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.     

An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition

Tracking control of oxygen excess ratio (OER) is crucial for dynamic performance and operating efficiency of the proton exchange membrane fuel cell (PEMFC). OER tracking errors and overshoots under dynamic load limit the PEMFC output power performance, and also could lead oxygen starvation which seriously affect the life of PEMFC. To solve this problem, an adaptive sliding mode observer based near-optimal OER tracking control approach is proposed in this paper. According to real time load demand, a dynamic OER optimization strategy is designed to obtain an optimal OER. A nonlinear system model based near-optimal controller is designed to minimize the OER tracking error under variable operation condition of PEMFC. An adaptive sliding mode observer is utilized to estimate the uncertain parameters of the PEMFC air supply system and update parameters in near-optimal controller. The proposed control approach is implemented in OER tracking experiments based on air supply system of a 5 kW PEMFC test platform. The experiment results are analyzed and demonstrate the efficacy of the proposed control approach under load changes, external disturbances and parameter uncertainties of PEFMC system.     

基于概率法的电力系统安全分析

为应对电力系统安全分析中的停机问题，基于概率法的方式，将常用的确定停机计算与加入了概率法的概率停机进行比较，研究了二者的区别与其在长期投资方向的不同。在进行电力系统停机分析时，通常会分别从确定停机与概率停机的角度出发，对其应急状态下的潮流进行计算。但前者的方法可能导致极低概率的停机事件被忽略，进而影响长期的资金投资。通过加入概率法的计算，使得对单个停机事件的判定由其具体的频率来确定，增加了系统运行的稳定性。     

基于软件校准的短波发射机功率控制系统设计

短波发射机功率稳定一直是通信领域致力改善的重点问题,短波发射机功率不稳定会直接影响无线电通信质量,造成通信失真、表达不清晰等问题。针对上述问题,基于软件校准设计短波发射机功率控制系统。该系统借鉴MVC设计模式搭建系统数据库层、业务逻辑层、控制层以及界面显示层基础框架；将功率计与短波发射机相连,实时采集工作状态下的短波发射机功率数据,通过信号处理器实施处理后并存储,借鉴传输元件,将数据发送到控制器,通过控制器校准短波发射机功率与预期之间的偏差,以偏差量为输入,利用改进PID运算得出控制量,生成控制命令,通过输入输出信号接口板输出命令,控制驱动装置调节短波发射机运行参数,实现功率控制。结果表明：与 控制系统、自动调谐系统应用相比较,在所设计系统应用控制下,100s内短波发射机的功率变化曲线与预期曲线之间的拟合优度指数更大,更接近1,优于对比系统,说明相比于对比系统。本系统控制表现更好,更能维持短波发射机功率稳定,达到了研究目标。     

Shared human–robot path following control of an unmanned ground vehicle

This paper considers the shared path following control of an unmanned ground vehicle by a single person. A passive measure of human intent is used to blend the human and machine inputs in a mixed initiative approach. The blending law is combined with saturated super-twisting sliding mode speed and heading controllers, so that exogenous disturbances can be counteracted via equivalent control. It is proven that when the proposed blending law is used, the combined control signals from both the human and automatic controller respect the actuator magnitude constraints of the machine. To demonstrate the approach, shared control experiments are performed using an unmanned ground vehicle, which follows a lawn mower pattern shaped path.     

Electrochemical Quantification of Neurotransmitters in Single Live Cell Vesicles Shows Exocytosis is Predominantly Partial

Exocytosis plays an essential role in the communication between cells in the nervous system. Understanding the regulation of neurotransmitter release during exocytosis and the amount of neurotransmitter content that is stored in vesicles is of importance, as it provides fundamental insights to understand how the brain works and how neurons elicit a certain behavior. In this minireview, we summarize recent progress in amperometric measurements for monitoring exocytosis in single cells and electrochemical cytometry measurements of vesicular neurotransmitter content in individual vesicles. Important steps have increased our understanding of the different mechanisms of exocytosis. Increasing evidence is firmly establishing that partial release is the primary mechanism of release in multiple cell types.     

