一种船舶漂浮状态下捷联惯导快速自对准方法

为解决无外部参考信息船舶SINS漂浮状态下捷联惯导快速自对准问题,提出了在粗对准阶段采用时变参数罗经法、精对准阶段采用卡尔曼滤波精对准的方案.传统方案中罗经对准方案常常被用于精对准,这里采用大方位失准角条件下时变参数的罗经法进行粗对准,代替目前成熟的凝固法粗对准方案,在大方位失准角条件下同时利用东向通道和北向通道的速度...     

基于MYO和Android的肌电假肢手控制系统设计与实现*

针对目前假肢手控制系统成本高、操作不灵活、实用性差等问题,设计了一种基于MYO和Android的肌电假肢手控制系统。在Android平台上,开发了一款智能终端应用,实现了对MYO臂环采集的表面肌电信号进行数据处理和模式识别,并实时控制假肢手完成五种模式。实验结果表明,系统的在线识别率可达98.2%,并可在300ms左右完成一次识别过程,满足了假肢手控制的精度和实时性要求。该系统设计成本低廉、方便携带且易于扩展,很好地满足了截肢患者对假肢手控制的需求。     

Cooperative impulsive formation control for networked uncertain Euler–Lagrange systems with communication delays

This paper investigates the cooperative formation problem via impulsive control for a class of networked Euler–Lagrange systems. To reduce the energy consumption and communication frequency, the impulsive control method and cooperative formation control approach are combined. With the consideration of system uncertainties and communication delays among agents, neural networks-based adaptive technique is used for the controller design. Firstly, under the constraint that each agent interacts with its neighbors only at some sampling moments, an adaptive neural-networks impulsive formation control algorithm is proposed for the networked uncertain Euler–Lagrange systems without communication delays. Using Lyapunov stability theory and Laplacian potential function in the graph theory, we conclude that the formation can be achieved by properly choosing the constant control gains. Further, when considering communication delays,a modified impulsive formation control algorithm is proposed, in which the extended Halanay differential inequality is used to analyze the stability of the impulsive delayed dynamical systems. Finally, numerical examples and performance comparisons with continuous algorithm are provided to illustrate the effectiveness of the proposed methods.     

Cooperatively surrounding control for multiple Euler–Lagrange systems subjected to uncertain dynamics and input constraints

In this paper, we investigate cooperatively surrounding control(CSC) of multi-agent systems modeled by Euler–Lagrange(EL) equations under a directed graph. With the consideration of the uncertain dynamics in an EL system, a backstepping CSC algorithm combined with neural-networks is proposed first such that the agents can move cooperatively to surround the stationary target. Then, a command filtered backstepping CSC algorithm is further proposed to deal with the constraints on control input and the absence of neighbors' velocity information. Numerical examples of eight satellites surrounding one space target illustrate the effectiveness of the theoretical results.