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.

A Fractional-Order Ultra-Local Model-Based Adaptive Neural Network Sliding Mode Control of n-DOF Upper-Limb Exoskeleton With Input Deadzone

This paper proposes an adaptive neural network sliding mode control based on fractional-order ultra-local model for n-DOF upper-limb exoskeleton in presence of uncertainties,external disturbances and input deadzone.Considering the model complexity and input deadzone,a fractional-order ultra-local model is proposed to formulate the original dynamic system for simple controller design.Firstly,the control gain of ultra-local model is considered as a constant.The fractional-order sliding mode technique is designed to stabilize the closed-loop system,while fractional-order time-delay estimation is combined with neural network to estimate the lumped disturbance.Correspondingly,a fractional-order ultra-local model-based neural network sliding mode controller(FO-NNSMC) is proposed.Secondly,to avoid disadvantageous effect of improper gain selection on the control performance,the control gain of ultra-local model is considered as an unknown parameter.Then,the Nussbaum technique is introduced into the FO-NNSMC to deal with the stability problem with unknown gain.Correspondingly,a fractional-order ultra-local model-based adaptive neural network sliding mode controller(FO-ANNSMC) is proposed.Moreover,the stability analysis of the closed-loop system with the proposed method is presented by using the Lyapunov theory.Finally,with the co-simulations on virtual prototype of 7-DOF iReHave upper-limb exoskeleton and experiments on 2-DOF upper-limb exoskeleton,the obtained compared results illustrate the effectiveness and superiority of the proposed method.

Influence of heat input on microhardness and microstructure across the welding interface between stainless steel and low alloy steel

The welding interface is crucial to the service safety of dissimilar metal weld(DMW)joints between stainless steel(SS)and low alloy(LA)steel.Different status of welding interfaces was prepared by cladding SS consumables to LA steel substrates with different heat inputs via tungsten inert gas arc welding(TIG),followed by a series of microstructural characterizations and hardness tests.Results showed that a hardening and transition layer(TL)would be generated along the welding interface,and the width and hardening degree of the TL would increase with the heat input.Meanwhile,heavy load hardness tests showed that highly severe inhomogeneous plastic deformation and the microcrack would be generated in the interfacial region and the welding interface respectively in the highest heat input sample(1.03 kJ/mm).These results indicate that the increase in heat input would deteriorate the bonding performance of DMW joints.Further microstructural observations showed that the higher hardening degree of the highest heat input sample was mainly attributed to the stronger grain boundary,solution,and dislocation strengthening effects.

Dynamic Event-Triggered Consensus Control for Input Constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical simulations show the effectiveness of the proposed approach.

A Hybrid Compensation Scheme for the Input Rate-Dependent Hysteresis of the Piezoelectric Ceramic Actuators

A hybrid compensation scheme for piezoelectric ceramic actuators(PEAs)is proposed.In the hybrid compensation scheme,the input rate-dependent hysteresis characteristics of the PEAs are compensated.The feedforward controller is a novel input rate-dependent neural network hysteresis inverse model,while the feedback controller is a proportion integration differentiation(PID)controller.In the proposed inverse model,an input ratedependent auxiliary inverse operator(RAIO)and output of the hysteresis construct the expanded input space(EIS)of the inverse model which transforms the hysteresis inverse with multi-valued mapping into single-valued mapping,and the wiping-out,rate-dependent and continuous properties of the RAIO are analyzed in theories.Based on the EIS method,a hysteresis neural network inverse model,namely the dynamic back propagation neural network(DBPNN)model,is established.Moreover,a hybrid compensation scheme for the PEAs is designed to compensate for the hysteresis.Finally,the proposed method,the conventional PID controller and the hybrid controller with the modified input rate-dependent Prandtl-Ishlinskii(MRPI)model are all applied in the experimental platform.Experimental results show that the proposed method has obvious superiorities in the performance of the system.