Thermo-economic investigation on the hydrogen production through the stored solar energy in a salinity gradient solar pond: A comparative study by employing APC and ORC with zeotropic mixture

In this paper, a salinity gradient solar pond (SGSP) is used to harness the solar energy for hydrogen production through two cycles. The first cycle includes an absorption power cycle (APC), a proton exchange membrane (PEM) electrolyzer, and a thermoelectric generator (TEG) unit; in the second one, an organic Rankine cycle (ORC) with the zeotropic mixture is used instead of APC. The cycles are analyzed through the thermoeconomic vantage point to discover the effect of key decision variables on the cycles’ performance. Finally, NSGA-II is used to optimize both cycles. The results indicate that employing ORC with zeotropic mixture leads to a better performance in comparison to utilizing APC. For the base mode, unit cost product (UCP), exergy, and energy efficiency when APC is employed are 59.9 $/GJ, 23.73%, and 3.84%, respectively. These amounts are 47.27 $/GJ, 29.48%, and 5.86% if ORC with the zeotropic mixture is utilized. The APC and ORC generators have the highest exergy destruction rate which is equal to 6.18 and 10.91 kW. In both cycles, the highest investment cost is related to the turbine and is 0.8275 $/h and 0.976 $/h for the first and second cycles, respectively. In the optimum state the energy efficiency, exergy efficiency, UCP, and H₂ production rate of the system enhances 42.44%, 27.54%,15.95%, and 38.24% when ORC with the zeotropic mixture is used. The maximum H₂ production is 0.47 kg/h, and is obtained when the mass fraction of R142b, LCZ temperature, pumps pressure ratio, generator bubble point temperature are 0.603, 364.35 K, 2.12, 337.67 K, respectively.     

超宽带大功率合成器设计北大核心CSCD

在80 MHz~1 GHz频段,单个功率管输出功率能达到100 W以上,为研制输出功率400 W的功率放大器,文中设计了四路功率合成器。该合成器需要实现功率容量大、工作频带宽、体积小的设计目标。在功率容量方面,文中采用悬置带状线结构,其功率容量远远大于微带线结构;在工作频带方面,采用切比雪夫九节阻抗变换器,将工作带宽拓宽为80 MHz~1 GHz;在体积方面,文中合成器的功率合成部分采用Y型节级联实现四路功率合成,阻抗变换部分采用切比雪夫阻抗变换器进行阻抗变换,该结构相较于磁环巴伦功率合成器,不但具有损耗小、平坦度高的优点,而且通过将阻抗变换器设计成曲折的形状,进一步缩小了合成器体积。仿真与实测结果显示该合成器在80 MHz~1 GHz范围内还具有较高的平坦度,合成效率可达90%以上。     

Neural network-based flight control systems: Present and future

As the first review in this field, this paper presents an in-depth mathematical view of Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural networks. The rapid evolution of IFCSs in the last two decades in both the methodological and technical aspects necessitates a comprehensive view of them to better demonstrate the current stage and the crucial remaining steps towards developing a truly intelligent flight management unit. To this end, in this paper, we will provide a detailed mathematical view of Neural Network (NN)-based flight control systems and the challenging problems that still remain. The paper will cover both the model-based and model-free IFCSs. The model-based methods consist of the basic feedback error learning scheme, the pseudocontrol strategy, and the neural backstepping method. Besides, different approaches to analyze the closed-loop stability in IFCSs, their requirements, and their limitations will be discussed in detail. Various supplementary features, which can be integrated with a basic IFCS such as the fault-tolerance capability, the consideration of system constraints, and the combination of NNs with other robust and adaptive elements like disturbance observers, would be covered, as well. On the other hand, concerning model-free flight controllers, both the indirect and direct adaptive control systems including indirect adaptive control using NN-based system identification, the approximate dynamic programming using NN, and the reinforcement learning-based adaptive optimal control will be carefully addressed. Finally, by demonstrating a well-organized view of the current stage in the development of IFCSs, the challenging issues, which are critical to be addressed in the future, are thoroughly identified. As a result, this paper can be considered as a comprehensive road map for all researchers interested in the design and development of intelligent control systems, particularly in the field of aerospace applications.