Transmission Dynamics and Optimal Control Strategies of a Hand-Foot-Mouth Disease Model with Treatment and Vaccination Interventions

In this article, the transmission dynamics of a Hand-Foot-Mouth disease model with treatment and vaccination interventions are studied. We calculated the basic reproduction number and proved the global stability of disease-free equilibrium when R0 R0 > 1. Meanwhile, we obtained the optimal control strategies minimizing the cost of intervention and minimizing the infected person. We also give some numerical simulations to verify our theoretical results.

Comprehensive Prevention and Control Technology of Vegetable Diseases and Pests in Shandong Province

An in-depth research and practice has been conducted on vegetable diseases and pests in Shandong Province,and the principles of comprehensive and ecological control of diseases and pests are put forward,including agricultural control measures such as crop rotation,field cleaning,fertilizer and water management,physical control measures such as catching and killing,trapping,blocking,photoelectric energy treatment,biological control measures such as the use of natural enemies,pathogenic microorganisms,other beneficial organisms and metabolites,and scientific and rational chemical control measures.Comprehensive prevention and control not only controls vegetable diseases and pests effectively,but also protects the ecological environment.

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.

Study on the Effective Prevention and Control of Maize Rough Dwarf Disease in Different Areas with Varying Epidemic Intensity in Shandong Province

[ Objective] This study aimed to investigate the effective prevention and control of maize rough dwarf disease in different areas with varying epidemic inten-sity in Shandong Province. [Method] Control effects of single application of virus in-hibitors and composite application of virus inhibitors with seed dressing agents and pesticides on maize rough dwarf disease in different areas with varying epidemic intensity were investigated. [Result] The same treatment possessed entirely different effects in severely affected areas and slightly affected areas. To be specific, single application of virus inhibitors in slightly affected areas exhibited good control effects, with a control efficiency of 76.59% and yield increment rate of 158.21%; in severely affected areas, single application of virus inhibitors led to low control efficiency and yield increment rate. The highest control efficiency of composite application of virus inhibitors with seed dressing agents and pesticides in severely affected areas was 71.38%, and experimental plots changed from total crop failure to have certain eco-nomic output. [Conclusion] ln different areas with varying epidemic intensity of maize rough dwarf disease, different application modes should be adopted according to lo-cal conditions, thereby saving cost and improving control efficiency.

An Anthropomorphic Robot Hand Developed Based on Underactuated Mechanism and Controlled by EMG Signals

When developing a humanoid myo-control hand,not only the mechanical structure should be considered to afford a high dexterity,but also the myoelectric (electromyography,EMG) control capability should be taken into account to fully accomplish the actuation tasks.This paper presents a novel humanoid robotic myocontrol hand (AR hand Ⅲ) which adopted an underac- tuated mechanism and a forearm myocontrol EMG method.The AR hand Ⅲ has five fingers and 15 joints,and actuated by three embedded motors.Underactuation can be found within each finger and between the rest three fingers (the middle finger,the ring finger and the little finger) when the hand is grasping objects.For the EMG control,two specific methods are proposed:the three-fingered hand gesture configuration of the AR hand Ⅲ and a pattern classification method of EMG signals based on a statistical learning algorithm-Support Vector Machine (SVM).Eighteen active hand gestures of a testee are recognized ef- fectively,which can be directly mapped into the motions of AR hand Ⅲ.An on-line EMG control scheme is established based on two different decision functions:one is for the discrimination between the idle and active modes,the other is for the recog- nition of the active modes.As a result,the AR hand Ⅲ can swiftly follow the gesture instructions of the testee with a time delay less than 100 ms.

A novel grasping force control strategy for multi-fingered prosthetic hand

A grasping force control strategy is proposed in order to complete various free manipulations by using anthropomorphic prosthetic hand. The position-based impedance control and force-tracking impedance control are used in free and constraint spaces, respectively. The fuzzy observer is adopted in transition in order to switch control mode. Two control modes use one position-based impedance controller. In order to achieve grasping force track, reference force is added to the impedance controller in the constraint space. Trajectory tracking in free space and torque tracking in constrained space are realized, and reliability of mode switch and stability of system are achieved. An adaptive sliding mode friction compensation method is proposed. This method makes use of terminal sliding mode idea to design sliding mode function, which makes the tracking error converge to zero in finite time and avoids the problem of conventional sliding surface that tracking error cannot converge to zero. Based on the characteristic of the exponential form friction, the sliding mode control law including the estimation of friction parameter is obtained through terminal sliding mode idea, and the online parameter update laws are obtained based on Lyapunov stability theorem. The experiments on the HIT Prosthetic Hand IV are carried out to evaluate the grasping force control strategy, and the experiment results verify the effectiveness of this control strategy.

