An integral sliding mode guidance law(ISMGL)combined with the advantages of the integral sliding mode control(SMC)method is designed to address maneuvering target interception problems with impact angle constraints.Th...An integral sliding mode guidance law(ISMGL)combined with the advantages of the integral sliding mode control(SMC)method is designed to address maneuvering target interception problems with impact angle constraints.The relative motion equation of the missile and the target considering the impact angle constraint is established in the longitudinal plane,and an integral sliding mode surface is constructed.The proposed guidance law resolves the existence of a steady-state error problem in the traditional SMC.Such a guidance law ensures that the missile hits the target with an ideal impact angle in finite time and the missile is kept highly robust throughout the interception process.By adopting the dynamic surface control method,the ISMGL is designed considering the impact angle constraints and the autopilot dynamic characteristics.According to the Lyapunov stability theorem,all states of the closed-loop system are finally proven to be uniformly bounded.Simulation results are compared with the general sliding mode guidance law and the trajectory shaping guidance law,and the findings verify the effectiveness and superiority of the ISMGL.展开更多
针对非完整移动机器人编队控制问题,基于领航者-跟随者l-ψ控制结构,提出了一种运动学控制器与自适应神经滑模控制器相结合的新型控制策略。采用径向基神经网络(radial basis function neural network,RBFNN)对跟随者及领航者动力学非...针对非完整移动机器人编队控制问题,基于领航者-跟随者l-ψ控制结构,提出了一种运动学控制器与自适应神经滑模控制器相结合的新型控制策略。采用径向基神经网络(radial basis function neural network,RBFNN)对跟随者及领航者动力学非线性不确定部分进行在线估计,并通过自适应鲁棒控制器对神经网络建模误差进行补偿。实验结果表明所提方法不但解决了移动机器人编队控制的参数与非参数不确定性问题,还确保了机器人编队在期望队形下对指定轨迹的跟踪;基于Lyapunov方法的设计过程,保证了控制系统的稳定。展开更多
针对独立风柴混合电力系统中风能和无功负荷变化所引起的电压波动问题,提出了利用静止无功补偿器(static var compensator,SVC)稳定电压的控制策略。实际SVC存在模型参数不确定及状态变量不完全可测的问题,故利用滑模控制算法,设计基于...针对独立风柴混合电力系统中风能和无功负荷变化所引起的电压波动问题,提出了利用静止无功补偿器(static var compensator,SVC)稳定电压的控制策略。实际SVC存在模型参数不确定及状态变量不完全可测的问题,故利用滑模控制算法,设计基于鲁棒观测器的SVC附加滑模电压控制器。为此,首先建立孤岛情况下包含SVC的风柴混合电力系统的数学模型;然后选择适当的比例切换面和趋近律到达条件,并基于观测器估计值来构造SVC鲁棒电压控制器;最后基于Matlab仿真平台搭建算例模型,对所设计SVC滑模电压控制器的鲁棒性进行验证。仿真结果表明,所设计的SVC滑模电压控制器与传统的SVC控制策略相比,可有效抑制电压波动。展开更多
基金supported by the Joint Equipment Fund of the Ministry of Education(6141A02022340)
文摘An integral sliding mode guidance law(ISMGL)combined with the advantages of the integral sliding mode control(SMC)method is designed to address maneuvering target interception problems with impact angle constraints.The relative motion equation of the missile and the target considering the impact angle constraint is established in the longitudinal plane,and an integral sliding mode surface is constructed.The proposed guidance law resolves the existence of a steady-state error problem in the traditional SMC.Such a guidance law ensures that the missile hits the target with an ideal impact angle in finite time and the missile is kept highly robust throughout the interception process.By adopting the dynamic surface control method,the ISMGL is designed considering the impact angle constraints and the autopilot dynamic characteristics.According to the Lyapunov stability theorem,all states of the closed-loop system are finally proven to be uniformly bounded.Simulation results are compared with the general sliding mode guidance law and the trajectory shaping guidance law,and the findings verify the effectiveness and superiority of the ISMGL.
文摘针对非完整移动机器人编队控制问题,基于领航者-跟随者l-ψ控制结构,提出了一种运动学控制器与自适应神经滑模控制器相结合的新型控制策略。采用径向基神经网络(radial basis function neural network,RBFNN)对跟随者及领航者动力学非线性不确定部分进行在线估计,并通过自适应鲁棒控制器对神经网络建模误差进行补偿。实验结果表明所提方法不但解决了移动机器人编队控制的参数与非参数不确定性问题,还确保了机器人编队在期望队形下对指定轨迹的跟踪;基于Lyapunov方法的设计过程,保证了控制系统的稳定。
文摘针对独立风柴混合电力系统中风能和无功负荷变化所引起的电压波动问题,提出了利用静止无功补偿器(static var compensator,SVC)稳定电压的控制策略。实际SVC存在模型参数不确定及状态变量不完全可测的问题,故利用滑模控制算法,设计基于鲁棒观测器的SVC附加滑模电压控制器。为此,首先建立孤岛情况下包含SVC的风柴混合电力系统的数学模型;然后选择适当的比例切换面和趋近律到达条件,并基于观测器估计值来构造SVC鲁棒电压控制器;最后基于Matlab仿真平台搭建算例模型,对所设计SVC滑模电压控制器的鲁棒性进行验证。仿真结果表明,所设计的SVC滑模电压控制器与传统的SVC控制策略相比,可有效抑制电压波动。
