单级无桥Sepic谐振LED驱动电路及其APWM-PFM混合控制

针对传统两级式LED驱动电源中存在着半导体功率器件数目多,控制电路复杂,效率低,成本高,可靠性差等问题,提出一种单级无桥Sepic谐振LED驱动电路,通过将单开关无桥Sepic电路主开关管与半桥LLC电路下开关管复用集成单级LED驱动电路,减少了半导体功率器件数目,简化控制电路,提高了电路效率和工作可靠性。详细分析了所提出电路的工作原理和工作过程,深入开展了电路输入输出电压变比、网侧特性、软开关特性等稳态特性推导和电路关键参数设计,并针对所提出单级电路由于输入电压变化引起直流母线电压变动范围大等问题,分析设计了一种APWM-PFM混合控制策略。最后进行计算机仿真分析,并设计一台交流输入185~265 V_(rms)、额定输出2 A/96 W的实验样机,样机效率最高可达91.5%,PF最大值为0.995,THD最小为5.5%,不同交流电压下直流母线电压总体变化范围在60 V以内,实现直流母线电压限压。计算机仿真结果和实验结果验证所提出电路和混合控制策略的理论预期和有效性。

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

基于PT-PFM激励阻抗谱数字重构的电缆故障诊断定位

由于传统频谱测试仪器增益带宽积有限,高频区间内输出电压过低,在针对长距离电缆测试时信号衰减较为严重,导致阻抗谱在高频区间内存在一定失真问题。该文提出一种基于伪梯形波激励阻抗谱数字重构算法的电缆故障诊断定位算法。分析不同故障类型下电力电缆的局部故障阻抗对电缆输入阻抗谱的影响规律、首端激励电压信号的衰减特性和不同电压幅值的功率传输特性。设计一种基于Si C高速逆变器的大容量伪梯形励磁系统,用于测量最高频率7 MHz的阻抗谱信息,利用阻抗谱数字重构方法实现0.1 Hz~60 MHz宽频区间的全覆盖。与传统的低压正弦激励相比,采用该时空转换函数的定位结果具有更小的区间振荡和更快的收敛速度。缺陷定位精度提高了80%,验证了该方法的有效性和准确性。

Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer

This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.

Vibration Control of A Flexible Marine Riser System Subject to Input Dead Zone and Extraneous Disturbances

An observer-based adaptive backstepping boundary control is proposed for vibration control of flexible offshore riser systems with unknown nonlinear input dead zone and uncertain environmental disturbances.The control algorithm can update the control law online through real-time data to make the controller adapt to the environment and improve the control precision.Specifically,based on the adaptive backstepping framework,virtual control laws and Lyapunov functions are designed for each subsystem.Three direction interference observers are designed to track the timevarying boundary disturbance.On this basis,the inverse of the dead zone and linear state transformation are used to compensate for the original system and eliminate the adverse effects of the dead zone.In addition,the stability of the closed-loop system is proven by Lyapunov stability theory.All the system states are bounded,and the vibration offset of the riser converges to a small area of the initial position.Finally,four examples of flexible marine risers are simulated in MATLAB to verify the effectiveness of the proposed controller.

一种基于DCM下的漏极反馈反激变换器在PFM峰值电流模式控制下的稳定性分析

针对原边反馈反激变换器具有辅助绕组而成本偏高的问题,基于原边反馈与峰值电流控制方案,提出了一种基于开关管漏极反馈的反激变换器模型。与原边反馈反激变换器相比,漏极反馈反激变换器能够减少变压器辅助绕组,降低了成本,且具有较高的稳定性。首先,对此漏极反馈反激变换器模型进行了理论分析,并提出了一种高精度漏极采样方法。其次,基于开关网络模型法对工作在断续导通模式(Discontinuous conduction mode,DCM)下脉冲频率调制(Pulse frequency modulation,PFM)的漏极反馈反激变换器进行了小信号建模并进行补偿设计。通过Matlab/Simulink搭建模型验证其正确性;最后搭建试验平台来进行验证。结果表明,所提出的漏极反馈反激变换器模型是可行的。

