Development of new energy management strategy for a household fuel cell/battery hybrid system

This work aims to construct an efficient and robust fuel cell/battery hybrid operating system for a household application. The ability to dispatch the power demands, sustain the state of charge (SOC) of battery, optimize the power consumption, and more importantly, ensure the durability as well as extend the lifetime of a fuel cell system is the basic requirements of the hybrid operating system. New power management strategy based on fuzzy logical combined state machine control is developed, and its effectiveness is compared with various strategies such as dynamic programming (DP), state machine control, and fuzzy logical control with simulation. Experimental results are also presented, except for DP because of difficulties in achieving real‐time implementation and much faster response to load variation. The given current from the energy management system (EMS) as a reference of the fuel cell output current is determined by filtering out various harmful signals. The new power management strategy is applied to a 1‐kW stationary fuel cell/battery hybrid system. Results show that the fuel cell hybrid system can run much smoothly with prolonged lifetime.     

Full and reduced-order H∞ filtering of Takagi–Sugeno fuzzy time-varying delay systems: Input–output approach

This article addresses the issue of delay-dependent H_∞ filtering design for TakagiŮSugeno fuzzy time-varying delay systems using the input–output approach. A three-term approximation model has been used to transform the original system into two interconnected subsystems. Since the nonquadratic Lyapunov–Krasovskii functional requires to deal with the membership function's (MF) time derivative, upper-bound inequalities have been added to the obtained conditions. Based on the scaled small gain theorem, nonquadratic Lyapunov–Krasovskii functional approach and considering the bounds of the MF time-derivative, the H_∞ full- and reduced-order filters are designed and then formulated in terms of linear matrix inequalities. Finally, illustrative examples are presented to demonstrate the validity of the proposed methods.     

Observer‐based fuzzy adaptive quantized control for uncertain nonlinear multiagent systems

This paper focuses on consensus quantized control design problem for uncertain nonlinear multiagent systems with unmeasured states. Every follower can be denoted through a system with unmeasurable states, hysteretic quantized input, and unknown nonlinearities. Fuzzy state observer and Fuzzy logic systems are employed to estimate unmeasured states and approximate unknown nonlinear functions, respectively. The hysteretic quantized input can be split into two bounded nonlinear functions to avoid chattering problem. By combining adaptive backstepping and first‐order filter signals, an observer‐based fuzzy adaptive quantized control scheme is designed for each follower. All signals exist in closed‐loop systems are semiglobally uniformly ultimately bounded, and all followers can accomplish a desired consensus results. Finally, a numerical example is employed to elaborate the effectiveness of proposed control strategy.     

Retracted: State estimation of Takagi-Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks

This article concerns the event-triggered fuzzy filter design for Takagi-Sugeno (T-S) fuzzy systems subject to deception attacks under the stochastic multiple time-varying delays. A sequence of random variables, which are mutually independent but obey the Bernoulli distribution, is introduced to account for the randomly occurring communication delays. In order to efficiently utilize limited network communication bandwidth resources, the event-triggering scheme is adopted. A fuzzy filter with the attacked input signal is presented. Moreover, due to communication delays caused by event-triggering schemes and transmission, the filter adopts non-synchronous premise variables with the system. Then, by utilizing a model transformation technique, the fuzzy systems are developed. Furthermore, using the piecewise Lyapunov functional method technique, the resulting criterion provides sufficient conditions to ensure that fuzzy systems under deception attacks are stochastically stable with an H_∞ performance. Accordingly, the conditions for the co-design of the fuzzy filter and event-triggering schemes are given. Finally, numerical simulation with the industrial process provided to verify the proposed event-triggered design.     

基于数据挖掘的开源电子资源访问行为统计模型

为了解决当前图书馆资源个性化推荐过程中存在推荐的准确率、召回率以及效率较低的问题,采用二维距离模型构建用户社区模型,用于描述访问用户与图书馆开源电子资源之间的关系,并对互联网用户需求和访问行为进行模糊规则推理.依据互联网用户属性和图书馆资源访问需求属性之间的模糊规则,建立图书馆开源电子资源访问行为统计模型,并利用该模型向用户提供个性化推荐服务.仿真结果表明,所建模型的推荐召回率高达98. 4%,推荐准确率为99. 2%,运行时间小于0. 04 s.所建模型能够为互联网用户提供准确、高效地图书馆资源个性化推荐服务.     

基于模糊综合评价的景区解说设施优化研究

目的 系统地研究景区解说设施评价体系,建立合理完善的评价方法,为景区解说设施的优化升级提供科学的理论支撑.方法 选取泉州市崇武古城的解说设施为研究对象,以SERVQUAL(服务质量)模型为基础建立解说设施满意度评价体系,借助主成分分析、模糊综合评价以及IPA分析法3种方法,探索景区解说设施满意度及其影响因素.结论 研究表明,构成景区解说设施满意度评价体系的一级指标主要为有形性(UA)、保证性(UB)、移情性(UC)、可靠性(UD),四者的权重由大到小依次为UB>UA>UD>UC;泉州崇武古城景区解说设施满意度评价结果为良好,基本达到旅游解说要求.但是解说设施的有形性方面亟待提升,在视觉效果上的满意度相对较低,影响游客对古城景区的满意度.     