Adaptive Sensor-Fault Tolerant Control of Unmanned Underwater Vehicles With Input Saturation

This paper investigates the tracking control problem for unmanned underwater vehicles(UUVs)systems with sensor faults,input saturation,and external disturbance caused by waves and ocean currents.An active sensor fault-tolerant control scheme is proposed.First,the developed method only requires the inertia matrix of the UUV,without other dynamic information,and can handle both additive and multiplicative sensor faults.Subsequently,an adaptive fault-tolerant controller is designed to achieve asymptotic tracking control of the UUV by employing robust integral of the sign of error feedback method.It is shown that the effect of sensor faults is online estimated and compensated by an adaptive estimator.With the proposed controller,the tracking error and estimation error can asymptotically converge to zero.Finally,simulation results are performed to demonstrate the effectiveness of the proposed method.

Exact controllability of rational expectations model with multiplicative noise and input delay

This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.

Estimating the Input Power of a Power Plant Using the Efficiency of the Inverter

The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation systems and proposes an approach based on the efficiency formula widely documented in the literature. In the absence of input data, this method makes it possible to estimate the plant’s input power using data extracted from the site, in particular that provided by the Ministry of the Environment. The importance of this study lies in the need to accurately determine the input power in order to assess the overall performance of the energy system.

Input Structure Design for Structural Controllability of Complex Networks

This paper addresses the problem of the input design of large-scale complex networks.Two types of network components,redundant inaccessible strongly connected component(RISCC)and intermittent inaccessible strongly connected component(IISCC)are defined,and a subnetwork called a driver network is developed.Based on these,an efficient method is proposed to find the minimum number of controlled nodes to achieve structural complete controllability of a network,in the case that each input can act on multiple state nodes.The range of the number of input nodes to achieve minimal control,and the configuration method(the connection between the input nodes and the controlled nodes)are presented.All possible input solutions can be obtained by this method.Moreover,we give an example and some experiments on real-world networks to illustrate the effectiveness of the method.

Effects of heat input on layer heterogeneity of selective laser melting Ti-6Al-4V components

Due to the layer-by-layer manufacturing characteristics,metallurgical process of selective laser melting(SLM)is inherently dif-ferent in the building direction because of varying conditions,thereby resulting inter-layer heterogeneity.To mitigate such anisotropy,it is of great significance to understand the effects of processing parameters on the property evolution and thus metallurgy of fabrication process.This research proposes one-factor-at-a-time experiment to investigate the influences of laser power and scanning speed on the surface qual-ity,microstructures and mechanical properties of selective laser melted Ti-6Al-4V parts.Surface quality is assessed by roughness around the printings while mechanical properties are evaluated through microhardness and tensile strengths.Phases in microstructure are quantified by XRD to correlate with mechanical properties.Fracture morphology is analyzed to understand the effect of defects and microstructure on mechanical performance.The optimized parameter corresponding to best surface quality and mechanical properties has been found respect-ively in laser power of 190 W and scanning speed of 800 mm/s.After optimization,surface roughness has decreased by 44.47%for upper surface.Yielding strength,tensile strength and elongation rate have improved by 13.17%,43.34%and 64.51%,respectively,with similar hardness and Young’s modulus.In addition,heterogeneity of mechanical properties has great improvement by a range of 31.63%-92.68%.

Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison

Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state responses.This paper presents a deep observation on and a comparison between two of those methods:the generalized extended-state observer(GESO)and the equivalent input disturbance(EID)from assumptions,system configurations,stability conditions,system design,disturbance-rejection performance,and extensibility.A time-domain index is introduced to assess the disturbance-rejection performance.A detailed observation of disturbance-suppression mechanisms reveals the superiority of the EID approach over the GESO method.A comparison between these two methods shows that assumptions on disturbances are more practical and the adjustment of disturbance-rejection performance is easier for the EID approach than for the GESO method.

