Analysis of debris flow control effect and hazard assessment in Xinqiao Gully,Wenchuan M_(s)8.0 earthquake area based on numerical simulation

Xinqiao Gully is located in the area of the 2008 Wenchuan M_(s)8.0 earthquake in Sichuan province,China.Based on the investigation of the 2023"6-26"Xinqiao Gully debris flow event,this study assessed the effectiveness of the debris flow control project and evaluated the debris flow hazards.Through field investigation and numerical simulation methods,the indicators of flow intensity reduction rate and storage capacity fullness were proposed to quantify the effectiveness of the engineering measures in the debris flow event.The simulation results show that the debris flow control project reduced the flow intensity by41.05%to 64.61%.The storage capacity of the dam decreases gradually from upstream to the mouth of the gully,thus effectively intercepting and controlling the debris flow.By evaluating the debris flow of different recurrence intervals,further measures are recommended for managing debris flow events.

Real-Time Co-optimization of Gear Shifting and Engine Torque for Predictive Cruise Control of Heavy-Duty Trucks

Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty trucks.To minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is used.Finding the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin’s maximum principle and indirect shooting method.Dynamic programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed solver.Simulation,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed controller.The results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing roads.Moreover,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time.

Exploring Variability in Sea Level at a Tide Gauge Station through Control Charts

Monitoring temporal changes in sea level is important in assessing coastal risk.Sea level anomalies at a tide gauge station,if kinematically conceived,include systematic variations such as trend,acceleration,periodic oscillations,and random disturbances.Among them,the non-stationary nature of the random sea level variations of known or unknown origin at coastal regions has been long recognized by the sea level community.This study proposes the analyses of subgroups of random residual statistics of a rigorously formulated kinematic model solution of tide gauge variations using X-bar and S control charts.The approach is demonstrated using Key West,Florida tide gauge records.The mean and standard errors of 5-year-long subgroups of the residuals revealed that sea level changes at this location have been progressively intensifying from 1913 to the present.Increasing oscillations in sea level at this locality may be attributed partly to the thermal expansion of seawater with increasing temperatures causing larger buoyancy-related sea level fluctuations as well as the intensification of atmospheric events including wind patterns and the impact of changes in inverted barometer effects that will alter coastal risk assessments for the future.

Fuzzy Sliding Mode Control Based on Longitudinal Force Estimation for Electro-mechanical Braking Systems using BLDC Motor

This paper focuses on the controller design using fuzzy sliding mode control(FSMC)with application to electro-mechanical brake(EMB)systems using BLDC Motor.The EMB controller transmits the control signal to the motor driver to rotate the motor.The torque distribution of motors is studied in this paper actually.Firstly,the model of the EMB system is established.Then the state observer is developed to estimate the vehicle states including the vehicle velocity and longitudinal force.Due to the fact that the EMB system is nonlinear and uncertain,a FSMC strategy based on wheel slip ratio is proposed,where both the normal and emergency braking conditions are taken into account.The equivalent control law of sliding mode controller is designed on the basis of the variation of the front axle and rear axle load during the brake process,while the switching control law is adjusted by the fuzzy corrector.The simulation results illustrate that the FSMC strategy has the superior performance,better adaptability to various types of roads,and shorter braking distance,as compared to PID control and traditional sliding mode control technologies.Finally,the hardware-in-loop(HIL)experimental results have exemplified the validation of the developed methodology.

DC–DC Converter with Pi Controller for BLDC Motor Fuzzy Drive System

The Brushless DC Motor drive systems are used widely with renewable energy resources.The power converter controlling technique increases the performance by novel techniques and algorithms.Conventional approaches are mostly focused on buck converter,Fuzzy logic control with various switching activity.In this proposed research work,the QPSO(Quantum Particle Swarm Optimization algorithm)is used on the switching state of converter from the generation unit of solar module.Through the duty cycle pulse from optimization function,the MOSFET(Metal-Oxide-Semiconductor Field-Effect Transistor)of the Boost converter gets switched when BLDC(Brushless Direct Current Motor)motor drive system requires power.Voltage Source three phase inverter and Boost converter is controlled by proportional-integral(PI)controller.Based on the BLDC drive,the load utilized from the solar generating module.Experimental results analyzed every module of the proposed grid system,which are solar generation utilizes the irradiance and temperature depends on this the Photovoltaics(PV)power is generated and the QPSO with Duty cycle switching state is determined.The Boost converter module is boost stage based on generation and load is obtained.Single Ended Primary Inductor Converter(SEPIC)and Zeta converter model is compared with the proposed logic;the proposed boost converter achieves the results.Three phase inverter control,PI,and BLDC motor drive results.Thus the proposed grid model is constructed to obtain the better performance results than most recent literatures.Overall design model is done by using MATLAB/Simulink 2020a.