基于虚拟导航线的农业机器人精确视觉导航方法

针对农田、野外环境中无人工标记情况下的导航问题，提出了一种基于虚拟导航线的农业机器人精确视觉导航方法。该方法不需要铺设导航线或者路标即可引导机器人行走直线。首先，根据需求确定需要跟踪的目标区域，之后控制机器人调整方向直到目标移至视野中央；其次，根据机器人和目标的位置确定参照目标，并依据两个目标的位置确定虚拟导航线；然后，动态更新导航线，并结合虚拟定标线和虚拟导航线确定偏移角度和偏移距离；最后，利用偏移参数构建模糊控制表，并以此实现对机器人旋转角度和行走速度的调整。实验结果表明，该算法能较为精确地实现对导航路线的识别，进而利用模糊控制策略使机器人沿直线向目标行走，且导航精度在10 cm以内。     

An evolved VIKOR method for multiple-criteria compromise ranking modeling under T-spherical fuzzy uncertainty

The development of T-spherical fuzzy (T-SF) sets in qualitative multiple-criteria choice analysis has been well investigated, but little is explored about how the VIKOR (i.e., VIšekriterijumsko KOmpromisno Rangiranje in Serbian) mechanism is generalized into intricate T-SF environments. This paper has the objective of propounding a creative T-SF VIKOR methodology for compromise ranking modeling in multiple criteria analysis. The exploitation of the T-SF configuration brings about superior information space representation in response to intricate realistic environments. However, because of the increased complexity of decision situations involving T-spherical fuzziness, treatment with the T-SF information arises a pragmatic difficulty in developing methodological approaches to T-SF VIKOR. In light of this concern, this paper unfolds an analytical framework for the T-SF VIKOR method predicated on new notions of an evolved T-SF score function and the Minkowski-type T-SF distance measure along with its special cases of the Manhattan-, Euclidean-, and Chebyshev-type distances. The aspired and despised T-SF characteristics can be identified supported by the evolved T-SF score function of T-SF performance ratings. This paper gives a new delineation of the group utility, individual regret, and joint generalized measures with the aid of the Minkowski-type T-SF distance measure relative to the aspired/despised T-SF characteristics. A synthetic mechanism is built to validate the standards of acceptable advantage and stability and yield the ultimate compromise choices for multiple criteria decision aiding. The practicality of the T-SF VIKOR methodology in down-to-earth decision situations has been well demonstrated through the selection issues of warehouse locations and advertisement strategies. Moreover, the developed approach has shown better application outcomes than the past methods did. The comparative study with parametric analysis has revealed the steadiness and effectiveness of the compromise choice results in T-SF circumstances.     

An efficient method for estimating time-dependent failure possibility by combining adaptive Kriging with adaptive truncated fuzzy simulation

Time-dependent failure possibility (TDFP) can measure the structural safety level for a time interval of interest under fuzzy uncertainty, but its calculational cost is unaffordable by using fuzzy simulation (FS) due to a required large size of FS candidate sampling pool (CSP). Although time-dependent adaptive Kriging model (T-AK) combined with FS (T-AK-FS) was presented to reduce the number of calling performance function, a large FS CSP still makes training T-AK time-consuming. To improve its efficiency, an adaptive truncated FS (ATFS) with T-AK (T-AK-ATFS) is proposed by CSP size reduction approach. By T-AK-ATFS, the largest safety hypercube in fuzzy standard space is adaptively searched, in which the samples are in safety states and can be removed from the FS CSP. Moreover, T-AK is adaptively trained to search the largest safety hypercube and estimate TDFP simultaneously. In adaptively searching process, the FS CSP is divided into several sub-CSPs, on which training T-AK is more time-saving. Overall, strategies of T-AK-ATFS include proposing ATFS to reduce the FS CSP, adaptively searching the largest safety hypercube, estimating the TDFP with the same T-AK and training T-AK in the sub-CSPs sequentially. Verified by examples, these strategies make T-AK-ATFS more efficient than existing FS and T-AK-FS.     

Memory-based dynamic event-triggered control for networked interval type-2 fuzzy systems subject to DoS attacks

In this article, the memory-based dynamic event-triggered controller design issue is investigated for networked interval type-2 (IT2) fuzzy systems under non-periodic denial-of-service (DoS) attacks. For saving limited network bandwidth, a novel memory-based dynamic event-triggered mechanism (DETM) is proposed to schedule data communication. Unlike existing event-triggered generators, the developed memory-based DETM can utilize a series of newly released signals and further save network resources by introducing interval dynamic variables. Moreover, to improve design flexibility, an IT2 fuzzy controller with freely selectable fuzzy rule number and premise membership functions (MFs) is synthesized. Then, a new switched time-delay system with imperfectly matched MFs is established under the consideration of memory-based DETM and DoS attacks simultaneously. Besides, based on the property of MFs, the boundary information of membership grades and slack matrices are introduced in the stability analysis. Furthermore, by using a piecewise Lyapunov–Krasovskii method, membership-functions-dependent criteria are deduced to ensure the asymptotic stability of built fuzzy switched systems. Finally, the effectiveness of proposed control strategies is demonstrated by simulation examples.