Observer-Based Path Tracking Controller Design for Autonomous Ground Vehicles With Input Saturation

This paper investigates the problem of path tracking control for autonomous ground vehicles(AGVs),where the input saturation,system nonlinearities and uncertainties are considered.Firstly,the nonlinear path tracking system is formulated as a linear parameter varying(LPV)model where the variation of vehicle velocity is taken into account.Secondly,considering the noise effects on the measurement of lateral offset and heading angle,an observer-based control strategy is proposed,and by analyzing the frequency domain characteristics of the derivative of desired heading angle,a finite frequency H_∞index is proposed to attenuate the effects of the derivative of desired heading angle on path tracking error.Thirdly,sufficient conditions are derived to guarantee robust H_∞performance of the path tracking system,and the calculation of observer and controller gains is converted into solving a convex optimization problem.Finally,simulation examples verify the advantages of the control method proposed in this paper.

Stabilization of fractional bilinear systems with multiple inputs

In this paper,we study in a constructive way the stabilization problem of fractional bilinear systems with multiple inputs.Using the quadratic Lyapunov functions and some additional hypotheses on the unit sphere,we construct stabilizing feedback laws for the considered fractional bilinear system.A numerical example is given to illustrate the efficiency of the obtained result.

SRResNet Performance Enhancement Using Patch Inputs and Partial Convolution-Based Padding

Due to highly underdetermined nature of Single Image Super-Resolution(SISR)problem,deep learning neural networks are required to be more deeper to solve the problem effectively.One of deep neural networks successful in the Super-Resolution(SR)problem is ResNet which can render the capability of deeper networks with the help of skip connections.However,zero padding(ZP)scheme in the network restricts benefits of skip connections in SRResNet and its performance as the ratio of the number of pure input data to that of zero padded data increases.In this paper.we consider the ResNet with Partial Convolution based Padding(PCP)instead of ZP to solve SR problem.Since training of deep neural networks using patch images is advantageous in many aspects such as the number of training image data and network complexities,patch image based SR performance is compared with single full image based one.The experimental results show that patch based SRResNet SR results are better than single full image based ones and the performance of deep SRResNet with PCP is better than the one with ZP.

Defected Ground Structure Multiple Input-Output Antenna For Wireless Applications

In this paper,the investigation of a novel compact 2×2,2×1,and 1×1 Ultra-Wide Band(UWB)based Multiple-Input Multiple-Output(MIMO)antenna with Defected Ground Structure(DGS)is employed.The proposed Electromagnetic Radiation Structures(ERS)is composed of multiple radiating elements.These MIMO antennas are designed and analyzed with and without DGS.The feeding is introduced by a microstrip-fed line to significantly moderate the radiating structure’s overall size,which is 60×40×1 mm.The high directivity and divergence characteristics are attained by introducing the microstripfed lines perpendicular to each other.And the projected MIMO antenna structures are compared with others by using parameters like Return Loss(RL),Voltage Standing Wave Ratio(VSWR),Radiation Pattern(RP),radiation efficiency,and directivity.The same MIMO set-up is redesigned with DGS,and the resultant parameters are compared.Finally,the Multiple Input and Multiple Output Radiating Structures with and without DGS are compared for result considerations like RL,VSWR,RP,radiation efficiency,and directivity.This projected antenna displays an omnidirectional RP with moderate gain,which is highly recommended for human healthcare applications.By introducing the defected ground structure in bottom layer the lower cut-off frequencies of 2.3,4.5 and 6.0 GHz are achieved with few biological effects on radio propagation in human body communications.The proposed design covers numerous well-known wireless standards,along with dual-function DGS slots,and it can be easily integrated into Wireless Body Area Networks(WBAN)in medical applications.This WBAN links the autonomous nodes that may be situated either in the clothes,on-body or beneath the skin of a person.This system typically advances the complete human body and the inter-connected nodes through a wireless communication channel.

China's low-carbon competitiveness and its effect decomposition from the perspective of wellbeing performance of ecological input