Automobile light control system based on CAN bus and contactless switch

In order to solve the complex wiring and low reliability of conventional light control system,an automobile contactless switch light system is designed combined with Hall element and controller area network （CAN） bus technology.The processing system of electromagnetic compatibility controlled by CAN bus is improved to reduce the electromagnetic interference from the controller and other sources of interference.With Freescale＇s high-performance single-chip MC9S08DZ60 and CAN transceiver TJA1050,the overall circuit design and software design are presented.The test results show that the designed light control system is feasible.

基于STM32的步进电机加减速轨迹规划算法

针对传统步进电机开环控制下加减速过程中柔性冲击大、失步和过冲等问题,结合STM32单片机提出了一种离散化的、带有电流调节的S曲线加减速控制算法。首先,通过多项式算法构建连续光滑的S曲线,根据矩频特性拟合转速和转矩的关系,联立转速和功率的关系,推导出电流计算方法;然后,对连续的S曲线进行等时间间隔采样,完成对S曲线的离散化;最后,在Keil平台进行算法代码编写,将编译后的工程文件下载到STM32中,通过步进电机的速度和位置跟踪实验验证了算法的有效性。

车辆主动悬架自适应变论域T-S模糊控制研究

针对传统变论域模糊控制存在过度依赖专家经验、伸缩因子参数不能自适应调整的问题,提出一种车辆主动悬架自适应变论域T-S模糊控制策略,从而提高车辆的行驶平顺性。结合神经网络和T-S模糊推理建立基于自适应神经模糊推理的一阶T-S模糊控制器,利用神经网络的自学习特性产生完善的模糊规则,进而在传统函数型伸缩因子的基础上,将系统误差和误差变化率作为动态参数引入伸缩因子中,实现伸缩因子参数的自适应调整,解决了传统函数型伸缩因子因参数确定难度大导致控制效果差的问题。通过随机工况下的仿真分析和基于相似理论的缩尺实验,对所提出算法的有效性和工况自适应性进行了验证。结果表明,所提出的自适应变论域T-S模糊控制策略具有较强的工况适应性,在不同车速、路面激励下均可有效提高车辆的平顺性并保证轮胎接地安全性。

基于B/S架构的远程会诊质控系统的设计与应用

目的研发远程会诊质控系统,在区域内实现远程会诊质控、管理、监管、考评、统计和持续改进的信息化。方法2020年,组建多学科团队,运用智力激励法和专题小组讨论法,基于B/S架构研发远程会诊质控系统,与既有远程会诊信息系统完全嵌合兼容,满足远程会诊全流程质量管理的功能需求。结果针对远程会诊质控工作要求,系统设计研发了质控管理、质控考评、实时监管、统计分析4个子模块,可满足远程会诊全流程质量管理的功能需求。结论该质控系统创新了远程会诊信息化质量管理模式,在区域内实现了远程会诊全流程的信息化管理,取得了较好的质量管理成效,有效促进区域内远程会诊工作的推进和发展。

A wide-angle wave control method of reducing torque ripple for brushless DC motor

In order to deal with torque pulsation problem caused by traditional control method for brushless DC （BLDC） motor and to achieve high precision and good stability, a novel control strategy is proposed. Compared with the traditional control scheme, by using phase voltage as a control objective and making waveform of phase current approximately quasi-sinusoidal, torque ripple of BLDC motor is reduced from the original 14% to 3.4%, while toque is increased by 3.8%. Furthermore, by detecting zero-crossings of back electromotive force （BEMF） with non-conducting phases, sensorless control is realized. The new control strategy is simple. It can minimize torque ripple, increase torque, and realize sensorless control for BLDC motor. Simulation and experiments show good performance of BLDC motor by using the new control method.

