无线传感器/执行器网络中能量有效的实时分簇路由协议

无线传感器/执行器网络(WSANs)主要应用于自动控制领域,实时性问题是其面临的首要挑战.根据实际环境中的节点部署情况,建立了系统模型;研究了分簇策略与功率控制技术对于自组织网络实时性的影响,提出了一种可适用于WSANs的能量有效的实时分簇路由协议--RECRP协议.该协议采用二级成簇策略使网络中的各类节点稳定分簇.分簇后的各类节点具有不同发射功率,利用执行器节点的强大通信能力有效降低网络延时.采用能量有效性算法使网络中的传感器节点轮换担任簇首,从而使网络能量均匀消耗,延长网络的生存时间.实验结果证明,在WSANs中RECRP协议可使网络稳定分簇,并且在网络的实时性与能量有效性方面与现有典型路由协议相比具有更优越的性能.     

Dynamic Coverage with Wireless Sensor and Actor Networks in Underwater Environment

This paper studies the problem of dynamic coverage with wireless sensor and actor networks (WSANs) in underwater environment. Different from most existing works, the WSANs consist of two kinds of nodes, i.e., sensor nodes (SNs) which cannot move autonomously and actor nodes (ANs) which can move autonomously according to the performance requirement. The problem of how to coordinate two kinds of nodes to facilitate dynamic coverage in underwater environment is challenging due to their heterogeneous capabilities. To reduce redundancy of communication links and improve connectivity between ANs and SNs in underwater WSANs, a min-weighted rigid graph based topology optimization scheme is first developed, such that the underwater communication energy consumption can be saved. With the optimized topology, a dynamic coverage strategy is proposed to improve the coverage among SNs and ANs for underwater WSAN where underwater fluid motions are considered. Furthermore, it is proved that the network coverage area is connected by using the min-weighted rigid graph. Finally, simulation results are presented to show the effectiveness of the main results.      

An optimal control method for applications using wireless sensor/actuator networks

The wireless sensor/actuator networks (WSANs) can be used for spatially distributed control systems. With smart sensors and actuators, the WSANs are able to not only sense the control system states and report measurements, but also perform control and actuation. This paper investigates WSANs on their ability of control. A centralized controller is introduced into WSANs to make up closed-loop control systems, in which control decisions are made based on global network-wide information. A model of the control and communication over WSANs is made theoretically, based on which we achieved an optimal control method. It is demonstrated by simulations that the control method proposed could stabilize the control system quickly.     

基于遗传算法的无线传感器/执行器网络故障检测滤波器设计

为提高无线传感器/执行器网络(WSAN)的可靠性,提出一种基于遗传算法(GA)的WSAN故障检测滤波器的优化设计方法。在系统建模时将无线网络传输延迟对网络控制系统的影响建模为一种系统扰动噪声,将由敏感度和鲁棒性构成的复合优化指标作为故障检测滤波器的优化目标函数,即适应度函数。同时根据优化目标在自动控制系统中的数值特性,选择与之相适应的实数编码、均匀变异和算术交叉等处理方法,以期在加快收敛速度的同时也兼顾计算结果的精确度。所提的优化滤波器设计,不仅能抑制滤波器信号中的噪声分量,而且能放大故障信号。最后,通过Matlab/OMNET++的仿真平台验证了这一设计的有效性。     

An approach based on the domain perspective to develop WSAN applications

As wireless sensor and actuator networks (WSANs) can be used in many different domains, WSAN applications have to be built from two viewpoints: domain and network. These different viewpoints create a gap between the abstractions handled by the application developers, namely the domain and network experts. Furthermore, there is a coupling between the application logic and the underlying sensor platform, which results in platform-dependent projects and source codes difficult to maintain, modify, and reuse. Consequently, the process of developing an application becomes cumbersome. In this paper, we propose a model-driven architecture (MDA) approach for WSAN application development. Our approach aims to facilitate the task of the developers by: (1) enabling application design through high abstraction level models; (2) providing a specific methodology for developing WSAN applications; and (3) offering an MDA infrastructure composed of PIM, PSM, and transformation programs to support this process. Our approach allows the direct contribution of domain experts in the development of WSAN applications, without requiring specific knowledge of programming WSAN platforms. In addition, it allows network experts to focus on the specific characteristics of their area of expertise without the need of knowing each specific application domain.     

