Recent insights in synthesis and energy storage applications of porous carbon derived from biomass waste: A review

In the last few decades, global warming, environmental pollution, and an energy shortage of fossil fuel may cause a severe economic crisis and health threats. Storage, conversion, and application of regenerable and dispersive energy would be a promising solution to release this crisis. The development of porous carbon materials from regenerated biomass are competent methods to store energy with high performance and limited environmental damages. In this regard, bio-carbon with abundant surface functional groups and an easily tunable three-dimensional porous structure may be a potential candidate as a sustainable and green carbon material. Up to now, although some literature has screened the biomass source, reaction temperature, and activator dosage during thermochemical synthesis, a comprehensive evaluation and a detailed discussion of the relationship between raw materials, preparation methods, and the structural and chemical properties of carbon materials are still lacking. Hence, in this review, we first assess the recent advancements in carbonization and activation process of biomass with different compositions and the activity performance in various energy storage applications including supercapacitors, lithium-ion batteries, and hydrogen storage, highlighting the mechanisms and open questions in current energy society. After that, the connections between preparation methods and porous carbon properties including specific surface area, pore volume, and surface chemistry are reviewed in detail. Importantly, we discuss the relationship between the pore structure of prepared porous carbon with surface functional groups, and the energy storage performance in various energy storage fields for different biomass sources and thermal conversion methods. Finally, the conclusion and prospective are concluded to give an outlook for the development of biomass carbon materials, and energy storage applications technologies. This review demonstrates significant potentials for energy applications of biomass materials, and it is expected to inspire new discoveries to promote practical applications of biomass materials in more energy storage and conversion fields.     

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.     

A robust model-free controller for a three-phase grid-connected photovoltaic system based on ultra-local model

In this paper, a robust model-free controller for a grid-connected photovoltaic (PV) system is designed. The system consists of a PV generator connected to a three-phase grid by a DC/AC converter. The control objectives of the overall system are to extract maximum power from the PV source, to control reactive power exchange and to improve the quality of the current injected into the grid. The model-free control technique is based on the use of an ultra-local model instead of the dynamic model of the overall system. The local model is continuously updated based on a numerical differentiator using only the input–output behavior of the controlled system. The model-free controller consists of a classical feedback controller and a compensator for the effects of internal parameter changes and external disturbances. Simulation results illustrate the efficiency of the controller for grid-connected PV systems.     

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.     

Energy conversion performances during biomass air gasification process under microwave irradiation

Biomass gasification technology under microwave irradiation is a new and novel method, and the energy conversion performances during the process play a guiding role in improving the energy conversion efficiencies and developing the gasification simulation models. In order to improve the energy utilization efficiency of microwave biomass gasification system, this study investigated and presented the energy conversion performances during biomass gasification process under microwave irradiation, and these were materialized through detailing (a) the energy conversion performance in the microwave heating stage, and (b) the energy conversion performance in the microwave assisted biomass gasification stage. Different forms of energies in the biomass microwave gasification process were calculated by the method given in this study based on the experimental data. The results showed that the useful energy (energy in silicon carbide (SiC), 18.73 kJ) accounted for 31.22% of the total energy input (electrical energy, 60.00 kJ) in the heating stage, and the useful energy (energy in the products, 758.55 kJ) accounted for 63.41% of the total energy input (electrical and biomass energy, 1196.28 kJ) in the gasification stage. During the whole biomass gasification process under microwave irradiation, the useful energy output (energy in the products, 758.55 kJ) accounted for 60.38% of the total energy input (electrical and biomass energy, 1256.28 kJ), and the energy in the gas (523.40 kJ) product played a dominate role in product energy (758.55 kJ). The energy loss mainly included the heat loss in the gas flow (89.20 kJ), magnetron loss (191.80 kJ) and microwave dissipation loss (198.00 kJ), which accounted for 7.10%, 15.27% and 15.76% of the total energy, respectively. The contents detailed in this study not only presented the energy conversion performances during microwave assisted gasification process but also supplied important data for developing gasification simulation models.     

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.     

A Voltage Control Method for a Distributed Line Feeder by means of Multiagent Approach

This paper proposes a method for the coordinated control of power factor by means of a multiagent approach. The proposed multiagent system consists of two types of agent: single feeder agent (F_AG) and bus agent (B_AG). In the proposed system, an F_AG plays as an important role, which decides the power factors of all distributed generators by executing the load flow calculations repeatedly. The voltage control strategies are implemented as the class definition of Java into the system. In order to verify the performance of the proposed method, it has been applied to a typical distribution model system. The simulation results show that the system is able to control very violent fluctuation of the demands and the photovoltaic (PV) generations.