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.     

Ion migration behavior and its interaction with sintering environment in cation conductor during flash sintering

Flash sintering has been reported in various ceramics. Nevertheless, anion and cation conductors exhibit different flash-sintering behaviors, and the interaction mechanism between the conductive species and the sintering environment has remained unclear. Herein, we report the flash-sintering phenomena of a typical cation conductor, Na₃Zr₂(SiO₄)₂(PO₄) with anode region surrounded by air and NaNO₃ environments. The results prove that the ionic behavior and joule heating distribution can be controlled by changing the electrode environment. Four possible scenarios describing the ion migration behavior and interaction with the environment are proposed for providing a guidance for controlling the ion interaction behavior during flash sintering.     

Motion trajectory prediction model of hydrogen leak and diffusion in a stable thermally-stratified environment

The motion trajectory of hydrogen leakage is an essential safe issue for the application of hydrogen energy. A dimensionless fast-running motion trajectory prediction model is proposed to predict the dispersion characteristics of the buoyant jet of hydrogen leakage for the accident. The impact of different leakage angles, leakage velocity and thermal stratification of ambient air on hydrogen leakage behavior was analyzed. The new developed model was verified by experimental results in literatures. Leakage hydrogen can flow upwards freely in a uniform environment. However, it shows an oscillating trajectory at a certain height in a thermally stratified environment, which is so called “locking phenomenon”. The trajectory of hydrogen leakage is upward and hydrogen gathers at the top of the space to form stratification in a uniform environment, while the hydrogen leakage shows an oscillating trajectory at a certain height in a thermal stratification environment. With the increase of Froude number Fr, it shows that the stable height and maximum height of the leakage airflow have a trend of rising first and then falling in a thermally stratified environment. The findings are expected to give guidance in real-world situations, for example, a larger Fr value and a larger temperature gradient can lead to a decrease in the stable height in the thermally stratified environment. It is found that the fitting of the stable height with different temperature gradients satisfies the power function relationship. This work is expected to be helpful for reducing hydrogen leakage accumulation and explosion risk.     

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.     

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.     

当代室内环境生态评估与生态审美价值观的传播

价值观的传播是一个缓慢的过程,在当前工业文明向生态文明过渡的时期,如何有效地提升民众的生态意识是值得探讨的问题。以生态审美意识传播为切入点,通过了解国内外主流的室内环境生态评估指标体系的前后变化,总结当前室内环境生态评估的变化趋势及其主要特征;从指标体系的变化中分析生态审美价值观的渗透方式,探讨当代室内环境生态评估对生态审美价值观传播的促进作用。最后,通过实验设定针对室内传统营造技艺应用的评估工具,并且在评估工具的使用过程中展示传播的模式与效用,通过评估反馈再一次验证室内环境生态评估对生态审美价值观的正向传播作用。     

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.     

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.     

Regulation of sensory nerve conduction velocity of human bodies responding to annual temperature variations in natural environments

The extensive research interests in environmental temperature can be linked to human productivity / performance as well as comfort and health; while the mechanisms of physiological indices responding to temperature variations remain incompletely understood. This study adopted a physiological sensory nerve conduction velocity (SCV) as a temperature‐sensitive biomarker to explore the thermoregulatory mechanisms of human responding to annual temperatures. The measurements of subjects’ SCV (over 600 samples) were conducted in a naturally ventilated environment over all four seasons. The results showed a positive correlation between SCV and annual temperatures and a Boltzmann model was adopted to depict the S‐shaped trend of SCV with operative temperatures from 5°C to 40°C. The SCV increased linearly with operative temperatures from 14.28°C to 20.5°C and responded sensitively for 10.19°C‐24.59°C, while tended to be stable beyond that. The subjects’ thermal sensations were linearly related to SCV, elaborating the relation between human physiological regulations and subjective thermal perception variations. The findings reveal the body SCV regulatory characteristics in different operative temperature intervals, thereby giving a deeper insight into human autonomic thermoregulation and benefiting for built environment designs, meantime minimizing the temperature‐invoked risks to human health and well‐being.