以实现多扰动耦合影响下的电压稳定性量化约束;同时,通过Bonferroni不等式将CVSC和联合机会约束结合,提出耦合电压稳定联合机会约束(coupling voltage stability joint chance constraint,CVS-JCC);进一步,对CVS-JCC进行确定性转化,得到CVS-JCC的解析表达式,并提出考虑CVS-JCC的配电网优化运行方法,以提高配电网安全、稳定、经济运行能力;最后,通过浙江台州某配电网模型进行仿真实验,证明CVS-JCC的有效性以及不同场景下优化运行方法的先进性。
文摘在多无人机协同突防过程中,针对无人机需完成目标分配与探干侦动作选择的任务决策存在模型构建难,对模型求解方法复杂度高的问题,提出一种蒙特卡罗树搜索(Monte Carlo tree search,MCTS)的改进方法实现多无人机多任务联合决策。首先,考虑无人机与雷达对抗中的角度、距离等态势要素,以及当前无人机动作执行成功概率和雷达状态有效概率,构建多无人机目标分配与探干侦动作统一决策数学模型。其次,提出搜索次数自适应调整的改进MCTS算法对模型求解,实现大规模解空间在线快速寻优。仿真结果表明,改进算法使多雷达系统对无人机的威胁程度下降约16.8%,相比多臂赌博机算法效果提升约5.08%,决策时间约0.23 s,比传统MCTS缩短约45.7%,有助于提升无人机战场生存率。
