Robust optimal operation of continuous catalytic reforming process under feedstock uncertainty

The continuous catalytic regenerative (CCR) reforming process is one of the most significant sources of hydrogen production in the petroleum refining process. However, the fluctuations in feedstock composition and flow rate could significantly affect both product distribution and energy consumption. In this study, a robust deviation criterion based multi-objective optimization approach is proposed to perform the optimal operation of CCR reformer under feedstock uncertainty, with simultaneous maximization of product yields and minimization of energy consumption. Minimax approach is adopted to handle these uncertain objectives, and the Latin hypercube sampling method is then used to calculate these robust deviation criteria. Multi-objective surrogate-based optimization methods are next introduced to effectively solve the robust operational problem with high computational cost. The level diagram method is finally utilized to assist in multi-criteria decision-making. Two robust operational optimization problems with different objectives are solved to demonstrate the effectiveness of the proposed method for robust optimal operation of the CCR reforming process under feedstock uncertainty.     

Finite-time adaptive fuzzy control for a class of output constrained nonlinear systems with dead-zone

The article investigates the finite-time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead-zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite-time control theory, a novel adaptive state-feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite-time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed-loop are proved to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.     

Establishment of a color tolerance for yarn-dyed fabrics from different color-depth yarns

Yarn-dyed fabric is often woven from warp and weft yarns in the same color depth to ensure a uniform color appearance. The difference in color depth between warp and weft tends to result in the uneven color of the yarn-dyed fabric. This article aims to establish a color tolerance for yarn-dyed fabric that can be woven with a qualified color appearance but from the warp and weft yarns in different color depths. A total of 27 yarn-dyed fabric samples in three color series (red, yellow, and blue) were evaluated by using the yarn-dyed fabric from warp and weft yarns in the same color depth of 2% (on weight of fabric, owf) as the standard. Visual assessment and instrumental measurement of color were carried out to establish the color tolerance ellipse that was defined as CMC (Color Measurement Committee) color differences (2:1) of no more than 1.00. It was found that the color strengths (K/S) and color differences (ΔE_CMC(2:1)) of these fabric samples for each color series had linear relationships with the color depths of warp and weft yarns. The color tolerance ellipses indicated that, even though the warp and weft yarns had an apparent color difference, they could be woven in fabrics with relatively uniform color appearance and meet the requirements for yarn-dyed fabric. This work provided valuable insight into the production of qualified yarn-dyed fabrics from unqualified dyed yarns.     

Stress wave propagation in adhesively bonded functionally graded cylinders: an improved model

This study presents an improved mathematical model to analyse the stress wave propagation in adhesively bonded functionally graded (FG) circular cylinders (butt joint) under an axial impulsive load. The volume fractions of the material constituents in the upper and lower cylinders were functionally tailored through the thickness of each cylinder using a power-law. The effective material properties of both cylinders, which are made of aluminum (Al) and silicon carbide (SiC), at any point were predicted by using the Mori–Tanaka homogenization scheme. In this improved model, the governing equations of the wave propagation include the spatial derivatives of local mechanical properties and were discretized by means of the finite difference method. The influence of these spatial derivatives and the compositional gradient exponent on the displacement and stress distributions of the joint was investigated. The material composition variations of both cylinders affected the displacement and stress fields whereas the compositional gradient exponent had a minor effect. The stress concentrations were alleviated in time, the displacement and stress distributions/variations around/along the upper and lower cylinder-adhesive interfaces were significantly affected by the adhesive layer. The spatial derivatives also affected the temporal histories of the displacement and stress components evaluated at the selected critical points of the upper cylinder, adhesive layer and lower cylinder. The consideration of the spatial local material derivatives provided a more accurate mathematical model of wave propagations through the graded layered structures.     

