Distributed estimation and control for mobile sensor networks with coupling delays

This paper deals with the issue of distributed estimation and control for mobile sensor networks with coupling delays. Based on the Kalman-Consensus filter and the flocking algorithm, all mobile sensors move to a target to increase the quality of gathered data, and achieve consensus on the estimation values of the target in the presence of time-delay and noises. By applying an effective cascading Lyapunov method and matrix theory, stability analysis is carried out. Furthermore, a necessary condition for the convergence is presented via the boundary conditions of feedback coefficients. Some numerical examples are provided to validate the effectiveness of theoretical results.     

塑料静电植绒工艺

介绍了PVC薄膜静电植绒的工艺及控制要点，并对产品所存在的问题进行了探讨解决。     

静电植绒胶的品种与制作二例

简要阐述静电植绒胶的现状、品种与研制方向，并介绍了布植绒胶和胶植绒胶的配方及制法。     

移动传感器网络中目标跟踪与监测的同步优化

针对移动传感器网络(Mobile sensor networks, MSNs)中动态目标(事件源)的监测优化问题, 为提高网络覆盖质量, 建立基于Voronoi剖分的监测性能(Quality of monitoring, QoM)评价函数, 提出基于群集控制的传感器节点部署分布式控制算法. 每个节点在本地结合最小二乘法和一致性算法来估计目标相对位置. 相比传统算法, 本文算法只需本地和单跳通信(可观测)邻居的信息, 从而减小通信时长和能耗. 算法在提高以目标为中心的一定区域监测性能的同时, 使全体传感器速度趋于一致, 从而在尽量保持网络拓扑结构的同时减少了整体移动能耗. 在目标匀速或目标加速度信息全网可知的情况下, 全体传感器速度渐近收敛至目标速度, 且监测性能收敛至局部最优. 所采用的目标位置估计滤波算法计算简单、切实可行.     

Flocking based distributed self-deployment algorithms in mobile sensor networks

In this paper, we address a novel deployment problem in isotropic mobile sensor networks. Sensors are to be relocated uniformly in a region of interest (ROI) centered at a target of interest (TOI) which could be stationary or mobile. With the assumption that relative direction of a sensor to the TOI can be recognized or inferred by devices equipped in the sensor, distributed control algorithms based on first-order and second-order dynamic models are proposed for both stationary and mobile TOI situations. The Lyapunov stabilities and coverage guarantee are provided. To further improve the deployment such as coverage holes inside the network and uniformity of the deployment, four assisted rules are also proposed. Then algorithms proposed for the situation of a stationary TOI are extended to anisotropic sensor networks. Simulations demonstrate the effective performances of the proposed algorithms.     

Flocking control of a fleet of unmanned aerial vehicles

Current applications using single unmanned vehicle have been gradually extended to multiple ones due to their increased efficiency in mission accomplishment, expanded coverage areas and ranges, as well as enhanced system reliability. This paper presents a flocking control method with application to a fleet of unmanned quadrotor helicopters (UQHs). Three critical characteristics of formation keeping, collision avoidance, and velocity matching have been taken into account in the algorithm development to make it capable of accomplishing the desired objectives (like forest/pipeline surveillance) by safely and efficiently operating a group of UQHs. To achieve these, three layered system design philosophy is considered in this study. The first layer is the flocking controller which is designed based on the kinematics of UQH. The modified Cucker and Smale model is used for guaranteeing the convergence of UQHs to flocking, while a repelling force between each two UQHs is also added for ensuring a specified safety distance. The second layer is the motion controller which is devised based on the kinetics of UQH by employing the augmented state-feedback control approach to greatly minimize the steady-state error. The last layer is the UQH system along with its actuators. Two primary contributions have been made in this work: first, different from most of the existing works conducted on agents with double integrator dynamics, a new flocking control algorithm has been designed and implemented on a group of UQHs with nonlinear dynamics. Furthermore, the constraint of fixed neighbouring distance in formation has been relaxed expecting to significantly reduce the complexity caused by the increase of agents number and provide more flexibility to the formation control. Extensive numerical simulations on a group of UQH nonlinear models have been carried out to verify the effectiveness of the proposed method.     

Emotional clouds: Showing arousal and valence through the movement and darkness of digital cartoonish clouds

While nowadays the most usual way to show emotions in digital contexts is via virtual characters, its use may raise false expectations (the user attributes human abilities to the virtual character). This paper proposes and explores an approach to express emotions which intends to minimize the user's expectations by using a non-anthropomorphic model. Emotions are represented in terms of arousal and valence dimensions. They are visualized in a simple way through the behaviour and appearance of a series of cartoonish clouds. In particular, the arousal value is expressed through the movement of these clouds (controlled by a flocking algorithm), while the valence value is expressed through their degree of darkness. Furthermore, the paper describes a user experiment which investigated whether the arousal and valence expressed by our model are appropriately interpreted by the users or not. The results suggest that movement and darkness are interpreted as arousal and valence respectively and that they are independent of each other.     

Experimental implementation of distributed flocking algorithm for multiple robotic fish

This paper presents the experimental implementation of a flocking algorithm for multiple robotic fish governed by extended second-order unicycles. Combing consensus protocols with attraction/repulsion functions, a flocking algorithm is proposed to make the agents asymptotically converge to swim with consistent velocities and approach the equilibrium distances to their neighbors. The LaSalle–Krasovskii invariance principle is applied to verify the stability of the system. Besides numerical simulations, platform simulations involving robotic fish kinematic constraint and control mechanism are shown. An experiment with three robotic fish is implemented to illustrate the effectiveness of the proposed flocking algorithm in the presence of external disturbance and boundary collision.     

Robust adaptive fault-tolerant control for leader-follower flocking of uncertain multi-agent systems with actuator failure

In this work, we study the flocking problem of multi-agent systems with uncertain dynamics subject to actuator failure and external disturbances. By considering some standard assumptions, we propose a robust adaptive fault tolerant protocol for compensating of the actuator bias fault, the partial loss of actuator effectiveness fault, the model uncertainties, and external disturbances. Under the designed protocol, velocity convergence of agents to that of virtual leader is guaranteed while the connectivity preservation of network and collision avoidance among agents are ensured as well.