Control of highly pathogenic avian influenza through vaccination

The stamping-out strategy has been used to control highly pathogenic avian influenza viruses in many countries,driven by the belief that vaccination would not be successful against such viruses and fears that avian influenza virus in vaccinated birds would evolve more rapidly and pose a greater risk to humans.In this review,we summarize the successes in controlling highly pathogenic avian influenza in China and make suggestions regarding the requirements for vaccine selection and effectiveness.In addition,we present evidence that vaccination of poultry not only eliminates human infection with avian influenza virus,but also significantly reduces and abolishes some harmful characteristics of avian influenza virus.

An Integrated Control Framework for Torque Vectoring and Active Suspension System

Four-wheel independently driven electric vehicles(FWID-EV)endow a flexible and scalable control framework to improve vehicle performance.This paper integrates the torque vectoring and active suspension system(ASS)to enhance the vehicle’s longitudinal and vertical motion control performance.While the nonlinear characteristic of the tire model leads to a relatively heavier computational burden.To facilitate the controller design and ease the load,a half-vehicle dynamics system is built and simplified to the linear-time-varying(LTV)model.Then a model predictive controller is developed by formulating the objective function by comprehensively considering the safety,energy-saving and comfort requirements.The in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy consumption.Finally,the effectiveness of the proposed controller is verified through the rapid-control-prototype(RCP)test.The results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability.

Mitochondrial dysfunction and quality control lie at the heart of subarachnoid hemorrhage

The dramatic increase in intracranial pressure after subarachnoid hemorrhage leads to a decrease in cerebral perfusion pressure and a reduction in cerebral blood flow.Mitochondria are directly affected by direct factors such as ischemia,hypoxia,excitotoxicity,and toxicity of free hemoglobin and its degradation products,which trigger mitochondrial dysfunction.Dysfunctional mitochondria release large amounts of reactive oxygen species,inflammatory mediators,and apoptotic proteins that activate apoptotic pathways,further damaging cells.In response to this array of damage,cells have adopted multiple mitochondrial quality control mechanisms through evolution,including mitochondrial protein quality control,mitochondrial dynamics,mitophagy,mitochondrial biogenesis,and intercellular mitochondrial transfer,to maintain mitochondrial homeostasis under pathological conditions.Specific interventions targeting mitochondrial quality control mechanisms have emerged as promising therapeutic strategies for subarachnoid hemorrhage.This review provides an overview of recent research advances in mitochondrial pathophysiological processes after subarachnoid hemorrhage,particularly mitochondrial quality control mechanisms.It also presents potential therapeutic strategies to target mitochondrial quality control in subarachnoid hemorrhage.

用于LLC谐振拓扑的PFM发生器IP核设计

阐述LLC谐振拓扑的结构和频率特性,针对LLC谐振变换器对占空比固定为50%、频率可调节的需求,基于国产Seal 5000系列SA5Z-30-D1平台,提出一种带死区和互补输出的PFM发生器IP核。提出的IP核内部具有上下计数模式计数器和死区与互补生成模块,通过寄存器设置计数器最大值与自增量,以计数器方向信号作为PFM输出送入死区与互补生成模块,在死区与互补生成模块中产生反相信号并插入死区。通过示波器观测实际输出信号表明该IP核输出效果良好,可以灵活地输出可配置的带有死区、互补输出的PFM波形。

A Blockchain-Based Access Control Scheme for Reputation Value Attributes of the Internet of Things

The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.

