A new framework for consensus for discrete-time directed networks of multi-agents with distributed delays

In this article, the distributed consensus problem is considered for discrete-time delayed networks of dynamic agents with fixed topologies, where the networks under investigation are directed and the time delays involved are distributed time delays including a single or multiple time delay(s) as special cases. By using the invariance principle of delay difference systems, a new unified framework is established to deal with the consensus for the discrete-time delayed multi-agent system. It is shown that the addressed discrete-time network with arbitrary distributed time delays reaches consensus provided that it is strongly connected. A numerical example is presented to illustrate the proposed methods.     

Novel distributed robust adaptive consensus protocols for linear multi-agent systems with directed graphs and external disturbances

This paper addresses the distributed consensus protocol design problem for linear multi-agent systems with directed graphs and external unmatched disturbances. Novel distributed adaptive consensus protocols are proposed to achieve leader–follower consensus for any directed graph containing a directed spanning tree with the leader as the root node and leaderless consensus for strongly connected directed graphs. It is pointed out that the adaptive protocols involve undesirable parameter drift phenomenon when bounded external disturbances exist. By using the σ modification technique, distributed robust adaptive consensus protocols are designed to guarantee the ultimate boundedness of both the consensus error and the adaptive coupling weights in the presence of external disturbances. All the adaptive protocols in this paper are fully distributed, relying on only the agent dynamics and the relative states of neighbouring agents.     

Distributed cooperative control of multi-converter systems via networks

Modular converters are employed for ultra-large ship degaussing systems to improve the magnetic stealth capability. However, the degaussing performance could be compromised by the inconsistent current in various modules. Therefore, current synchronization is a crucial issue in the control of distributed multi-converter systems (DMCSs). To meet the high requirement of such an industrial scenario, a distributed cooperative control scheme is conceived for DMCSs in this paper. The consensus and stability of the DMCS are analyzed, in contrast to existing works that only take consensus into account, and the necessary and sufficient conditions are derived with the constructed closed-loop control system. Then, the tailor-made controller design guideline is presented. Different cases of a cyber-physical DMCS in the MATLAB/SimPowerSystems environment are examined to confirm the viability. Furthermore, experiments with a multi-converter prototype system are carried out to confirm the efficiency of the proposed control method. Results from simulations and experiments are in line with the theoretical analysis, validating the efficacy.     

A framework for decentralised feedback connectivity control with application to sensor networks

In this article, we propose a decentralised algorithm for connectivity maintenance in a distributed sensor network. Our algorithm uses the dynamics of a consensus algorithm to estimate the connectivity of a network topology in a decentralised manner. These estimates are then used to inform a decentralised control algorithm that regulates the network connectivity to some desired level. Under certain realistic assumptions we show that the closed-loop dynamics can be described as a consensus algorithm with an input, and eventually reduces to a scalar system. Bounds are given to ensure the stability of the algorithm and examples are given to illustrate the efficacy of the proposed algorithm.     

非平衡有向网络下带约束的连续时间分布式优化算法设计EI北大核心CSCD

本文基于权重不平衡有向网络,对一类分布式约束优化问题进行研究,其中全局目标函数等于具有李普希兹梯度的强凸目标函数之和,并且每个智能体的状态都有一个局部约束集.每个智能体仅知道自身的局部目标函数和非空约束集.本文的目标是用分布式方法求解该问题的最优解.针对优化问题,提出了一种新的分布式投影梯度连续时间协调算法,利用拉普拉斯矩阵的零特征值对应的左特征向量消除了图的不平衡性.在某些假设下,结合凸分析理论和李雅普诺夫稳定性理论,证明了算法能够获得问题的最优解.最后,通过仿真验证了算法的有效性.     

A distributed market-based boundary coverage algorithm for multiple microrobots with network connectivity maintenance

In this paper, the boundary coverage of known environments is investigated using multiple microrobots (MMR) involved in a distributed inspection case study. A strong need for an operator is able to control and receive feedback from microrobots. However, communication range is limited because of the size effect of microrobot, and obstacles may also prevent microrobots from communicating. To enable MMR to accomplish coverage task while maintaining the network connectivity with a base station, we propose a market-based boundary coverage algorithm. This algorithm can dynamically allocate the boundary coverage task to a microrobot, so as to adapt to the change of communication network topology. A motion control model based on virtual spring–damper system is established to prevent communication network splitting by monitoring infrared link quantity information among microrobot nodes. Simulations and experimental results, obtained using our MMR tested in a distributed inspection case study, demonstrate that the proposed solution fulfills the objective of maintaining network connectivity at all times while completing the allocated boundary coverage task.     

Sliding mode control of wind-induced vibrations using fuzzy sliding surface and gain adaptation

Although fuzzy/adaptive sliding mode control can reduce the chattering problem in structural vibration control applications, they require the equivalent control and the upper bounds of the system uncertainties. In this paper, we used fuzzy logic to approximate the standard sliding surface and designed a dead-zone adaptive law for tuning the switching gain of the sliding mode control. The stability of the proposed controller is established using Lyapunov stability theory. A six-storey building prototype equipped with an active mass damper has been used to demonstrate the effectiveness of the proposed controller towards the wind-induced vibrations.     

