Observer-based dynamic event-triggered control for distributed parameter systems over mobile sensor-plus-actuator networks

We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.

基于DCS-惯性权重组合的柔性机械臂运动轨迹控制系统研究

为了有效调控机械臂运动幅度,避免柔性机械臂实际运动轨迹与目标轨迹发生较大的偏差,设计一种基于分散控制系统(DCS)-惯性权重组合的柔性机械臂运动轨迹控制系统,它是一个集合了计算机、通信、显示和控制的计算机系统,该系统由过程控制和过程监控。通过DCS算法控制监测对象行为幅度并计算柔性机械臂惯性权重,利用DCS-惯性权重组合求解素数控制指标的具体数值,实现了对柔性机械臂运动轨迹控制系统的软件设计。实验结果表明,DCS-惯性权重组合算法作用下的机械臂末端坐标在横轴、纵轴、空间轴方向上的运动幅值均可以被控制在10个单位长度之内,并且在0.52 s内进入机械臂运动轨迹最佳控制状态,运动轨迹差值最大仅为0.01 rad,验证了该系统具备可行性和有效性。

基于CNN的OCR技术在核电厂DCS系统测试中的应用和实现

核电厂分布式控制系统(DCS)的输入/输出模块在运行期间,随着电子器件性能下降以及时漂的影响,需要定期进行进度复测和校准。针对传统的DCS输入/输出通道测试覆盖率不足,测试效率低及人因问题,本文提出一种基于卷积神经网络(CNN)的光学字符识别(OCR)技术应用在DCS系统的在线测试方法。通过模拟设备和视频采集设备完成画面的自动切换,并读取画面信息,截取特定画面后对其图像预处理,再使用OCR识别模型识别画面内容,将得到的识别结果与期望值进行比较判断,从而实现自动化测试。测试结果表明,通过CNN训练后,显控设备画面字符识别率能达到100%,该方法可以突破设备厂家的专有通信协议的壁垒,可有效降低操作员的人因失误,提升测试效率和核电厂的经济性。

基于SCADA-DCS通讯技术的油气开采数据自动化采集与控制系统

设计基于SCADA-DCS通讯技术的油气开采数据自动化采集与控制系统。系统以SCADA服务器为上层监控服务器,通过与井站现场仪器仪表实时通信,监控整个开采过程。当油气缓冲罐液位越限时,SCADA服务器自动下达指令至原油处理站DCS,启动基于智能PID的油泵控制器,调节油泵变频器,控制油气液位不溢出。系统使用SCADA-DCS通讯技术的MODBUS通信协议,并根据通信中断优先级分配方法,确保对中断处理时间要求高的通信请求能实时响应。实验结果表明,该系统能提升油气液位控制和紧急信息通讯效率。

Data-Driven Control of Distributed Event-Triggered Network Systems

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems(a.k.a.network systems).To this end,we start by putting forth a novel distributed event-triggering transmission strategy based on periodic sampling,under which a model-based stability criterion for the closed-loop network system is derived,by leveraging a discrete-time looped-functional approach.Marrying the model-based criterion with a data-driven system representation recently developed in the literature,a purely data-driven stability criterion expressed in the form of linear matrix inequalities(LMIs)is established.Meanwhile,the data-driven stability criterion suggests a means for co-designing the event-triggering coefficient matrix and the feedback control gain matrix using only some offline collected state-input data.Finally,numerical results corroborate the efficacy of the proposed distributed data-driven event-triggered network system(ETS)in cutting off data transmissions and the co-design procedure.

DCS devices based non-linear process control system design for plants with distributed time-delay using particle filter

Remote control process system with distributed time-delay has attracted much attention in different fields.In this paper,non-linear remote control of a single tank process system with wireless network is considered.To deal with the distributed time-delay in a large-scale plant,the time-delay compensation controller based on DCS devices is designed by using operator theory and particle filter.Distributed control system(DCS)device is developed to monitor and control from the central monitoring room to each process.The particle filter is a probabilistic method to estimate unobservable information from observable information.First,remote control system and experimental equipment are introduced.Second,control system based on an operator theory is designed.Then,process system with distributed time-delay using particle filter is carried out.Finally,the actual experiment is conducted by using the proposed time-delay compensation controller.When estimating with the proposed method,the result is close to the case in which the distributed time-delay does not exist.The effectiveness of the proposed control system is confirmed by experiment results.

