Non-fragile guaranteed cost control for uncertain neutral large-scale interconnected systems

This paper focuses on the problem of non-fragile decentralized guaranteed cost control for uncertain neutral large-scale interconnected systems with time-varying delays in state,control input and interconnections.A novel scheme,viewing the interconnections with time-varying delays as effective information but not disturbances,is developed.Based on Lyapunov stability theory,using various techniques of decomposing and magnifying matrices,a design method of the non-fragile decentralized guaranteed cost controller for unperturbed neutral large-scale interconnected systems is proposed and the guaranteed cost is presented.The further results are derived for the uncertain case from the criterion of unperturbed neutral large-scale interconnected systems.Finally,an illustrative example shows that the results are significantly better than the existing results in the literatures.

DECENTRALIZED STABILIZATION OF LARGE-SCALE LINEAR INTERCONNECTED SYSTEMS WITH TIME-VARYING DELAYS

The decentralized stabilization conditions for large-scale linear interconnection systems with time-varying delays were established by using some different decomposition cases of interconnection matrices, and a method for designing the decentralized local memoryless state feedback controllers was proposed. All of the considered delays are continuous function, and satisfy some conditions.

Fundamental Research on Enhancing Operation Reliability for Large-Scale Interconnected Power Grids——An interview with Zhou Xiaoxin, chief scientist of "973 Program"

At the end of last year, the editors from Power and Electrical Engineers interviewed Zhou Xiaoxin on "Fundamental Research on Enhancing Operation Reliability for Large-Scale Interconnected Power Grids", a project of "973 Program". Mr. Zhou, the chief engineer of China Electric Power Research Institute(CEPRI) and an academician of Chinese Academy of Sciences, is the chief scientist in charge of this research project.

Power interconnected system clustering with advanced fuzzy C-mean algorithm

An advanced fuzzy C-mean （FCM） algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, modified similarity measure was considered to gather nodes having similar characteristics. The similarity measure was needed to contain locafi0nal prices as well as regional coherency. In order to consider the two properties simultaneously, distance measure of fuzzy C-mean algorithm had to be modified. Regional clustering algorithm for interconnected power systems was designed based on the modified fuzzy C-mean algorithm. The proposed algorithm produces proper classification for the interconnected power system and the results are demonstrated in the example of IEEE 39-bus interconnected electricity system.

Application research on large-scale battery energy storage system under Global Energy Interconnection framework

In the context of constructing Global Energy Interconnection(GEI), energy storage technology, as one of the important basic supporting technologies in power system, will play an important role in the energy configuration and optimization. Based on the most promising battery energy storage technology, this paper introduces the current status of the grid technology, the application of large-scale energy storage technology and the supporting role of battery energy storage for GEI. Based on several key technologies of large-scale battery energy storage system, preliminary analysis of the standard system construction of energy storage system is made, and the future prospect is put forward.

Adaptive Decentralized Asymptotic Tracking Control for Large-Scale Nonlinear Systems With Unknown Strong Interconnections

An adaptive decentralized asymptotic tracking control scheme is developed in this paper for a class of large-scale nonlinear systems with unknown strong interconnections,unknown time-varying parameters,and disturbances.First,by employing the intrinsic properties of Gaussian functions for the interconnection terms for the first time,all extra signals in the framework of decentralized control are filtered out,thereby removing all additional assumptions imposed on the interconnec-tions,such as upper bounding functions and matching conditions.Second,by introducing two integral bounded functions,asymptotic tracking control is realized.Moreover,the nonlinear filters with the compensation terms are introduced to circumvent the issue of“explosion of complexity”.It is shown that all the closed-loop signals are bounded and the tracking errors converge to zero asymptotically.In the end,a simulation example is carried out to demonstrate the effectiveness of the proposed approach.

Decentralized robust stabilization of discrete-time fuzzy large-scale systems with parametric uncertainties: a LMI method

Decentralized robust stabilization problem of discrete-time fuzzy large-scale systems with parametric uncertainties is considered. This uncertain fuzzy large-scale system consists of N interconnected T-S fuzzy subsystems, and the parametric uncertainties are unknown but norm-bounded. Based on Lyapunov stability theory and decentralized control theory of large-scale system, the design schema of decentralized parallel distributed compensation （DPDC） fuzzy controllers to ensure the asymptotic stability of the whole fuzzy large-scale system is proposed. The existence conditions for these controllers take the forms of LMIs. Finally a numerical simulation example is given to show the utility of the method proposed.