Suboptimal distributed control and estimation: application to a four coupled tanks system

The paper proposes an innovative estimation and control scheme that enables the distributed monitoring and control of large-scale processes. The proposed approach considers a discrete linear time-invariant process controlled by a network of agents that may both collect information about the evolution of the plant and apply control actions to drive its behaviour. The problem makes full sense when local observability/controllability is not assumed and the communication between agents can be exploited to reach system-wide goals. Additionally, to reduce agents bandwidth requirements and power consumption, an event-based communication policy is studied. The design procedure guarantees system stability, allowing the designer to trade-off performance, control effort and communication requirements. The obtained controllers and observers are implemented in a fully distributed fashion. To illustrate the performance of the proposed technique, experimental results on a quadruple-tank process are provided.     

Cooperative tracking control for general linear multiagent systems with directed intermittent communications: An artificial delay approach

This paper investigates the consensus tracking problem for general linear multiagent systems on directed graph containing a spanning tree. For the considered linear systems, the consensus tracking aim cannot be achieved by using only memoryless static relative output feedbacks. Of particular interest is that both current and delayed relative output information of agents are required to achieve consensus. For the case of continuous communication among agents, an artificial delay output feedback control method is proposed. By utilizing the Taylor representation for the delayed signal with the remainder in the integral form, a delay‐dependent sufficient condition is presented to guarantee the exponential convergence of the global tracking error systems. For the intermittent case, the consensus tracking performance can still be guaranteed based on a multiple graph‐dependent Lyapunov functionals method. It is theoretically revealed that the time delay plays a key role in the exponential convergence of the closed‐loop systems, and the definite relationships among the time delay, network structure, communication rate, and consensus convergence rate are also provided. The effectiveness of the proposed control scheme is confirmed by numerical simulations.     

基于复合自适应律的直线电机自适应鲁棒控制

自适应鲁棒控制(ARC)能克服参数不确定性与扰动对系统的影响, 具有良好的输出跟踪性能. 然而常规ARC的参数估计值难以逼近真值. 为实现高性能的控制与准确的参数估计, 本文提出了基于复合自适应律的自适应鲁棒控制(CAARC). 该方法同时采用了输出误差与参数估计误差的相关信息构造自适应律, 具有比常规ARC更好的参数估计效果. 本文在理论上证明了CAARC的闭环稳定性与参数估计误差的收敛性, 并通过分析表明CAARC具有比常规ARC更好的输出跟踪性能, 最后通过仿真验证了该方法的有效性.     

Distributed consensus estimation for diffusion systems with missing measurements over sensor networks

In this paper, the problem of distributed consensus estimation with randomly missing measurements is investigated for a diffusion system over the sensor network. A random variable, the probability of which is known a priori, is used to model the randomly missing phenomena for each sensor. The aim of the addressed estimation problem is to design distributed consensus estimators depending on the neighbouring information such that, for all random measurement missing, the estimation error systems are guaranteed to be globally asymptotically stable in the mean square. By using Lyapunov functional method and the stochastic analysis approach, the sufficient conditions are derived for the convergence of the estimation error systems. Finally, a numerical example is given to demonstrate the effectiveness of the proposed distributed consensus estimator design scheme.     

多目标跟踪中多传感器分布式控制策略

分布式传感器网络技术在复杂的多目标跟踪系统中发挥了极其重要的作用.本文针对多传感器多目标跟踪中的分布式传感器控制问题,提出了基于信息论的多传感器控制策略.首先,本文利用随机有限集(RFS)建模,给出了多传感器多伯努利滤波器,并通过一组参数化的多伯努利过程来近似多传感器多伯努利密度.进一步的,通过多伯努利滤波器的序贯蒙特卡罗实现,设计采样方案对多伯努利密度进行粒子采样,用一组带有权值的粒子集近似多目标状态空间分布.随后,借助巴氏距离(Bhattacharyya distance)作为传感器控制的评价函数用于多个传感器的独立并行控制方案的决策制定.作为另外一个重要内容,本文提出了一种基于多目标战术重要性评估的多传感器控制策略.该控制方案旨在评估多目标战术重要性的基础上对威胁度最大的目标进行优先跟踪.最后,仿真实验验证了所提算法的有效性.     

Sensor-network-based robust distributed control and estimation

This paper proposes a novel distributed estimation and control method for uncertain plants. It is of application in the case of large-scale systems, where each control unit is assumed to have access only to a subset of the plant outputs, and possibly controls a restricted subset of input channels. A constrained communication topology between nodes is considered so the units can benefit from estimates of neighboring nodes to build their own estimates. The paper proposes a methodology to design a distributed control structure so that the system is asymptotically driven to equilibrium with L₂-gain disturbance rejection capabilities. A difficulty that arises is that the separation principle does not hold, as every single unit ignores the control action that other units might be applying. To overcome this, a two-stage design is proposed: firstly, the distributed controllers are obtained to robustly stabilize the plant despite the observation errors in the controlled output. At the second stage, the distributed observers are designed aiming to minimize the effects of the communication noise in the observation error. Both stages are formulated in terms of linear matrix inequalities. The performance is shown on a level-control real plant.     