DCS控制器中电表接触传感器计量误差检测方法

由于DCS控制器中电表传感器在计量检测过程中,传统的B-MAC-DCS协议能耗和丢包率较高,无法缓解汇聚节点的漏斗效应,导致在远程抄表过程中传感器计量误差增大。提出一种机械电表接触传感器计量误差检测方法。采用小波基函数对DCS控制器中的接触传感器计量数据抗干扰处理,并通过动态选取阈值的方法,对经过小波变换后的数据去除噪声。使用低功耗自适应集簇分层型(low energy adaptive clustering hierarchy,LEACH)协议分簇代替传统的B-MAC协议;根据簇内监测值,引入阈值分析方法获取传感器计量指标,并将其作为判定依据进行误差检测,根据计量指标的变化情况判断是否存在计量误差。实验结果表明,所提方法可以准确且有效检测出机械电表接触传感器计量误差,解决DCS中机械电表的运行隐患问题。

A PI+R Control Scheme Based on Multi-Agent Systems for Economic Dispatch in Isolated BESSs

Battery energy storage systems(BESSs)are widely used in smart grids.However,power consumed by inner impedance and the capacity degradation of each battery unit become particularly severe,which has resulted in an increase in operating costs.The general economic dispatch(ED)algorithm based on marginal cost(MC)consensus is usually a proportional(P)controller,which encounters the defects of slow convergence speed and low control accuracy.In order to solve the distributed ED problem of the isolated BESS network with excellent dynamic and steady-state performance,we attempt to design a proportional integral(PI)controller with a reset mechanism(PI+R)to asymptotically promote MC consensus and total power mismatch towards 0 in this paper.To be frank,the integral term in the PI controller is reset to 0 at an appropriate time when the proportional term undergoes a zero crossing,which accelerates convergence,improves control accuracy,and avoids overshoot.The eigenvalues of the system under a PI+R controller is well analyzed,ensuring the regularity of the system and enabling the reset mechanism.To ensure supply and demand balance within the isolated BESSs,a centralized reset mechanism is introduced,so that the controller is distributed in a flow set and centralized in a jump set.To cope with Zeno behavior and input delay,a dwell time that the system resides in a flow set is given.Based on this,the system with input delays can be reduced to a time-delay free system.Considering the capacity limitation of the battery,a modified MC scheme with PI+R controller is designed.The correctness of the designed scheme is verified through relevant simulations.

Autonomous Vehicle Platoons In Urban Road Networks:A Joint Distributed Reinforcement Learning and Model Predictive Control Approach

In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the proposed approach. Moreover, it is important to underline that in different operating scenarios the proposed reinforcement learning scheme is capable of significantly reducing traffic congestion phenomena when compared with well-reputed competitors.

Distributed Economic MPC for Synergetic Regulation of the Voltage of an Island DC Micro-Grid

In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltage together with the insurance of having computational efficiency under a real-time requirement.Based on the feedback of the bus voltage,the deviation of the current is dispatched to each DG according to cost over the prediction horizon.Moreover,to avoid the excessive fluctuation of the battery power,both the discharge-charge switching times and costs are considered in the model predictive control(MPC) optimization problems.A Lyapunov constraint with a time-varying steady-state is designed in each local MPC to guarantee the stabilization of the entire system.The voltage stabilization of the MG is achieved by this strategy with the cooperation of DGs.The numeric results of applying the proposed method to a MG of the Shanghai Power Supply Company shows the effectiveness of the distributed economic MPC.

核电厂安全级DCS缺省值设置策略研究

针对数字化仪控系统中无效信号的质量位随意蔓延使系统处于一种不确定状态的问题,结合核电厂运行工况和信号特性,对龙鳞平台故障诊断机制和信号质量位标识进行研究。考虑故障安全准则,系统性地提出缺省值设置原则。从信号执行功能和信号边界两个维度进行分析,确认缺省值的设置范围,并详细给出执行保护功能、报警功能、维护和试验功能信号的缺省值设置策略。同时,针对传统的缺省值验证方式无法全面、有效地进行缺省值验证的问题,提出一种利用全范围模拟机和虚拟数字化控制系统(DCS)进行缺省值验证的新方法。利用该方法可有效地对DCS内设置的缺省值进行系统性的验证。所提出的缺省值设置策略和验证方法可为后续核电厂安全级DCS的缺省值分析和设置提供全面的指导。

DCS在电除尘系统自动控制的应用研究

传统的电除尘器自动控制系统采用可编程逻辑控制器(PLC)控制,其逻辑复杂、可读性差、可维护性低。PLC系统无法与主控系统完成一体化,导致工艺上的割裂,额外地增加了运维成本。本文提出了一种基于分散控制系统(DCS)的电除尘器自动控制方案。

Research on Scheduling Strategy of Flexible Interconnection Distribution Network Considering Distributed Photovoltaic and Hydrogen Energy Storage

Distributed photovoltaic(PV)is one of the important power sources for building a new power system with new energy as the main body.The rapid development of distributed PV has brought new challenges to the operation of distribution networks.In order to improve the absorption ability of large-scale distributed PV access to the distribution network,the AC/DC hybrid distribution network is constructed based on flexible interconnection technology,and a coordinated scheduling strategy model of hydrogen energy storage(HS)and distributed PV is established.Firstly,the mathematical model of distributed PV and HS system is established,and a comprehensive energy storage system combining seasonal hydrogen energy storage(SHS)and battery(BT)is proposed.Then,a flexible interconnected distribution network scheduling optimization model is established to minimize the total active power loss,voltage deviation and system operating cost.Finally,simulation analysis is carried out on the improved IEEE33 node,the NSGA-II algorithm is used to solve specific examples,and the optimal scheduling results of the comprehensive economy and power quality of the distribution network are obtained.Compared with the method that does not consider HS and flexible interconnection technology,the network loss and voltage deviation of this method are lower,and the total system cost can be reduced by 3.55%,which verifies the effectiveness of the proposed method.

