This paper concentrates on developing a missile terminal guidance law against a highly maneuvering target whose maneuvering acceleration is very close to that of the missile or even exceeds the missile normal accelera...This paper concentrates on developing a missile terminal guidance law against a highly maneuvering target whose maneuvering acceleration is very close to that of the missile or even exceeds the missile normal acceleration in a finite period of time.A new saturated super-twisting algorithm is proposed and applied to the design of missile guidance law.The proposed algorithm has the advantages of simple structure,easy parameter tuning rules and a full utilization of the limit control input.The designed saturated super-twisting sliding mode guidance law is then employed in a missile guidance system.Simulation and its superior performance against strong maneuvering targets is demonstrated.展开更多
The purpose of this study is to design a fractional-order super-twisting sliding-mode controller for a class of nonlinear fractionalorder systems.The proposed method has the following advantages:(1)Lyapunov stability ...The purpose of this study is to design a fractional-order super-twisting sliding-mode controller for a class of nonlinear fractionalorder systems.The proposed method has the following advantages:(1)Lyapunov stability of the overall closed-loop system,(2)output tracking error’s convergence to zero,(3)robustness against external uncertainties and disturbances,and(4)reduction of the chattering phenomenon.To investigate the performance of the method,the proposed controller is applied to an autonomous underwater robot and Lorenz chaotic system.Finally,a simulation is performed to verify the potential of the proposed method.展开更多
This paper presents an adaptive gain,finite-and fixedtime convergence super-twisting-like algorithm based on a revised barrier function,which is robust to perturbations with unknown bounds.It is shown that this algori...This paper presents an adaptive gain,finite-and fixedtime convergence super-twisting-like algorithm based on a revised barrier function,which is robust to perturbations with unknown bounds.It is shown that this algorithm can ensure a finite-and fixed-time convergence of the sliding variable to the equilibrium,no matter what the initial conditions of the system states are,and maintain it there in a predefined vicinity of the origin without violation.Also,the proposed method avoids the problem of overestimation of the control gain that exists in the current fixed-time adaptive control.Moreover,it shows that the revised barrier function can effectively reduce the computation load by obviating the need of increasing the magnitude of sampling step compared with the conventional barrier function.This feature will be beneficial when the algorithm is implemented in practice.After that,the estimation of the fixed convergence time of the proposed method is derived and the impractical requirement of the preceding fixed-time adaptive control that the adaptive gains must be large enough to engender the sliding mode at time t=0 is discarded.Finally,the outperformance of the proposed method over the existing counterpart method is demonstrated with a numerical simulation.展开更多
在心电图诊断中,经常用到ST段的偏移和形态变化分析,由于ST段难以精确定位,使得ST段形态分析难以直接进行。本文考虑到ST段起点J难以确定,但S点与ST段融合后有较好的区分度,所以将S点到T波起点这段作为区分ST形态的数据段。首先利用小...在心电图诊断中,经常用到ST段的偏移和形态变化分析,由于ST段难以精确定位,使得ST段形态分析难以直接进行。本文考虑到ST段起点J难以确定,但S点与ST段融合后有较好的区分度,所以将S点到T波起点这段作为区分ST形态的数据段。首先利用小波变换准确地确定S点和ST段终点(T波起点),提取出数据段平滑后,经改进动态时间规整(dynamic time warping,DTW)算法即可得到ST段的形态。经MIT/BIHST-T数据库的验证,该方法能较好地识别出心电图ST段的5种常见压低形态,即上斜型、下陷型、水平型、下垂型、弓背型。展开更多
时空聚类算法是地理时空大数据挖掘的基础研究命题。针对传统CFSFDP聚类算法无法应用于时空数据挖掘的问题,本文提出一种时空约束的ST-CFSFDP(spatial-temporal clustering by fast search and find of density peaks)算法。在CFSFDP算...时空聚类算法是地理时空大数据挖掘的基础研究命题。针对传统CFSFDP聚类算法无法应用于时空数据挖掘的问题,本文提出一种时空约束的ST-CFSFDP(spatial-temporal clustering by fast search and find of density peaks)算法。在CFSFDP算法基础上加入时间约束,修改了样本属性值的计算策略,不仅解决了原算法单簇集多密度峰值问题,且可以区分并识别相同位置不同时间的簇集。本文利用模拟时空数据与真实的室内定位轨迹数据进行对比试验。结果表明,该算法在时间阈值90 s、距离阈值5 m的识别正确率高达82.4%,较经典ST-DBCSAN、ST-OPTICS及ST-AGNES聚类算法准确率分别提高了5.2%、4.2%和7.6%。展开更多
In this paper, first-order and second-order sliding mode controllers for underactuated manipulators are proposed. Sliding mode control(SMC) is considered as an effective tool in different studies for control systems. ...In this paper, first-order and second-order sliding mode controllers for underactuated manipulators are proposed. Sliding mode control(SMC) is considered as an effective tool in different studies for control systems. However, the associated chattering phenomenon degrades the system performance. To overcome this phenomenon and track a desired trajectory, a twisting, a supertwisting and a modified super-twisting algorithms are presented respectively. The stability analysis is performed using a Lyapunov function for the proposed controllers. Further, the four different controllers are compared with each other. As an illustration, an example of an inverted pendulum is considered. Simulation results are given to demonstrate the effectiveness of the proposed approaches.展开更多
基金National Natural Science Foundation of China(No.61773142)。
文摘This paper concentrates on developing a missile terminal guidance law against a highly maneuvering target whose maneuvering acceleration is very close to that of the missile or even exceeds the missile normal acceleration in a finite period of time.A new saturated super-twisting algorithm is proposed and applied to the design of missile guidance law.The proposed algorithm has the advantages of simple structure,easy parameter tuning rules and a full utilization of the limit control input.The designed saturated super-twisting sliding mode guidance law is then employed in a missile guidance system.Simulation and its superior performance against strong maneuvering targets is demonstrated.