A Review on Vibration Control of Multiple Cylinders Subjected to FlowInduced Vibrations

The fatigue damage caused by flow-induced vibration(FIV)is one of the major concerns for multiple cylindrical structures in many engineering applications.The FIV suppression is of great importance for the security of many cylindrical structures.Many active and passive control methods have been employed for the vibration suppression of an isolated cylinder undergoing vortex-induced vibrations(VIV).The FIV suppression methods are mainly extended to the multiple cylinders from the vibration control of the isolated cylinder.Due to the mutual interference between the multiple cylinders,the FIV mechanism is more complex than the VIV mechanism,which makes a great challenge for the FIV suppression.Some efforts have been devoted to vibration suppression of multiple cylinder systems undergoing FIV over the past two decades.The control methods,such as helical strakes,splitter plates,control rods and flexible sheets,are not always effective,depending on many influence factors,such as the spacing ratio,the arrangement geometrical shape,the flow velocity and the parameters of the vibration control devices.The FIV response,hydrodynamic features and wake patterns of the multiple cylinders equipped with vibration control devices are reviewed and summarized.The FIV suppression efficiency of the vibration control methods are analyzed and compared considering different influence factors.Further research on the FIV suppression of multiple cylinders is suggested to provide insight for the development of FIV control methods and promote engineering applications of FIV control methods.

Communication Resource-Efficient Vehicle Platooning Control With Various Spacing Policies

Platooning represents one of the key features that connected automated vehicles may possess as it allows multiple automated vehicles to be maneuvered cooperatively with small headways on roads. However, a critical challenge in accomplishing automated vehicle platoons is to deal with the effects of intermittent and sporadic vehicle-to-vehicle data transmissions caused by limited wireless communication resources. This paper addresses the co-design problem of dynamic event-triggered communication scheduling and cooperative adaptive cruise control for a convoy of automated vehicles with diverse spacing policies. The central aim is to achieve automated vehicle platooning under various gap references with desired platoon stability and spacing performance requirements, while simultaneously improving communication efficiency. Toward this aim, a dynamic event-triggered scheduling mechanism is developed such that the intervehicle data transmissions are scheduled dynamically and efficiently over time. Then, a tractable co-design criterion on the existence of both the admissible event-driven cooperative adaptive cruise control law and the desired scheduling mechanism is derived. Finally, comparative simulation results are presented to substantiate the effectiveness and merits of the obtained results.

A 16-bit 18-MSPS flash-assisted SAR ADC with hybrid synchronous and asynchronous control logic

This paper presents a 16-bit,18-MSPS(million samples per second)flash-assisted successive-approximation-register(SAR)analog-to-digital converter(ADC)utilizing hybrid synchronous and asynchronous(HYSAS)timing control logic based on an on-chip delay-locked loop(DLL).The HYSAS scheme can provide a longer settling time for the capacitive digital-to-analog converter(CDAC)than the synchronous and asynchronous SAR ADC.Therefore,the issue of incomplete settling or ringing in the DAC voltage for cases of either on-chip or off-chip reference voltage can be solved to a large extent.In addition,the fore-ground calibration of the CDAC’s mismatch is performed with a finite-impulse-response bandpass filter(FIR-BPF)based least-mean-square(LMS)algorithm in an off-chip FPGA(field programmable gate array).Fabricated in 40-nm CMOS process,the proto-type ADC achieves 94.02-dB spurious-free dynamic range(SFDR),and 75.98-dB signal-to-noise-and-distortion ratio(SNDR)for a 2.88-MHz input under 18-MSPS sampling rate.

Distributed Platooning Control of Automated Vehicles Subject to Replay Attacks Based on Proportional Integral Observers

Secure platooning control plays an important role in enhancing the cooperative driving safety of automated vehicles subject to various security vulnerabilities.This paper focuses on the distributed secure control issue of automated vehicles affected by replay attacks.A proportional-integral-observer(PIO)with predetermined forgetting parameters is first constructed to acquire the dynamical information of vehicles.Then,a time-varying parameter and two positive scalars are employed to describe the temporal behavior of replay attacks.In light of such a scheme and the common properties of Laplace matrices,the closed-loop system with PIO-based controllers is transformed into a switched and time-delayed one.Furthermore,some sufficient conditions are derived to achieve the desired platooning performance by the view of the Lyapunov stability theory.The controller gains are analytically determined by resorting to the solution of certain matrix inequalities only dependent on maximum and minimum eigenvalues of communication topologies.Finally,a simulation example is provided to illustrate the effectiveness of the proposed control strategy.