Cartesian impedance control of dexterous robot hand

Presents a novel compliant motion control for a robot hand using the Cartesian impedance approach based on fingertip force measurements. The fingertip can accurately track desired motion in free space and appear as mechanical impedance in constrained space. In the position based impedance control strategy, any switching mode in contact transition phase is not needed. The impedance parameters can be adjusted in a certain range according to various tasks. In this paper, the analysis of the finger’s kinematics and dynamics is given. Experimental results have shown the effectiveness of this control strategy.

Direct Yaw Moment Control for Distributed Drive Electric Vehicle Handling Performance Improvement

For a distributed drive electric vehicle（DDEV） driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control（DYC） has been widely studied and applied to vehicle stability control. Good vehicle handling performance： quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts： a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error（ITAE） function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method： yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.

Nonlinear adaptive optimal control for vehicle handling improvement through steer-by-wire system

A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel,based on the nonlinear adaptive optimal control(NAOC).A nonlinear 4-DOF model was initially developed,then it was simplified to a 2-DOF model with reasonable assumptions to design observer and optimal controllers.Then a simplified model was developed for steering system.The numerical simulations were carried out using vehicle parameters for standard maneuvers in dry and wet road conditions.Moreover,the hardware in the loop method was implemented to prove the controller ability in realistic conditions.Simulation results obviously show the effectiveness of NAOC on vehicle handling and reveal that the proposed controller can significantly improve vehicle handling during severe maneuvers.

Real-time and wearable functional electrical stimulation system for volitional hand motor function control using the electromyography bridge method

Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy.A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor function control using the electromyography bridge method.Through a series of novel design concepts,including the integration of a detecting circuit and an analog-to-digital converter,a miniaturized functional electrical stimulation circuit technique,a low-power super-regeneration chip for wireless receiving,and two wearable armbands,a prototype system has been established with reduced size,power,and overall cost.Based on wrist joint torque reproduction and classification experiments performed on six healthy subjects,the optimized surface electromyography thresholds and trained logistic regression classifier parameters were statistically chosen to establish wrist and hand motion control with high accuracy.Test results showed that wrist flexion/extension,hand grasp,and finger extension could be reproduced with high accuracy and low latency.This system can build a bridge of information transmission between healthy limbs and paralyzed limbs,effectively improve voluntary participation of hemiplegic patients,and elevate efficiency of rehabilitation training.

基于HAND的流域洪水淹没快速分析技术

快速分析计算流域洪水淹没,对于防洪具有重要作用,而基于水动力学模型的经典淹没算法在时效性方面存在不足,制约防洪“四预”功能实现和数字孪生流域建设。针对此,本文建立了基于HAND(Height Above Nearest Drainage)的形态淹没模型,用于快速分析流域洪水淹没情况,在乐安河流域上游进行了应用验证。结果表明,模型可在5秒内完成洪水淹没计算,对四场历史洪水和三场设计洪水淹没范围的总体模拟精度平均为0.95,达到水动力学模型的模拟精度;对淹没水深的模拟存在较大误差,平均误差为0.79 m。基于HAND的形态淹没模型可快速绘制全流域洪水淹没范围图,大幅提升影响预报和防洪预演的时效性水平。

A Trajectory Prediction Based Intelligent Handover Control Method in UAV Cellular Networks

The airborne base station(ABS) can provide wireless coverage to the ground in unmanned aerial vehicle(UAV) cellular networks.When mobile users move among adjacent ABSs,the measurement information reported by a single mobile user is used to trigger the handover mechanism.This handover mechanism lacks the consideration of movement state of mobile users and the location relationship between mobile users,which may lead to handover misjudgments and even communication interrupts.In this paper,we propose an intelligent handover control method in UAV cellular networks.Firstly,we introduce a deep learning model to predict the user trajectories.This prediction model learns the movement behavior of mobile users from the measurement information and analyzes the positional relations between mobile users such as avoiding collision and accommodating fellow pedestrians.Secondly,we propose a handover decision method,which can calculate the users' corresponding receiving power based on the predicted location and the characteristic of air-to-ground channel,to make handover decisions accurately.Finally,we use realistic data sets with thousands of non-linear trajectories to verify the basic functions and performance of our proposed intelligent handover controlmethod.The simulation results show that the handover success rate of the proposed method is 8% higher than existing methods.