IoT Smart Devices Risk Assessment Model Using Fuzzy Logic and PSO

Increasing Internet of Things(IoT)device connectivity makes botnet attacks more dangerous,carrying catastrophic hazards.As IoT botnets evolve,their dynamic and multifaceted nature hampers conventional detection methods.This paper proposes a risk assessment framework based on fuzzy logic and Particle Swarm Optimization(PSO)to address the risks associated with IoT botnets.Fuzzy logic addresses IoT threat uncertainties and ambiguities methodically.Fuzzy component settings are optimized using PSO to improve accuracy.The methodology allows for more complex thinking by transitioning from binary to continuous assessment.Instead of expert inputs,PSO data-driven tunes rules and membership functions.This study presents a complete IoT botnet risk assessment system.The methodology helps security teams allocate resources by categorizing threats as high,medium,or low severity.This study shows how CICIoT2023 can assess cyber risks.Our research has implications beyond detection,as it provides a proactive approach to risk management and promotes the development of more secure IoT environments.

Decentralized state observer scheme for uncertain time-delay T-S fuzzy interconnected systems

This paper focuses on a class of T-S fuzzy interconnected systems with time delays and time-varying parameter uncertainties. Observer-based output feedback decentralized controller is designed such that the closed-loop interconnected system is asymptotically stable in the Lyapunov sense in probability for all admissible uncertainties and time delays. Sufficient conditions for robustly asymptotically stability of the systems are given in terms of a set of linear matrix inequalities （LMIs）.

Stability Analysis of Continuous-Time Fuzzy Large-Scale System

A continuous-time fuzzy large-scale system F consists of some interconnected Takagi-Sugeno fuzzy subsystems. Two sufficient conditions for the asymptotic stability of this system (namely, theorem 1 and theorem 2) are derived via a multiple Lyapunov function approach. In theorem 1, the information of membership functions of fuzzy rules should be known in order to analyze the stability of F. But in general this information is not easy to be acquired for their time-varying property. So theorem 2 is provided to judge the asymptotic stability of F, based on which there is no need to know the information of membership functions in stability analysis. Finally, a numerical example is given to show the utility of the method proposed in this paper.

Decentralized Control Based on FNNSMC for Interconnected Uncertain Nonlinear Systems

A new type controller, fuzzy neural networks sliding mode controller (FNNSMC), is developed for a class of large scale systems with unknown bounds of high order interconnections and disturbances. Although sliding mode control is simple and insensitive to uncertainties and disturbances, there are two main problems in the sliding mode controller (SMC): control input chattering and the assumption of known bounds of uncertainties and disturbances. The FNNSMC, which incorporates the fuzzy neural networks (FNN) and the SMC, can eliminate the chattering by using the continuous output of the FNN to replace the discontinuous sign term in the SMC. The bounds of uncertainties and disturbances are also not required in the FNNSMC design. The simulation results show that the FNNSMC has more robustness than the SMC.

Robust non-fragile control for discrete-delay nonlinear large-scale systems

Time-delays,due to the information transmission between subsystems,naturally exist in large-scale systems and the existence of the delay is frequently a source of instability. This paper considers the problems of robust non-fragile fuzzy control for a class of uncertain discrete nonlinear large-scale systems with time-delay and controller gain perturbations described by T-S fuzzy model. An equivalent T-S fuzzy model is represented for discrete-delay nonlinear large-scale systems. A sufficient condition for the existence of such non-fragile controllers is further derived via the Lyapunov function and the linear matrix inequality( LMI) approach. Simulation results demonstrate the feasibility and the effectiveness of the proposed design and the proper stabilization of the system in spite of controller gain variations and uncertainties.

Research of Personnel Operational Ability Evaluation of Large-scale Complex Equipment

The level of personnel operation ability determines the expected effectiveness of large-scale complex equipment. Firstly, this paper constructs the personnel operational ability evaluation index system and analyzes the data source of index. Secondly, the weight of index is determined and the fuzzy comprehensive evaluation model is proposed. Finally, results of instance analysis show that the evaluation model is feasible and effective.

粤港澳大湾区轨道交通互联互通标准判识研究

互联互通是我国轨道交通一体化融合和高质量发展的现实需求。本文对粤港澳大湾区多层次轨道交通体系进行了梳理,重新诠释了互联互通的概念,对不同层次轨道交通适宜达到的互联互通等级及可行性进行分析,针对是否采用直通跨线运营模式实现互联互通问题进行了研究。结果表明:(1)按照便利程度将互联互通分为直通跨线运营模式、付费区换乘(地铁换乘模式)、非付费区换乘(国铁换乘模式)和有物理隔离(自行换乘模式)4个等级;(2)高速铁路与城市轨道交通宜做好换乘接驳;城际铁路(区域通道型)与高速铁路间,都市圈城际铁路与市域(郊)铁路间宜直通跨线运营;(3)选取技术标准、运输需求、运营条件和经济效益4类评价指标,分析了各指标的评价函数,构建了基于遗传算法的模糊综合评价模型,通过采用遗传算法对指标权重进行优化确定,解决了二元评价指标的权重依赖问题;(4)以大湾区城际铁路为例,对互联互通直通跨线运营的线路进行了实证研究,计算结果与实际工程设计方案一致。

