Aircraft Electric Anti-skid Braking System Based on Fuzzy-PID Controller with Parameter Self-adjustment Feature

The principle of electric braking system is analyzed and an anti-skid braking system based on the slip rate control is proposed.The fuzzy-PID controller with parameter self-adjustment feature is designed for the anti-skid braking system.The dynamic model of aircraft ground braking is established in the simulation environment of MATLAB/SIMULINK,and simulation results of dry runway and wet runway are presented.The results show that the fuzzy-PID controller with parameter self-adjustment feature for the electric anti-skid braking system keeps working in the state of stability and the brake efficiencies are increased to 93%on dry runway and 82%on wet runway respectively.

Performance analysis of semi-active cab’s hydraulic system of the vibratory roller using optimal fuzzy-PID control

In order to evaluate the performance of semi-active cab’s hydraulic mounts(SHM)of the off-road vibratory roller with the optimal fuzzy-PID(proportional integral derivative)control,a nonlinear dynamic model of the vehicle interacting with off-road terrains is established based on Matlab/Simulink software.The weighted root-mean-square(RMS)acceleration responses of the driver’s seat heave and the cab’s pitch angle are chosen as objective functions.The SHM is then optimized and analyzed via the optimal fuzzy-PID control under different operation conditions.The simulations results show that the driver’s ride comfort and the cab shaking are greatly affected by the off-road terrains under various operating conditions of the vehicle,especially at the speed from 8 to 12 km/h on a very poor terrain surface of Grenville soil ground under the vehicle travelling.With SHM using the optimal fuzzy-PID control,the driver’s ride comfort and the cab shaking are clearly improved under various operation conditions of the vehicle,particularly at the speed from 6 to 7 km/h of the vehicle traveling.

A New Coordinated Fuzzy-PID Controller for Power System Considering Electric Vehicles

With penetration growing of renewable energy sources which integrated into power system have caused problems on grid stability. Electric Vehicles (EV) are one of the renewable energy sources that can bring significant impacts to power system during their charging and discharging operations. This article established a model of single machine infinite bus (SMIB) power system considering EV as a case study of load disturbance for power system oscillation. The objective of this research is to enhance stability and overcome the drawbacks of traditional control algorithms such as power system stabilizer (PSS), PID controller and fuzzy logic controller (FLC). The implementation’s effect of FLC parallel with PID controller (Fuzzy-PID) has been shown in this paper. The speed deviation (?ω) and electrical power (Pe) are the important factors to be taken into consideration without EV (only change in mechanical torque), EV with change in the mechanical torque and sudden plug-in EV. The obtained result by nonlinear simulation using Matlab/Simulink of a SMIB power system with EV has shown the effectiveness of using (Fuzzy-PID) against all disturbances.

Fuzzy-PID controlled lift feedback fin stabilizer

Conventional PID controllers are widely used in fin stabilizer control systems, but they have time-variations, nonlinearity, and uncertainty influencing their control effects. A lift feedback fuzzy-PID control method was developed to better deal with these problems, and this lift feedback fin stabilizer system was simulated under different sea condition. Test results showed the system has better anti-rolling performance than traditional fin-angle PID control systems.

Application of Fuzzy-PID Control System in Full-Mechanized Coal Face

The control system, which includes structure, the composition of software and hardware, the form of PID control system and its systematic closed-loop, was used in No.4236 full-mechanized coal face of Xinlongzhuang mine. The typical fuzzy PID control system structure was investigated, and a simplified fuzzy PID control system was taken the place of the complex three-dimension fuzzy controller. Based on the parameter relation between fuzzy controller and normal PID controller, a common method of parameter adjustment of PID controller was summed up and the computer simulation was realized. This system can overcome the problems of large delay, nonlinear, poor running en- vironment and great load change in the full-mechanized coal face. The simulating investigation indicates that the de- signing method of fuzzy controller is simple and feasible.

Design and simulation about a self-Tuning fuzzy-PID controller

Fuzzy logic has attracted the attention of structural control engineers during the last few years,because fuzzy logic can handle nonlinearities,uncertainties,and heuristic knowledge effectively and easily.In this paper,a self-Tuning fuzzy-PID control method which used the technology of the fuzzy control and PID control unified is presented.These techniques can visualize the results and processes for structure stress.These techniques will also provide convenience for engineers and users,and have high practical values.The MATLAB simulation result shows that the system precision and the efficiency are very high and the static error is small,and robustness was also validated.

Advanced Functional Electromagnetic Shielding Materials:A Review Based on Micro‑Nano Structure Interface Control of Biomass Cell Walls

Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and hierarchical.Due to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding materials.Despite concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding materials.In particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be valuable.The preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and analyzed.The composite methods and fillers of various biomass materials were reviewed.this paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.