Cooperative adaptive control for synchronization of second‐order systems with unknown nonlinearities

This paper studies synchronization to a desired trajectory for multi‐agent systems with second‐order integrator dynamics and unknown nonlinearities and disturbances. The agents can have different dynamics and the treatment is for directed graphs with fixed communication topologies. The command generator or leader node dynamics is also nonlinear and unknown. Cooperative tracking adaptive controllers are designed based on each node maintaining a neural network parametric approximator and suitably tuning it to guarantee stability and performance. A Lyapunov‐based proof shows the ultimate boundedness of the tracking error. A simulation example with nodes having second‐order Lagrangian dynamics verifies the performance of the cooperative tracking adaptive controller. Copyright © 2010 John Wiley & Sons, Ltd.     

Event-triggered robust distributed state estimation for sensor networks with state-dependent noises

This paper is concerned with the event-triggered distributed state estimation problem for a class of uncertain stochastic systems with state-dependent noises and randomly occurring uncertainties over sensor networks. An event-triggered communication scheme is proposed in order to determine whether the measurements on each sensor should be transmitted to the estimators or not. The norm-bounded uncertainty enters into the system in a random way. Through available output measurements from not only the individual sensor but also its neighbouring sensors, a sufficient condition is established for the desired distributed estimator to ensure that the estimation error dynamics are exponentially mean-square stable. These conditions are characterized in terms of the feasibility of a set of linear matrix inequalities, and then the explicit expression is given for the distributed estimator gains. Finally, a simulation example is provided to show the effectiveness of the proposed event-triggered distributed state estimation scheme.     

Sum‐of‐squares–based consensus verification for directed networks with nonlinear protocols

In this paper, we investigate the consensus verification problem of nonlinear agents in a fixed directed network with a nonlinear protocol. Inspired by the classical Lipschitz‐like condition, we introduce a more relax condition for the dynamics of the nonlinear agents. This condition is motivated via the construction of general Lyapunov functions for achieving asymptotic consensus. Especially, for agents where dynamics are described by polynomial function of the states, our consensus criterion can be converted to a sum of squares (SOS) programming problem, solvable via semidefinite programming tools. Of interest is that the scale of the resulting SOS programming problem does not increase as the size of the network increases, and thus, the applicability to analyze consensus of large‐scale networks is promising. Finally, an example is given to illustrate the effectiveness of our theoretical results.     

Distributed state estimation for uncertain Markov‐type sensor networks with mode‐dependent distributed delays

In this paper, the distributed state estimation problem is investigated for a class of sensor networks described by uncertain discrete‐time dynamical systems with Markovian jumping parameters and distributed time‐delays. The sensor network consists of sensor nodes characterized by a directed graph with a nonnegative adjacency matrix that specifies the interconnection topology (or the distribution in the space) of the network. Both the parameters of the target plant and the sensor measurements are subject to the switches from one mode to another at different times according to a Markov chain. The parameter uncertainties are norm‐bounded that enter into both the plant system as well as the network outputs. Furthermore, the distributed time‐delays are considered, which are also dependent on the Markovian jumping mode. Through the measurements from a small fraction of the sensors, this paper aims to design state estimators that allow the nodes of the sensor network to track the states of the plant in a distributed way. It is verified that such state estimators do exist if a set of matrix inequalities is solvable. A numerical example is provided to demonstrate the effectiveness of the designed distributed state estimators. Copyright © 2011 John Wiley & Sons, Ltd.     

城市路网交通分散协调控制

针对城市路网交通系统规模大和非线性、不确定性强等特点，利用模糊神经网络设计了一种新的实时分散协调控制算法．把城市区域和市内快速公路作为一个路网大系统，子系统为路网中的各个交叉口；每个子系统都有一个模糊神经网络控制器，该控制器根据它自己和相邻子系统的交通流信息来动态管理相序及绿灯时间．控制器由3个模块组成：相序选择模块、绿灯判断模块和相位切换模块．控制器的控制目标是保持快速公路主线密度均衡和区域内各车辆平均延误时间最短．仿真研究表明，该算法能有效处理各种路网交通环境．     

超级电容负载的耦合并联充电系统无源分布式协同控制

储能式轻轨车辆采用超级电容作为动力源,其并联充电系统每个充电机不可避免的存在着线路不对称、元器件老化及工艺误差等因素,使得输出电流不均衡.本文将并联充电系统的电流均衡问题抽象成一类非线性耦合动态互联系统的输出同步问题,结合系统的无源性,根据最近邻原则,借助饱和函数,设计了保证控制输入有界的输出同步控制器.利用子系统存储...