Path Planning and Tracking Control for Parking via Soft Actor-Critic Under Non-Ideal Scenarios

Parking in a small parking lot within limited space poses a difficult task. It often leads to deviations between the final parking posture and the target posture. These deviations can lead to partial occupancy of adjacent parking lots, which poses a safety threat to vehicles parked in these parking lots. However, previous studies have not addressed this issue. In this paper, we aim to evaluate the impact of parking deviation of existing vehicles next to the target parking lot(PDEVNTPL) on the automatic ego vehicle(AEV) parking, in terms of safety, comfort, accuracy, and efficiency of parking. A segmented parking training framework(SPTF) based on soft actor-critic(SAC) is proposed to improve parking performance. In the proposed method, the SAC algorithm incorporates strategy entropy into the objective function, to enable the AEV to learn parking strategies based on a more comprehensive understanding of the environment. Additionally, the SPTF simplifies complex parking tasks to maintain the high performance of deep reinforcement learning(DRL). The experimental results reveal that the PDEVNTPL has a detrimental influence on the AEV parking in terms of safety, accuracy, and comfort, leading to reductions of more than 27%, 54%, and 26%respectively. However, the SAC-based SPTF effectively mitigates this impact, resulting in a considerable increase in the parking success rate from 71% to 93%. Furthermore, the heading angle deviation is significantly reduced from 2.25 degrees to 0.43degrees.

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

STEAM教育理念下PFM混合教学模式在妇产科见习教学中的应用

目的:研究STEAM教育理念下PFM混合教学模式在妇产科见习教学中的应用效果。方法:将100名2020级临床医学专业的见习学生随机分为2组,分别通过STEAM教育理念下PFM混合教学模式(观察组)和传统的教学模式(对照组)接受临床见习教学。见习结束后,对2组学员的临床综合能力进行测评,另外用问卷调查的方法调查教学效果。结果:观察组学生在临床思维能力、学习兴趣以及与病人的沟通交流能力方面均显著优于对照组(P<0.01)。结论:STEAM教育理念下PFM混合教学模式在妇产科见习教学中切实可行,具有良好的教学效果。

A Tutorial on Quantized Feedback Control

In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.

Risk-Informed Model-Free Safe Control of Linear Parameter-Varying Systems

This paper presents a risk-informed data-driven safe control design approach for a class of stochastic uncertain nonlinear discrete-time systems.The nonlinear system is modeled using linear parameter-varying(LPV)systems.A model-based probabilistic safe controller is first designed to guarantee probabilisticλ-contractivity(i.e.,stability and invariance)of the LPV system with respect to a given polyhedral safe set.To obviate the requirement of knowing the LPV system model and to bypass identifying its open-loop model,its closed-loop data-based representation is provided in terms of state and scheduling data as well as a decision variable.It is shown that the variance of the closedloop system,as well as the probability of safety satisfaction,depends on the decision variable and the noise covariance.A minimum-variance direct data-driven gain-scheduling safe control design approach is presented next by designing the decision variable such that all possible closed-loop system realizations satisfy safety with the highest confidence level.This minimum-variance approach is a control-oriented learning method since it minimizes the variance of the state of the closed-loop system with respect to the safe set,and thus minimizes the risk of safety violation.Unlike the certainty-equivalent approach that results in a risk-neutral control design,the minimum-variance method leads to a risk-averse control design.It is shown that the presented direct risk-averse learning approach requires weaker data richness conditions than existing indirect learning methods based on system identification and can lead to a lower risk of safety violation.Two simulation examples along with an experimental validation on an autonomous vehicle are provided to show the effectiveness of the presented approach.