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.     

Double emulsion (W/O/W) gel stabilised by polyglycerol polyricinoleate and calcium caseinate as mangiferin carrier: insights on formulation and stability properties

Mangiferin (MGF) is a phenolic compound isolated from mango, but its poor solubility significantly limits its use. In this study, MGF was embedded into the inner aqueous phase of W₁/O/W₂ emulsions. Firstly, the dissolution method of MGF was determined. MGF remained stable in solution with pH 13 at 30 min, and its solubility reached 10 mg mL⁻¹. When the pH of MGF solutions was adjusted from pH 13 to pH 6, MGF did not immediately crystallise, providing sufficient time to construct the MGF-loaded W₁/O/W₂ emulsions. Subsequently, the MGF-loaded W₁/O/W₂ emulsions were constructed using polyglycerol polyricinoleate (PGPR) and calcium caseinate (CAS). The formation and stability of the W₁/O/W₂ emulsions were investigated. The MGF-loaded W₁/O/W₂ emulsions stabilised with 1% PGPR and 1% – 3% CAS exhibited a low viscosity, limited loading capacity, and poor stability. Conversely, the MGF-loaded W₁/O/W₂ emulsions stabilised by 3%PGPR–3%CAS exhibited optimal loading capacity (encapsulation efficiency = 95.31% and loading efficiency = 0.91%) and stability, which was attributed to the fact that high viscosity and gel state retarded the migration of inner aqueous phase. These results indicated that the W₁/O/W₂ emulsions stabilised by PGPR and CAS may be a potential alternative for encapsulating mangiferin.     

Machine fault diagnosis with small sample based on variational information constrained generative adversarial network

In actual engineering scenarios, limited fault data leads to insufficient model training and over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic models. To solve the problem, this paper proposes a variational information constrained generative adversarial network (VICGAN) for effective machine fault diagnosis. Firstly, by incorporating the encoder into the discriminator to map the deep features, an improved generative adversarial network with stronger data synthesis capability is established. Secondly, to promote the stable training of the model and guarantee better convergence, a variational information constraint technique is utilized, which constrains the input signals and deep features of the discriminator using the information bottleneck method. In addition, a representation matching module is added to impose restrictions on the generator, avoiding the mode collapse problem and boosting the sample diversity. Two rolling bearing datasets are utilized to verify the effectiveness and stability of the presented network, which demonstrates that the presented network has an admirable ability in processing fault diagnosis with few samples, and performs better than state-of-the-art approaches.     

基于Abaqus的双裂纹不同间距对裂纹扩展速率的研究

扩展有限元法是近年经过大量运用的,在传统有限元的范围中求解不连续问题一种有效计算方法,它是基于单位分解的思想,在计算不连续问题时加入跳跃函数。以ABAQUS为平台,基于扩展有限元方法 (XFEM),以含双穿透型裂纹的有限宽板受横向拉伸载荷为力学模型,建立相应的裂纹尖端应力的有限元模型,研究焊接接头区域不同间距双裂纹相互作用对裂纹扩展速率的影响。结果表明:双裂纹间距的的大小并没有对裂纹的扩展速率产生影响。     

NiFe layered double hydroxide as an efficient bifunctional catalyst for electrosynthesis of hydrogen peroxide and oxygen

Two electron oxygen reduction reaction to produce hydrogen peroxide (H₂O₂) is a promising alternative technique to the multistep and high energy consumption anthraquinone process. Herein, Ni–Fe layered double hydroxide (NiFe-LDH) has been firstly demonstrated as an efficient bifunctional catalyst to prepare H₂O₂ by electrochemical oxygen reduction (2e^? ORR) and oxygen evolution reaction (OER). Significantly, the NiFe-LDH catalyst possesses a high faraday efficiency of 88.75% for H₂O₂ preparation in alkaline media. Moreover, the NiFe-LDH catalyst exhibits excellent OER electrocatalytic property with small overpotential of 210 mV at 10 mA cm^?2 and high stability in 1 M KOH solution. On this basis, a new reactor has been designed to electrolyze oxygen and generate hydrogen peroxide. Under the ultra-low cell voltage of 1 V, the H₂O₂ yield reaches to 47.62 mmol g_cat^?1 h^?1. In order to evaluate the application potential of the bifunctional NiFe-LDH catalyst for H₂O₂ preparation, a 1.5 V dry battery has been used as the power supply, and the output of H₂O₂ reaches to 83.90 mmol g_cat^?1 h^?1. The excellent electrocatalytic properties of 2e^? ORR and OER make NiFe-LDH a promising bifunctional electrocatalyst for future commercialization. Moreover, the well-designed 2e^? ORR-OER reactor provides a new strategy for portable production of H₂O₂.     