文摘The purpose of this study is to design a fractional-order super-twisting sliding-mode controller for a class of nonlinear fractionalorder systems.The proposed method has the following advantages:(1)Lyapunov stability of the overall closed-loop system,(2)output tracking error’s convergence to zero,(3)robustness against external uncertainties and disturbances,and(4)reduction of the chattering phenomenon.To investigate the performance of the method,the proposed controller is applied to an autonomous underwater robot and Lorenz chaotic system.Finally,a simulation is performed to verify the potential of the proposed method.
文摘This paper presents an adaptive gain,finite-and fixedtime convergence super-twisting-like algorithm based on a revised barrier function,which is robust to perturbations with unknown bounds.It is shown that this algorithm can ensure a finite-and fixed-time convergence of the sliding variable to the equilibrium,no matter what the initial conditions of the system states are,and maintain it there in a predefined vicinity of the origin without violation.Also,the proposed method avoids the problem of overestimation of the control gain that exists in the current fixed-time adaptive control.Moreover,it shows that the revised barrier function can effectively reduce the computation load by obviating the need of increasing the magnitude of sampling step compared with the conventional barrier function.This feature will be beneficial when the algorithm is implemented in practice.After that,the estimation of the fixed convergence time of the proposed method is derived and the impractical requirement of the preceding fixed-time adaptive control that the adaptive gains must be large enough to engender the sliding mode at time t=0 is discarded.Finally,the outperformance of the proposed method over the existing counterpart method is demonstrated with a numerical simulation.
文摘在心电图诊断中,经常用到ST段的偏移和形态变化分析,由于ST段难以精确定位,使得ST段形态分析难以直接进行。本文考虑到ST段起点J难以确定,但S点与ST段融合后有较好的区分度,所以将S点到T波起点这段作为区分ST形态的数据段。首先利用小波变换准确地确定S点和ST段终点(T波起点),提取出数据段平滑后,经改进动态时间规整(dynamic time warping,DTW)算法即可得到ST段的形态。经MIT/BIHST-T数据库的验证,该方法能较好地识别出心电图ST段的5种常见压低形态,即上斜型、下陷型、水平型、下垂型、弓背型。
文摘时空聚类算法是地理时空大数据挖掘的基础研究命题。针对传统CFSFDP聚类算法无法应用于时空数据挖掘的问题,本文提出一种时空约束的ST-CFSFDP(spatial-temporal clustering by fast search and find of density peaks)算法。在CFSFDP算法基础上加入时间约束,修改了样本属性值的计算策略,不仅解决了原算法单簇集多密度峰值问题,且可以区分并识别相同位置不同时间的簇集。本文利用模拟时空数据与真实的室内定位轨迹数据进行对比试验。结果表明,该算法在时间阈值90 s、距离阈值5 m的识别正确率高达82.4%,较经典ST-DBCSAN、ST-OPTICS及ST-AGNES聚类算法准确率分别提高了5.2%、4.2%和7.6%。
文摘In this paper, first-order and second-order sliding mode controllers for underactuated manipulators are proposed. Sliding mode control(SMC) is considered as an effective tool in different studies for control systems. However, the associated chattering phenomenon degrades the system performance. To overcome this phenomenon and track a desired trajectory, a twisting, a supertwisting and a modified super-twisting algorithms are presented respectively. The stability analysis is performed using a Lyapunov function for the proposed controllers. Further, the four different controllers are compared with each other. As an illustration, an example of an inverted pendulum is considered. Simulation results are given to demonstrate the effectiveness of the proposed approaches.