Dynamics and adaptive control of a dual-arm space robot with closed-loop constraints and uncertain inertial parameters

A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane＇s equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov＇s method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.

Disease monitoring strategies in inflammatory bowel diseases: What do we mean by “tight control”?

In recent years,there has been a critical change in treatment paradigms in inflammatory bowel diseases(IBD)triggered by the arrival of new effective treatments aiming to prevent disease progression,bowel damage and disability.The insufficiency of symptomatic disease control and the well-known discordance between symptoms and objective measures of disease activity lead to the need of reviewing conventional treatment algorithms and developing new concepts of optimal therapeutic strategy.The treat-to-target strategies,defined by the selecting therapeutic targets in inflammatory bowel disease consensus recommendation,move away from only symptomatic disease control and support targeting composite therapeutic endpoints(clinical and endoscopical remission)and timely assessment.Emerging data suggest that early therapy using a treat-to-target approach and an algorithmic therapy escalation using regular disease monitoring by clinical and biochemical markers(fecal calprotectin and C-reactive protein)leads to improved outcomes.This review aims to present the emerging strategies and supporting evidence in the current therapeutic paradigm of IBD including the concepts of“early intervention”,“treat-to-target”and“tight control”strategies.We also discuss the real-word experience and applicability of these new strategies and give an overview on the future perspectives and areas in need of further research and potential improvement regarding treatment targets and(“tight”)disease monitoring strategies.

基于Super-Twisting滑模S面的无人机路径跟踪控制

针对小型固定翼无人机在执行任务时跟踪精度低以及容易受外界风影响的问题,设计基于Super-Twisting滑模S面(STSM S-Plane)的路径跟踪控制器,同时采用内外双环控制模式。外环即速度环采用Super-Twisting滑模控制,内环即姿态环采用S面控制。考虑到S面控制求导易导致积分爆炸的问题引入了二阶微分器,并对外界风组成进行建模研究。最后通过空间特殊曲线来验证所设计算法的控制性能。仿真结果表明,所设计的算法可以实现固定翼无人机对期望路径的精确跟踪,并具有良好的鲁棒性和抗干扰性能。

Fault tolerant controlled quantum dialogue against collective noise

Quantum system is inevitably affected by the external environment in the real world.Two controlled quantum dialogue protocols are put forward based on logicalχ-type states under collective noise environment.One is against collectivedephasing noise,while the other is against collective-rotation noise.Compared with existing protocols,there exist several outstanding advantages in our proposed protocols:Firstly,theχ-type state is utilized as quantum channels,it possesses better entanglement properties than GHZ state,W state as well as cluster state,which make it difficult to be destroyed by local operations.Secondly,two kinds of logicalχ-type states are constructed by us in theory,which can be perfectly immune to the effects of collective noise.Thirdly,the controller can be offline after quantum distribution and permission announcement,without waiting for all the participants to complete the information coding.Fourthly,the security analysis illuminates that our protocols can not only be free from the information leakage,but also resist against the interceptand-resend attack,the entanglement-and-measure attack,the modification attack,the conspiring attack,and especially the dishonest controller’s attacks.

售货机升降系统S型速度控制策略

在传统三闭环控制方式下,售货机升降接货系统易因启停过程中加速度突变产生冲击,导致系统运行不平稳。针对这一问题,文中对传统升降系统加减速控制策略进行改进,加入前馈和微分负反馈,提出一种S型速度曲线控制算法。根据路径规划判别条件将S型速度曲线分为七段式、六段式和四段式3种,并给出各路径约束条件下的参数求解方法和具体执行流程。将该算法运用到升降控制系统中进行仿真和实际工况测试,实验结果表明,与传统三闭环控制相比,文中所提控制策略可以提高售货机升降系统运行的平稳性,减小冲击,使速度曲线更加柔和,并能够保持较好的跟踪性能。

A novel mixed-synchronization phenomenon in coupled Chua's circuits via non-fragile linear control

