Distributed optimal coordination control for nonlinear multi-agent systems using event-triggered adaptive dynamic programming method

This paper is concerned with the design of distributed optimal coordination control for nonlinear multi-agent systems (NMASs) based on event-triggered adaptive dynamic programming (ETADP) method. The method is firstly introduced to design the distributed coordination controllers for NMASs, which not only avoids the transmission of redundant data compared with traditional time-triggered adaptive dynamic programming (TTADP) strategy and minimizes the performance function of each agent. The event-triggered conditions are proposed based on Lyapunov functional method, which is deduced by guaranteeing the stability of NMASs. Then a new adaptive policy iteration algorithm is presented to obtain the online solutions of the Hamiton–Jocabi–Bellman (HJB) equations. In order to implement the proposed ETADP method, the fuzzy hyperbolic model based critic neural networks (NN) are utilized to approximate the value functions and help calculate the control policies. In critic NNs, the NN weight estimations are updated at the event-triggered instants leading to aperiodic weight tuning laws so that computation cost is reduced. It is proved that the weight estimation errors and the local neighborhood coordination errors is uniformly ultimately bounded (UUB). Finally, two simulation examples are provided to show the effectiveness of the proposed ETADP method.     

Event-triggered consensus control of disturbed multi-agent systems using output feedback

In this article, the event-triggered consensus control is investigated for general linear multi-agent systems with external disturbances, by using the accessible measurement outputs. In particular, a novel protocol is proposed using the local observed state variables at event-triggered instants, which are respectively derived by adopting an observer to each agent based on output signal. Then it is proved that under the designed event-triggered control protocol consensus can be achieved with the desired disturbance attenuation ability and no Zeno behavior occurs. A numerical simulation is given to demonstrate the effectiveness of the developed control strategy     

基于事件触发的Buck型DC-DC变换器有限时间控制

针对Buck型DC-DC变换器输出电压跟踪控制问题,提出了一种基于事件触发机制的有限时间控制方案。首先,将Buck变换器建模成一类反馈型非线性系统。然后,为能有效地避免通信资源的浪费,通过构造一种状态变换设计了一种事件触发机制;同时,利用反步法,设计了系统的状态反馈控制器,该控制器在事件触发时刻更新;然后,基于所设计的事件触发控制器,利用有限时间Lyapunov稳定性理论分析了系统的稳定性,并证明了所设计的控制方案不会发生Zeno现象;最后,通过Buck变换器仿真实例验证了所提出的事件触发控制方案的有效性,仿真结果表明了在所设计的控制方案下,Buck型DC-DC变换器的输出在有限时间内可以达到期望值,同时还能减少通信资源的浪费。     

工业信息物理系统数据注入攻击的事件触发弹性控制

工业信息物理系统(ICPS)恶劣的工业环境使得无线通信网络的通信资源有限, 且通信网络的脆弱性使得系统的稳定性容易受到数据注入攻击的破坏. 本文基于输入到状态理论, 采用H1观测器、预测器和事件触发器建立基于事件触发的ICPS模型来降低通信资源的利用率, 并构造基于改进卡尔曼滤波器的攻击补偿模块进行攻击补偿, 攻击补偿模块的参数随着攻击者攻击策略不同而进行改变, 实现对数据注入攻击的弹性控制. 用matlab软件进行仿真实验, 以倒立摆作为被控对象, 模拟基于事件触发的ICPS模型受到数据注入攻击时系统的稳定性能. 仿真结果表明, 事件触发控制策略和基于改进卡尔曼滤波器的攻击补偿模块的组合不仅能够保证系统期望的稳定性, 还能有效减少数据通过无线网络传输的次数.     

Networked Control Systems: A Survey of Trends and Techniques

Networked control systems are spatially distributed systems in which the communication between sensors, actuators,and controllers occurs through a shared band-limited digital communication network. Several advantages of the network architectures include reduced system wiring, plug and play devices,increased system agility, and ease of system diagnosis and maintenance. Consequently, networked control is the current trend for industrial automation and has ever-increasing applications in a wide range of areas, such as smart grids, manufacturing systems,process control, automobiles, automated highway systems, and unmanned aerial vehicles. The modelling, analysis, and control of networked control systems have received considerable attention in the last two decades. The ‘control over networks’ is one of the key research directions for networked control systems. This paper aims at presenting a survey of trends and techniques in networked control systems from the perspective of ‘control over networks’, providing a snapshot of five control issues: sampled-data control, quantization control, networked control, event-triggered control, and security control. Some challenging issues are suggested to direct the future research.     

Sampled-data control systems with non-uniform sampling: A survey of methods and trends

The convergence of sensing, computing, communication and control elements drives the traditional point-to-point control systems towards networked control systems. Sampled-data control systems, which focus on the significant interplay between sampling and control, play a critical role in modern networked control systems, including intelligent transportation systems, smart grids, and advanced manufacturing systems. This paper presents a survey of methods and trends in non-uniform sampled-data control systems, where sampling and control actions are performed in an aperiodic manner. First, some fundamental issues of both continuous- and discrete-time sampled-data control systems are discussed. Next, main methods in both continuous-time and discrete-time domains are elaborated, respectively. Then, event-triggered sampling, under which sampling is executed only when the system needs attention, is examined. Typical triggering mechanisms in the existing literature are reviewed and classified into four types according to different threshold functions. Furthermore, two applications in terms of automated vehicle platoons and islanded microgrids are provided to demonstrate that sampled-data control methods are capable to support relevant practical application scenarios. Finally, several challenging issues are envisioned to direct future research.