DCS系统在燃气输配控制中的应用研究进展

为探讨DCS系统在燃气输配控制中的应用,并分析其通过实时监测和控制关键参数来提高系统效率和安全性的能力。采用DCS系统对天然气输配网络进行实时监测和控制。通过对天然气管道的压力、温度、流量等关键参数进行实时采集和调节,确保系统运行在稳定、高效的状态。同时,利用DCS系统的强大数据采集、处理和分析能力,对输配过程中的故障和异常情况进行快速诊断和处理,以提高故障排除的效率。此外,DCS系统还支持网络化和远程控制功能,实现对不同地理位置的天然气输配网络的集中监管和管理。结果表明:通过应用DCS系统,燃气输配控制实现了高效、准确和可靠的管理。实时监测和调节关键参数确保了系统运行的安全性和稳定性。快速诊断和处理故障和异常情况提高了故障排除的效率。网络化和远程控制功能实现了对不同地理位置的天然气输配网络的统一监管和管理,提高了管理效率。DCS系统在燃气输配控制中的应用具有重要意义和潜力。通过实时监测和控制关键参数,可以提高系统的效率和安全性。然而,该系统的应用也面临一些挑战,如高成本、技术难题以及应急处理等方面的问题。因此,需要进一步的技术研发和应用实践来不断提升DCS系统的性能和可靠性,以更好地满足燃气输配控制的需求。

A review of artificial intelligence applications in high-speed railway systems

In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,emergency communication,and real-time scheduling,demands advanced capabilities in real-time perception,automated driving,and digitized services,which accelerate the integration and application of Artificial Intelligence(AI)in the HSR system.This paper first provides a brief overview of AI,covering its origin,evolution,and breakthrough applications.A comprehensive review is then given regarding the most advanced AI technologies and applications in three macro application domains of the HSR system:mechanical manufacturing and electrical control,communication and signal control,and transportation management.The literature is categorized and compared across nine application directions labeled as intelligent manufacturing of trains and key components,forecast of railroad maintenance,optimization of energy consumption in railroads and trains,communication security,communication dependability,channel modeling and estimation,passenger scheduling,traffic flow forecasting,high-speed railway smart platform.Finally,challenges associated with the application of AI are discussed,offering insights for future research directions.

Plasma spraying system with distributed controlling

A distributed control system is designed for plasma spraying equipment and the configurations of system software and hardware is discussed. Through founding an expert database, the spraying process parameters are worked out and the initialization and control of spraying process are realized. The plasma spraying system with this control configuration can simplify the spraying operation, improve automation level of spray process, and approach the experience criterion as soon as possible.

Virtually coupled train set control subject to space-time separation:A distributed economic MPC approach with emergency braking configuration

The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.

化工安全生产中DCS自动化控制的应用

DCS自动化控制作为自动化控制最为重要的技术,极大推动了化工行业的发展。DCS控制系统在化工产品中的应用已是必然趋势,能大大加速国内化工行业的发展步伐,有效保障化工生产运行的安全性,降低生产能耗。重点探讨了DCS自动化控制系统在组合聚醚生产中的应用问题以及发展趋势,为相关化工企业的自动化转型提供参考。

The Design of Output Feedback Distributed Model Predictive Controller for a Class of Nonlinear Systems

For a class of nonlinear systems whose states are immeasurable, when the outputs of the system are sampled asynchronously, by introducing a state observer, an output feedback distributed model predictive control algorithm is proposed. It is proved that the errors of estimated states and the actual system's states are bounded. And it is guaranteed that the estimated states of the closed-loop system are ultimately bounded in a region containing the origin. As a result, the states of the actual system are ultimately bounded. A simulation example verifies the effectiveness of the proposed distributed control method.

DCS仪器控制系统在石化行业的优化设计

在石化行业中,DCS仪器控制系统已广泛应用于炼油化工生产过程中的各个环节,具有较高的控制精度和可靠性,有助于提高生产效率和降低能耗。然而,随着石化行业生产过程的日益复杂化和自动化水平的提高,对DCS仪器控制系统的要求也越来越高,DCS的性能和可靠性也直接影响到装置的整个生产过程。本文从DCS仪器控制系统设计需求出发,提出了现场运行中控制策略以及系统的软硬件的设计与开发的优化措施,并论述了未来的发展趋势,旨在提高其在石化行业的应用效果。