Dynamical variables of coupled nonlinear oscillators can exhibit different synchronization patterns depending on the designed coupling scheme. In this paper, a non-fragile linear feedback control strategy with multiplicative controller gain uncertainties is proposed for realizing the mixed-synchronization of Chua＇s circuits connected in a drive-response configuration. In particular, in the mixed-synchronization regime, different state variables of the response system can evolve into complete synchronization, anti-synchronization and even amplitude death simultaneously with the drive variables for an appropriate choice of scaling matrix. Using Lyapunov stability theory, we derive some sufficient criteria for achieving global mixed-synchronization. It is shown that the desired non-fragile state feedback controller can be constructed by solving a set of linear matrix inequalities （LMIs）. Numerical simulations are also provided to demonstrate the effectiveness of the proposed control approach.

THE OPTIMAL CONTROL FOR PROMOTING THE COOPERATION IN EVOLUTION GAME GENERATED BY PRISONER'S DILEMMA

Natural selection opposes the evolution of cooperation unless specific mechanisms are at work in Prisoner＇s Dilemma. By taking advantage of the modern control theory, the controller design is discussed and the optimal control is designed for promoting cooperation based on the recent advances in mechanisms for the evolution of cooperation. Two con- trol strategies are proposed： compensation control strategy for the cooperator when playing against a defector and reward control strategy for cooperator when playing against a coop- erator. The feasibility and effectiveness of these control strategies for promoting cooperation in different stages are analyzed. The reward for cooperation can＇t prevent defection from being evolutionary stable strategy （ESS）. On the other hand, compensation for the coopera- tor can＇t prevent defection from emerging and sustaining. By considering the effect and the cost, an optimal control scheme with constraint on the admissible control set is put forward. By analyzing the special nonlinear system of replicator dynamics, the exact analytic solution of the optimal control scheme is obtained based on the maximum principle. Finally, the effectiveness of the proposed method is illustrated by examples.

Improved S Surface Controller and Semi-physical Simulation for AUV

S surface controllers have been proven to provide effective motion control for an autonomous underwater vehicle (AUV).However, it is difficult to adjust their control parameters manually.Choosing the optimum parameters for the controller of a particular AUV is a significant challenge.To automate the process, a modified particle swarm optimization (MPSO) algorithm was proposed.It was based on immune theory, and used a nonlinear regression strategy for inertia weight to optimize AUV control parameters.A semi-physical simulation system for the AUV was developed as a platform to verify the proposed control method, and its structure was considered.The simulation results indicated that the semi-physical simulation platform was helpful, the optimization algorithm has good local and global searching abilities, and the method can be reliably used for an AUV.

The Modulation and Control of the Gecko's Foot Movement

The modulation and control of gecko＇s foot movements were studied electrophysiologically in order to design the motor control system of a gecko-mimic robot. In this study （1） the anatomy of the peripheral nerves controlling the gecko＇s foot movements was determined; （2） the relationship between the limb nerves of the gecko and its foot motor patterns was studied; （3） the afferent impulses of the nerves evoked by rubbing the gecko＇s toes and palm were recorded; （4） copying the natural patterns of movement of the gecko＇s foot （abduction, adduction, flexion, and revolution） and its limb nerve modulation and control mechanism, the nerves were stimulated under computer control, and the results recorded by CCD. Results suggest that gecko＇s foot movements can be successfully controlled by artificial electrical signals.

Adaptive Proportional-Derivative Sliding Mode Control Law With Improved Transient Performance for Underactuated Overhead Crane Systems

In this paper, an adaptive proportional-derivative sliding mode control(APD-SMC) law, is proposed for 2D underactuated overhead crane systems. The proposed controller has the advantages of simple structure, easy to implement of PD control, strong robustness of SMC with respect to external disturbances and uncertain system parameters, and adaptation for unknown system dynamics associated with the feedforward parts. In the proposed APD-SMC law, the PD control part is used to stabilize the controlled system, the SMC part is used to compensate the external disturbances and system uncertainties,and the adaptive control part is utilized to estimate the unknown system parameters. The coupling behavior between the trolley movement and the payload swing is enhanced and, therefore, the transient performance of the proposed controller is improved.The Lyapunov techniques and the La Salle's invariance theorem are employed in to support the theoretical derivations. Experimental results are provided to validate the superior performance of the proposed control law.