无线感知执行网的智能协作机制研究

针对无线感知执行网中的节点协作问题,提出了多目标智能协作策略。在感知节点不完全连通的WSANs中,设计局部感知节点成簇算法,实现感知节点间的通信协作;以网络能耗均衡和信息传输时延为目标,应用离散多目标自由搜索算法对WSANs进行实时路径规划,实现簇头节点和执行节点间的协作,并通过路径惩罚策略和路径均衡策略,保证寻优结果的有效性、均衡执行节点之间的能耗。仿真实验表明:无线感知执行网智能协作机制能有效地选择多执行节点路径,实现网络协作的实时需求与能量消耗之间的平衡。     

无线传感器/反应器网络中反应节点优化重定位机制研究

针对无线传感器/反应器网络中因多个反应器失效而造成的反应器网络连通性被破坏问题,以网络流理论为基础,提出了一个基于网络流的多目标规划模型来求解优化的反应器重定位方案。模型将反应器网络看成是一个运输网络,通过流平衡条件来重建反应器网络的连通性。最小化多个参与恢复的反应器总体开销和最小化单个反应器的最大开销是该模型的两个优化目标。仿真实验结果表明,基于该模型的优化重定位方案能够有效地恢复因多反应器节点失效而造成的网络连通性问题。     

生物启发的无线传感执行网络协同方法

本文针对无线传感执行网络(wireless sensor and actor network,WSAN),在昆虫生物种群协作机理的启发下,提出了一种WSAN协同方法,以改善网络传输可靠性、节能与执行效率.首先,针对传感器节点与执行器节点之间的协作,提出以信息传递能耗和剩余能量衡量中继节点选择概率的效能协同机制,以及包含区域中继、影响因子和学习因子3个保障单元的组织协同机制.进而,针对执行器--执行器间的协作,引入学习因子作为组织协同机制中的一个保障单元.最后,给出了算法执行的流程,并通过仿真验证了方法的优越性.仿真结果表明,采用本文提出的协同机制,不但优化了WSAN信息传递路径,而且在执行器节点间协作中选择优势节点参与信息处理和决策,降低了网络能耗,同时提高了网络执行效率.     

Neural-network-based approach to finite-time optimal control for a class of unknown nonlinear systems

This paper proposes a novel finite-time optimal control method based on input–output data for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. In this method, the single-hidden layer feed-forward network (SLFN) with extreme learning machine (ELM) is used to construct the data-based identifier of the unknown system dynamics. Based on the data-based identifier, the finite-time optimal control method is established by ADP algorithm. Two other SLFNs with ELM are used in ADP method to facilitate the implementation of the iterative algorithm, which aim to approximate the performance index function and the optimal control law at each iteration, respectively. A simulation example is provided to demonstrate the effectiveness of the proposed control scheme.     

Closed-loop drip irrigation control using a hybrid wireless sensor and actuator network

In this research, a closed-loop drip irrigation control hybrid wireless sensor and actuator network (HWSAN) prototype were developed and deployed in a crop field for soil property precise measurement and precision irrigation in accordance with the measured soil property. The HWSAN was composed of a wireless sensor and actuator network (WSAN) used for in-field soil property monitoring and irrigation control and a laboratory supervising system. The WSAN included ten sensor nodes, five irrigation control nodes...     

Design of robust model predictive control with input constraints

This article addresses the problem of designing a robust output feedback model predictive control (MPC) with input constraints, which ensures a parameter-dependent quadratic stability and guaranteed cost for the case of linear polytopic systems. A new heuristic method is introduced to guarantee input constraints for the MPC. To reject disturbances and maintain the process at the optimal operating conditions or setpoints, the integrator is added to the controller design procedure. Finally, some numerical examples are given to illustrate the effectiveness of the proposed method.     

Robust model predictive control under redundant channel transmission with applications in networked DC motor systems

In networked systems, intermittent failures in data transmission are usually inevitable due to the limited bandwidth of the communication channel, and an effective countermeasure is to add redundance so as to improve the reliability of the communication service. This paper is concerned with the model predictive control (MPC) problem by using static output feedback for a class of polytopic uncertain systems with redundant channels under both input and output constraints. By utilizing the min–max control approach combined with stochastic analysis, sufficient conditions are established to guarantee the feasibility of the designed MPC scheme that ensures the robust stability of the closed‐loop system. In terms of the solution to an auxiliary optimization problem, an easy‐to‐implement MPC algorithm is proposed to obtain the desired sub‐optimal control sequence as well as the upper bound of the quadratic cost function. Finally, to illustrate its effectiveness, the proposed design method is applied to control a networked direct current motor system. Copyright © 2016 John Wiley & Sons, Ltd.     

无线传感器/执行器网络中的定向简单竞拍聚合协议

在无线传感器/执行器网络(WSAN)中,移动执行器(actor)节点之间需要通过协商进行任务分配来响应产生的服务请求,其目标是尽可能减少协商时的通信开销和对事件的响应时间。现有的解决方案中,基于市场竞拍的分布式简单竞拍聚合协议(SAAP)比较适合资源受限的WSAN网络。在SAAP的基础上提出了一种定向的竞拍聚合协议DSAAP,该协议根据方向信息对下一跳子节点进行筛选,同时限制回传的信息,以减少竞拍过程中的消息转发。通过实验与现有的SAAP进行比较,发现该协议在最优节点发现率和选出节点与最优节点距离比这两个参数性能不降低的前提下降低了通信开销。     

Finite-time event-triggered control for a class of cascade switched affine nonlinear systems

This paper is concerned with the finite-time boundedness (FTB) problem of a class of cascade switched affine nonlinear systems. In order to avoid unnecessary waste of network communication and Zeno behavior, a dynamical event-triggered scheme is proposed, which is more general than some existing event-triggered schemes with a common parameter matrix. By using the average dwell time method and multiple Lyapunov function technologies, sufficient conditions for the existence of controller gains are first proposed such that the closed-loop system is finite-time bounded with a finite-time disturbance attenuation performance. It is also proved that the Zeno phenomenon is excluded. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.     