DSP ＆ FPGA-based control architecture for a highly integrated robot hand with enhanced impedance performance

A novel control system is developed to improve the capabilities of robet hand performing tasks in a variety of environments. A joint impedance control strategy has been successfully implemented in the low level control of a highly integrated robot hand. At flint, a real time controller with DSP＆FPGA-based multilevel control architecture is built. Then a current sensor of the single direct current （DC） link is used to measure and reconstruct the three phase currents, and a stable current signal is measured by optimizing sample instant. The experimental results of the joint impedance control show that the proposed method not only improves the effectiveness of contact environment performance, but also provides compliant interaction of robot hand with a person, which is very important for the development of friendly human robot of the next generation.

HIT anthropomorphic robotic hand and finger motion control

Nowadays many anthropomorphic robotic hands have been put forward. These hands emphasize different aspects according to their applications. HIT Anthropomorphic Robotic Hand (ARhand) is a simple, lightweight and dexterous design per the requirements of anthropomorphic robots. Underactuated self-adaptive theory is adopted to decrease the number of motors and weight. The fingers of HIT ARhand with multi phalanges have the same size as those of an adult hand. Force control is realized with the position sensor, joint torque sensor and fingertip torque sensor. From the 3D model, the whole hand, with the low power consumption DSP control board integrated in it, will weigh only 500 g. It will be assembled on a BIT-Anthropomorphic Robot.

Hand-eye-vision based control for an inspection robot's autonomous line grasping

In order to ensure that the off-line arm of a two-arm-wheel combined inspection robot can reliably grasp the line in case of autonomous obstacle crossing,a control method is proposed for line grasping based on hand-eye visual servo.On the basis of the transmission line's geometrical characteristics and the camera's imaging principle,a line recognition and extraction method based on structure constraint is designed.The line's intercept and inclination are defined in an imaging space to represent the robot's change of pose and a law governing the pose decoupling servo control is developed.Under the integrated consideration of the influence of light intensity and background change,noise(from the camera itself and electromagnetic field)as well as the robot's kinetic inertia on the robot's imaging quality in the course of motion and the grasping control precision,a servo controller for grasping the line of the robot's off-line arm is designed with the method of fuzzy control.An experiment is conducted on a 1:1 simulation line using an inspection robot and the robot is put into on-line operation on a real overhead transmission line,where the robot can grasp the line within 18 s in the case of autonomous obstacle-crossing.The robot's autonomous line-grasping function is realized without manual intervention and the robot can grasp the line in a precise,reliable and efficient manner,thus the need of actual operation can be satisfied.

Machine Learning and Data-Driven Techniques for the Control of Smart Power Generation Systems:An Uncertainty Handling Perspective

Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.

A five-fingered underactuated prosthetic hand:hardware and its control scheme

A five-fingered underactuated prosthetic hand controlled by surface EMG (electromyographic) signals is presented in this paper. The prosthetic hand was designed with simplicity, lightweight and dexterity on the requirement of anthropomorphic hands. Underactuated self-adaptive theory was adopted to decrease the number of motors and weight. The control part of the prosthetic hand was based on a surface EMG motion pattern classifier which combines LM-based (Levenberg-Marquardt) neural network with the parametric AR (autoregressive) model. This motion pattern classifier can successfully identify the flexions of the thumb, the index finger and the middle finger by measuring the surface EMG signals through two electrodes mounted on the flexor digitorum profundus and flexor pollicis longus. Furthermore, via continuously controlling a single finger's motion, the five-fingered underactuated prosthetic hand can achieve more prehensile postures such as power grasp, centralized grip, fingertip grasp, cylindrical grasp, etc. The experimental results show that the classifier has a great potential application to the control of bionic man-machine systems because of its fast learning speed, high recognition capability and strong robustness.

A Hybrid Model Predictive Control for Handling Infeasibility and Constraint Prioritization

A hybrid approach using MLD (mixed logical dynamical) framework to handle infeasibility and constraint prioritization issues in MPC (model predictive control) based on input-output model is introduced. By expressing constraint priorities as propositional logics and by transforming the propositional logics into inequalities,the infeasibility and constraint prioritization issues are solved in the MPC. Constraints with higher priorities are met first, and then these with lower priorities are satisfied as much as possible. This new approach is illustrated in the control of a heavy oil fractionator-Shell column. The overall control performance has been significantly improved through the infeasibility and control priorities handling.