Topology optimization of flexure hinges with a prescribed compliance matrix based on the adaptive spring model and stress constraint

This paper focuses on the configuration design of flexure hinges with a prescribed compliance matrix and preset rotational center position. A new method for the topology optimization of flexure hinges is proposed based on the adaptive spring model and stress constraint. The hinge optimization model is formulated by maximizing the bending displacement with a spring while optimizing the compliance matrix to a prescribed value. To avoid numerical instability, an artificial spring is used as an auxiliary calculation, and a new strategy is developed for adaptively adjusting the spring stiffness according to the prescribed compliance matrix. The maximum stress of flexure hinge is limited by using a normalized P-norm of the effective von Mises stress, and a position constraint of rotational center is proposed to predetermine the position of the rotational center. In addition, to reduce the error of the stress measurement, a simple but effective filtering method is presented to obtain a complete black-and-white design. Numerical examples are used to verify the proposed method. Topology results show that the obtained flexure hinges have the prescribed compliance matrix and preset rotational center position while also meeting the stress requirements.     

Mathematical representation of radiality constraint in distribution system reconfiguration problem

Distribution systems are most commonly operated in a radial configuration for a number of reasons. In order to impose radiality constraint in the optimal network reconfiguration problem, an efficient algorithm is introduced in this paper based on graph theory. The paper shows that the normally followed methods of imposing radiality constraint within a mixed-integer programming formulation of the reconfiguration problem may not be sufficient. The minimum-loss network reconfiguration problem is formulated using different ways to impose radiality constraint. It is shown, through simulations, that the formulated problem using the proposed method for representing radiality constraint can be solved more efficiently, as opposed to the previously proposed formulations. This results in up to 30% reduction in CPU time for the test systems used in this study.     

川西彭州地区雷口坡组潮坪相薄储层辨识机理研究

川西彭州地区三叠系雷口坡组雷四上亚段潮坪相薄储层识别难度极大。围绕如何从复合地震强反射中区分并识别上、下两套储层面临的地球物理难题,采用先“分”后“合”的研究思路,基于实际地层结构及不同储层叠加样式建立正演模型,利用全波场波动方程正演模拟技术,剖析了不同主频条件下薄储层的地震响应特征,通过波形差异化分析,从复合地震响应中“剥离”出了两套储层所引起的地震响应特征及变化规律,明确了两套储层在不同频带下的地震识别标志和识别方法,为该区强反射界面干扰下两套薄互层储层辨识机理分析及精准预测奠定了基础。基于不同频带下薄储层辨识机理的分析结果,定性预测了薄储层平面展布,提出了深层潮坪相薄储层识别和预测难题的解决方案,为该区地震资料品质评价、面向薄储层的地震采集技术设计、地震资料处理及薄储层预测提供了依据和指导。     

Event-triggered distributed receding horizon control for tracking and formation of homogeneous multi-agent systems

This paper proposes an event-triggered distributed receding horizon control (DRHC) approach for the formation and tracking problems of homogeneous multi-agent systems. For each agent, an event-triggering condition, based on assumed predictive information of the neighbours, is derived from stability analysis. Considering the uncertain deviation between the assumed and true predictive information, we design a time-varying compatibility constraint for the individual optimization problem. In the event-triggered DRHC algorithm, each agent solves the optimization problem and communicates with its neighbours only when the event-triggering condition is satisfied, so the communication and computation burden are reduced. Moreover, guarantees for the recursive feasibility and asymptotic stability of the overall system are proved. A simulation example is provided to illustrate effectiveness of the proposed approach.     

Three‐dimensional color prediction modeling of single‐ and double‐layered woven fabrics

In this research, the three‐dimensional structural and colorimetric modeling of three‐dimensional woven fabrics was conducted for accurate color predictions. One‐hundred forty single‐ and double‐layered woven samples in a wide range of colors were produced. With the consideration of their three‐dimensional structural parameters, three‐dimensional color prediction models, K/S‐, R‐, and L*a*b*‐based models, were developed through the optimization of previous two‐dimensional models which have been reported to be the three most accurate models for single‐layered woven structures. The accuracy of the new three‐dimensional models was evaluated by calculating the color differences ΔL*, ΔC*, Δh°, and ΔE_CMC(2:1) between the measured and the predicted colors of the samples, and then the error values were compared to those of the two‐dimensional models. As a result, there has been an overall improvement in color predictions of all models with a decrease in ΔE_CMC(2:1) from 10.30 to 5.25 units on average after the three‐dimensional modeling.