Passive activity enhances residual control ability in patients with complete spinal cord injury

Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these muscles may not effectively engage any of the remaining neurons in the descending pathway.A previous study unexpectedly found that a brief clinical round of passive activity significantly increased volitional muscle activation,as measured by surface electromyography.In this study,we further explored the effect of passive activity on surface electromyographic signals during volitional control tasks among individuals with complete spinal cord injury.Eleven patients with chronic complete thoracic spinal cord injury were recruited.Surface electromyography data from eight major leg muscles were acquired and compared before and after the passive activity protocol.The results indicated that the passive activity led to an increased number of activated volitional muscles and an increased frequency of activation.Although the cumulative root mean square of surface electromyography amplitude for volitional control of movement showed a slight increase after passive activity,the difference was not statistically significant.These findings suggest that brief passive activity may enhance the ability to initiate volitional muscle activity during surface electromyography tasks and underscore the potential of passive activity for improving residual motor control among patients with motor complete spinal cord injury.

A matrix metalloproteinase-responsive hydrogel system controls angiogenic peptide release for repair of cerebral ischemia/reperfusion injury

Vascular endothelial growth factor and its mimic peptide KLTWQELYQLKYKGI(QK)are widely used as the most potent angiogenic factors for the treatment of multiple ischemic diseases.However,conventional topical drug delivery often results in a burst release of the drug,leading to transient retention(inefficacy)and undesirable diffusion(toxicity)in vivo.Therefore,a drug delivery system that responds to changes in the microenvironment of tissue regeneration and controls vascular endothelial growth factor release is crucial to improve the treatment of ischemic stroke.Matrix metalloproteinase-2(MMP-2)is gradually upregulated after cerebral ischemia.Herein,vascular endothelial growth factor mimic peptide QK was self-assembled with MMP-2-cleaved peptide PLGLAG(TIMP)and customizable peptide amphiphilic(PA)molecules to construct nanofiber hydrogel PA-TIMP-QK.PA-TIMP-QK was found to control the delivery of QK by MMP-2 upregulation after cerebral ischemia/reperfusion and had a similar biological activity with vascular endothelial growth factor in vitro.The results indicated that PA-TIMP-QK promoted neuronal survival,restored local blood circulation,reduced blood-brain barrier permeability,and restored motor function.These findings suggest that the self-assembling nanofiber hydrogel PA-TIMP-QK may provide an intelligent drug delivery system that responds to the microenvironment and promotes regeneration and repair after cerebral ischemia/reperfusion injury.

Design Method for the Magnetic Bearing Control System with Fuzzy-PID Approach

The five degree freedom magnetic bearing is researched and its structure and working principles are introduced also. Based on the fuzzy control technology, combining fuzzy algorithm and PID control method, identifying the transition process mode of the online system to get the PID parameters＇ self-adjusting, the magnetic beating system＇s Fuzzy-PID nonlinear controller is designed by analyzing the system control demands. The Fuzzy-PID nonlinear controller can deal with the magnetic bearing system＇ s open loop instability and strong nonlinearity, and the approach could improve the system＇s rapidity, adaptability, stability and dynamic characteristics. Comparative analysis and experiments are conducted between linear PID and nonlinear fuzzy- PID control methods, the results show that the fuzzy-PID controller is better, and the five-freedom magnetic bearing＇ s rotary precision experiments are conducted by the fuzzy-PID controller, it satisfies the control rotary precision demands and realizes the hearing＇s steady floating and rotating.

Turbine speed control system based on a fuzzy-PID

The flexibility demand of marine nuclear power plant is very high,the multiple parameters of the marine nuclear power plant with the once-through steam generator are strongly coupled,and the normal PID control of the turbine speed can't meet the control demand.This paper introduces a turbine speed Fuzzy-PID controller to coordinately control the steam pressure and thus realize the demand for quick tracking and steady state control over the turbine speed by using the Fuzzy control's quick dynamic response and PID control's steady state performance.The simulation shows the improvement of the response time and steady state performance of the control system.

基于改进PSO-Fuzzy-PID的矿热炉电极升降控制仿真

矿热炉在运行过程中易受电极的影响,导致冶炼时耗电量增加,严重影响了产品的质量和产量,降低了生产效率。因此提出基于改进PSO-Fuzzy-PID的矿热炉电极升降控制方法。将TMR磁传感器安装到矿热炉上,获取外磁场响应信号,确定电极的实时位置。利用罗氏线圈设计二次侧电流检测系统,检测电极在运行过程中产生的二次侧电流。通过PSO算法优化Fuzzy-PID控制器的参数,建立PSO-Fuzzy-PID控制器,将二次侧电流输入PSO-Fuzzy-PID控制器中,通过调节电极二次侧电流完成矿热炉电极的升降控制。实验表明,上述方法可有效控制矿热炉的电压和电流,稳定性高,在控制响应试验中5s内可达到额定值,调节时间控制在0.5s内,所得数据证明了研究方法对矿热炉电极升降控制的效率更高。

Implementation of Fuzzy-PID in Smart Car Control

An unmanued smart car control system and the fuzzy-PID control algorithm are produced.A design scheme of fuzzy-PID controller is put forward.The simulation analysis from matlab indicated that the dynamic performance of fuzzy-PID control algorithm is better than that of usual PID.Experimental result of smart car show that it can follow the black guid line well and fast-stable complete running the whole trip.

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.

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.

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.

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.