Understanding the asymmetric perceptions of smartphone security from security feature perspective: A comparative study

Smartphones are being used and relied on by people more than ever before. The open connectivity brings with it great convenience and leads to a variety of risks that cannot be overlooked. Smartphone vendors, security policy designers, and security application providers have put a variety of practical efforts to secure smartphones, and researchers have conducted extensive research on threat sources, security techniques, and user security behaviors. Regrettably, smartphone users do not pay enough attention to mobile security, making many efforts futile. This study identifies this gap between technology affordance and user requirements, and attempts to investigate the asymmetric perceptions toward security features between developers and users, between users and users, as well as between different security features. These asymmetric perceptions include perceptions of quality, perceptions of importance, and perceptions of satisfaction. After scoping the range of smartphone security features, this study conducts an improved Kano-based method and exhaustively analyzes the 245 collected samples using correspondence analysis and importance satisfaction analysis. The 14 security features of the smartphone are divided into four Kano quality types and the perceived quality differences between developers and users are compared. Correspondence analysis is utilized to capture the relationship between the perceived importance of security features across different groups of respondents, and results of importance-satisfaction analysis provide the basis for the developmental path and resource reallocation strategy of security features. This article offers new insights for researchers as well as practitioners of smartphone security.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

Integral barrier Lyapunov function-based adaptive fuzzy output feedback control for nonlinear delayed systems with time-varying full-state constraints

In this article, an adaptive fuzzy output feedback control method is presented for nonlinear time-delay systems with time-varying full state constraints and input saturation. To overcome the problem of time-varying constraints, the integral barrier Lyapunov functions (IBLFs) integrating with dynamic surface control (DSC) are applied for the first time to keep the state from violating constraints. The effects of unknown time delays can be removed by using designed Lyapunov-Krasovskii functions (LKFs). An auxiliary design system is introduced to solve the problem of input saturation. The unknown nonlinear functions are approximated by the fuzzy logic systems (FLS), and the unmeasured states are estimated by a designed fuzzy observer. The novel controller can guarantee that all signals remain semiglobally uniformly ultimately bounded and satisfactory tracking performance is achieved. Finally, two simulation examples illustrate the effectiveness of the presented control methods.     

Revisiting rock classification to estimate rock mass properties

This paper presents the results of ongoing research carried out by the author exploring methods to provide a more robust estimate of rock mass properties specifically for use in tunnel design. Data from various large-scale rock mass failures are introduced, including coal pillars. The damage-initiation,spalling-limit approach is compared to the coal pillar database. New comparisons of estimating the geological strength index(GSI) and relationships to estimate the Hoeke Brown failure criterion parameters, mb, s and a, are presented.     

基于残差决策的自动飞行控制系统远程实时故障诊断

针对自动飞行控制系统结构复杂、关联部件众多,发生故障时诊断时间长,从而影响飞机运行效率的问题,提出一种基于飞机通信寻址报告系统(ACARS)的远程实时故障诊断方案。首先,分析自动飞行控制系统的故障特点,设计搭建检测滤波器;然后,利用ACARS数据链实时发送的自动飞行控制系统的关键信息进行相关部件的残差计算,并根据残差决策算法进行故障诊断及定位;最后,针对不同故障部件残差间的差异大、决策门限无法统一的缺点,提出基于二次差值的残差决策改进算法,减缓了检测对象的整体变化趋势,降低了随机噪声和干扰的影响,避免了将瞬态故障诊断为系统故障的情况。实验仿真结果表明,基于二次差值的改进残差决策算法避免了多决策门限的复杂性,在采样时间为0.1 s的情况下,故障检测所需时间大约为2 s,故障检测时间大幅降低,有效故障检测率大于90%。     

Some picture fuzzy Bonferroni mean operators with their application to multicriteria decision making

In this paper, we extend the Bonferroni mean (BM) operator with the picture fuzzy numbers (PFNs) to propose novel picture fuzzy aggregation operators and demonstrate their application to multicriteria decision making (MCDM). On the basis of the algebraic operational rules of PFNs and BM, we introduce some aggregation operators: the picture fuzzy Bonferroni mean, the picture fuzzy normalized weighted Bonferroni mean, and the picture fuzzy ordered weighted Bonferroni mean. Then, a new picture fuzzy MCDM method is proposed with the help of the proposed operators. Lastly, a practical application of proposed model is given to verify the developed model and related results of the proposed model is compared with the results of the existing models to indicate its applicability.