基于模糊控制的主动抗侧倾液压互联悬架研究

随着车速提高,车辆侧翻的风险随之增加,因此车辆的抗侧倾性能愈发受到人们的重视。液压互联悬架(HIS)能有效提升车辆的侧倾刚度且几乎不影响车辆的平顺性。根据所研究的主动液压互联悬架,设计了一个以侧倾角和侧倾角加速度作为输入的模糊控制器,直线行驶时控制器几乎不工作,此时车辆等同于被动HIS,两者平顺性近似相同;高速转向时通过控制电机推动调节油缸的活塞杆运动,产生主动的抗侧倾力矩提高车辆的操稳性能。搭建了主动抗侧倾HIS实验台架,通过台架实验验证了主动HIS模型的正确性。对试验车辆底盘进行主动抗侧倾HIS测试系统改装,进行蛇形和双移线试验,并利用MATLAB/Simulink进行相应仿真,比较分析被动HIS车辆和主动HIS车辆的车身侧倾角峰值。结果表明,与被动HIS相比,主动HIS能有效提高车辆的抗侧倾性能。

H_∞tracking design for a class of decentralized nonlinear systems via fuzzy adaptive observer

A novel H∞ tracking-based decentralized indirect adaptive output feedback fuzzy controller for a class of uncertain large-scale nonlinear systems is developed. By virtue of the proper filtering of the observation error dynamics, the observer-based decentralized indirect adaptive fuzzy control scheme is presented for a class of large-scale nonlinear systems using the combination of H∞ tracking technique, a fuzzy adaptive observer and fuzzy inference systems. The output feedback and adaptation mechanisms are both robust and implementable indeed owing to their freedom from the unavailable observation error vector. All the signals of the closed-loop largescale system are guaranteed to stay uniformly bounded and the output errors take on H∞ tracking performance. Simulation results substantiate the effectiveness of the proposed scheme.

Decentralised dynamic high-gain scaling-based output-feedback control of large-scale non-linear interconnected systems with delays

A general class of non-linear large-scale interconnected systems is considered,wherein each subsystem is comprised of a nominal part in a general strict-feedback-like structure and a set of appended dynamics.Parametric and functional uncertainties and time delays are allowed throughout the overall system structure including the nominal strictfeedback-like parts and appended dynamics of each subsystem as well as the non-linear subsystem interconnections.The controller design is based on the dual dynamic highgain scaling technique and provides a robust adaptive delay-independent globally stabilising decentralised output-feedback controller.The disturbance attenuation properties of the proposed output-feedback decentralised controller to an exogenous disturbance input are also analysed and specific conditions under which properties such as Input-toOutput-practical-Stability and asymptotic stabilisation are attained are also discussed.

Robust decentralized adaptive output feedback fuzzy controller design and application to AHS

A novel decentralized indirect adaptive output feedback fuzzy controller is developed for a class of large-scale uncertain nonlinear systems using error filtering.By the properly filtering of the observation error dynamics,the strictly positive-real condition is guaranteed to hold such that the proposed output feedback and adaptation mechanisms are practicable in practice owing to the fact that its implementation does not require the observation error vector itself any more,which corrects the impracticable schemes in the previous literature involved.The presented control algorithm can ensure that all the signals of the closed-loop large-scale system keep uniformly ultimately bounded and that the tracking error converges to zero asymptotically.The decentralized output feedback fuzzy controller can be applied to address the longitudinal control problem of a string of vehicles within an automated highway system（AHS） and the effectiveness of the design procedure is supported by simulation results.

液压互联悬架电磁平衡阀控制研究

液压互联悬架(hydraulically interconnected suspension,HIS)系统油缸内泄会直接影响其动态性能,为保证HIS系统的抗侧倾性能,文章提出一种基于电磁阀平衡两侧油路油压的解决方法,并对其控制策略进行分析。首先建立HIS模型,分析油路压力差对电磁阀平衡时间的影响,并进行实验验证;然后采用模糊控制方法实现对电磁阀开闭控制,通过MATLAB/Simulink对车辆行驶状态仿真,验证所提出的控制策略的有效性;最后进行实车试验与仿真结果分析。结果表明,该文提出的电磁平衡阀控制方法能有效平衡油缸内泄造成的两侧油路油压差。

Decomposition Based Fuzzy Model Predictive Control Approaches for Interconnected Nonlinear Systems

This paper proposes fuzzy model predictive control(FMPC)strategies for nonlinear interconnected systems based mainly on a system decomposition approach.First,the Takagi-Sugeno(TS)fuzzy model is formulated in such a way to describe the behavior of the nonlinear system.Based on that description,a fuzzy model predictive control is determined.The system under consideration is decomposed into several subsystems.For each subsystem,the main idea consists of the decomposition of the control action into two parts:The decentralized part contains the parameters of the subsystem and the centralized part contains the elements of other subsystems.According to such decomposition,two strategies are defined aiming to circumvent the problems caused by interconnection bet ween subsystems.The feasibility and efficiency of the proposed method are illustrated through numerical examples.