Input–output finite-time stabilisation of nonlinear stochastic system with missing measurements

This paper considers the problem of the input–output finite-time stabilisation for a class of nonlinear stochastic system with state-dependent noise. The phenomenon of the missing measurements may occur when state signals are transmitted via communication networks. An estimating method is proposed to compensate the lost state information. And then, a compensator-based controller is designed to ensure the input–output finite-time stochastic stability (IO-FTSS) of the closed-loop system. Some parameters-dependent sufficient conditions are derived and the corresponding solving approach is given. Finally, numerical simulations are provided to demonstrate the feasibility and effectiveness of the developed IO-FTSS scheme.     

Quasi-min-max output-feedback model predictive control for LPV systems with input saturation

In the research field of model predictive control (MPC), an output-feedback-type MPC method is consistently required for controlling a wide range of constrained systems. In this paper, we propose a two-stage control strategy for polytopic linear parameter varying (LPV) systems subject to input constraints. This strategy consists of a modified quasi-min-max output-feedback MPC method and a novel terminal output-feedback robust control technique. The proposed control mechanism involves the system states to be first controlled via the MPC method to be driven into a prescribed neighborhood of the origin, and then, the terminal output-feedback robust control method guaranteeing the input constraints is applied to make such states converge to the origin. It is also verified that our control method guarantees the closed-loop stability and feasibility in the presence of model uncertainties and input constraints. Finally, a numerical example is given to demonstrate its effectiveness.     

WSAN网络密钥管理模型的研究

无线传感器和反应器网络（wireless sensor and actor network．WSAN）由三种具有不同级别能力和作用的节点构成,节点的异构性导致单纯使用一种安全模型将无法满足不同节点对性能和安全性的要求。为此,本文首次提出了一种复合式的安全模型,根据节点的能力和作用将WSAN网络分为两层,不同层通过应用不同的安全机制,实现不同级别的安全服务。另外,本模型通过多种方式降低系统开销,力求达到安全和性能的平衡。     

Barrier function based finite-time tracking control for a class of uncertain nonlinear systems with input saturation

In this article, a novel robust finite-time tracking control scheme is proposed for a class of uncertain nonlinear systems subject to the model uncertainty, external disturbance, and input saturation. A barrier function based disturbance observer (BFDO) with finite-time convergence performance is developed to estimate the non-smooth nonlinear compound disturbance, which includes the uncertainty, disturbance of system and input saturation. In addition, an adaptive continuous nonsingular terminal sliding mode controller, based on the barrier function and the estimate of the BFDO is developed. The Lyapunov stability and finite-time convergence of the proposed control scheme are proved. The effectiveness and performance advantage of the proposed control scheme is demonstrated by numerical simulations and comparison with existing works.     

Scalable security in Wireless Sensor and Actuator Networks (WSANs): Integration re-keying with routing

Our research aims to address the challenging security issues in Wireless Sensor and Actuator Networks (WSANs), a special type of Wireless Sensor Networks (WSNs). Since WSANs have specific network constraints and data transmission requirements compared to general ad hoc networks and other wireless/wired networks, we propose to seamlessly integrate WASN security with a ripple-zone (RZ)-based routing architecture that is scalable and energy-efficient. In this research, we will also develop a two-level re-keying/re-routing schemes that cannot only adapt to a dynamic network topology but also securely update keys for each data transmission session. Moreover, to provide the security for the in-networking processing such as data aggregation in WSANs, we define a multiple-key management scheme in conjunction with our proposed Ripple-Zone routing architecture. Extensive simulations and hardware experiments have been conducted to verify the energy-efficiency and security performance of our security scheme for WSANs.     

Nash-based robust distributed model predictive control for large-scale systems

In this paper, a new robust distributed model predictive control (RDMPC) is proposed for large-scale systems with polytopic uncertainties. The time-varying system is first decomposed into several interconnected subsystems. Interactions between subsystems are obtained by a distributed Kalman filter, in which unknown parameters of the system are estimated using local measurements and measurements of neighboring subsystems that are available via a network. Quadratic boundedness is used to guarantee the stability of the closed-loop system. In the MPC algorithm, an output feedback-interaction feedforward control input is computed by an LMI-based optimization problem that minimizes an upper bound on the worst case value of an infinite-horizon objective function. Then, an iterative Nash-based algorithm is presented to achieve the overall optimal solution of the whole system in partially distributed fashion. Finally, the proposed distributed MPC approach is applied to a load frequency control (LFC) problem of a multi-area power network to study the efficiency and applicability of the algorithm in comparison with the centralized, distributed and decentralized MPC schemes.