From the perspective of wellbeing performance of ecological input,this paper constructs a low-carbon competitiveness evaluation model with wellbeing performance of carbon emissions as the measurement standard,and uses the LMDI factor decomposition method to decompose the total effect of low-carbon competitiveness changes into technology effect and service effect.And then it conducts positive analysis and comparison of the low-carbon competitiveness and its effect contribution of G20 countries from1990 to 2018.The results are as follows:Firstly,in 2018,the UK,France,Argentina,Brazil,and Germany had higher low-carbon competitiveness.From 1990 to 2018,the low-carbon competitiveness of the UK,Turkey,Germany,Italy,and Brazil increase rapidly.Secondly,from 1990 to 2018,the total effect of low-carbon competitiveness of G20 member states was all positive,that is to say,the overall wellbeing performance of carbon emissions increased,technology effect and service effect are positive in 17 countries and negative in 2 countries respectively.Thirdly,China's low-carbon competitiveness is low,lacking static and dynamic advantages,although the technology effect is the highest,but the service effect is the lowest,resulting in a low total effect,which indicates that the wellbeing performance of economic growth is the main bottleneck of China's low-carbon development.Finally,the policy recommendations for China's future low-carbon transition and sustainable development are put forward.

水稻种植模式与秸秆还田方式对土壤养分的影响

为探明水稻不同种植模式与还田方式下土壤养分含量的变化。以辽星21号为试验材料,在大田条件下,比较移栽与直播种植2种模式下秸秆还田、炭化还田和不还田3种方式土壤中有机碳、速效氮、速效磷、速效钾、全氮、全磷、全钾含量的差异。研究结果表明,直播种植模式较移栽方式土壤速效磷含量、速效钾含量和全磷含量增加0.9%、5.4%和7.1%,生物炭还田较不还田处理分别显著增加土壤有机碳含量、速效钾含量、全氮含量和全磷含量9.6%、20.1%、5.3%和8.1%。因此,直播种植结合生物炭还田可作为提高农田肥力、改善土壤养分的一项促进北方寒地稻田资源再利用有效措施。

隐性关联关系与审计费用——基于供应链工商大数据的研究

近年来,上市公司将其供应链商业关系隐藏化以规避信息披露要求的趋势越来越明显,不利于投资者评估和判断上市公司的交易性质和盈利能力。本文从审计师角度出发,以2010-2021年度我国A股上市公司为研究对象,基于供应链工商大数据度量隐性关联关系,分析隐性关联关系与审计费用之间的关系,结果发现上市公司与重要交易对象之间存在隐性关联关系提高了审计费用,一系列稳健性检验结果保持一致。在渠道检验中,研究发现隐性关联关系通过影响审计师投入,进一步影响审计费用。在分组检验中,研究发现隐性关联关系对审计费用的影响在高市场化进程地区、低信息透明度的公司以及当上市公司为事务所重要客户时更为显著。本文研究为审计师如何判断隐性关联关系问题提供了经验数据。

含风光出力随机性的独立微电网二次频率控制

针对风、光发电随机性的问题,提出一种考虑新能源减载参与二次调频的模型预测控制方法。建立包含随机功率扰动的扩展状态矩阵,采用卡尔曼滤波估算随机未知扰动;依据风、光最大可用功率,建立实时变约束,避免机组功率越限;设置合理的权重系数,优先风、光发电出力参与二次调频;通过求解变约束二次规划问题,获得各个机组的优化调频功率。最后,建立含多个光伏、风电的微电网模型,在不同场景下与常规二次调频方法进行对比仿真。仿真结果表明,所提方法能提高系统频率恢复速度,减小系统频率波动,尤其在风、光发电剧烈波动场景下。

微量元素对超大线能量EH36船板热影响区粗晶区组织和性能的影响

通过焊接热模拟研究了在超大线能量下焊接时Al元素、Mg元素和Ti元素含量对EH36高强船板钢热影响区粗晶区组织、性能的影响规律,采用Thermo-Calc热力学计算与SEM,EDS测试相结合的方法揭示了Al元素、Mg元素和Ti元素含量与母材中氧化物类型、尺寸、数量及粗晶区相变的关系.结果表明,Al_(2)O_(3)无法诱导针状铁素体相变,当Al元素质量分数低于0.005%时,钢中可形成Mg元素、Ti元素或其复合氧化物,可促进粗晶区针状铁素体相变.Mg元素和Ti元素联合添加时,当Mg元素质量分数由0.0042%降低为0.0013%,氧化物类型由MgO转变为Mg_(2)TiO_(4),经统计20个视场内的氧化物数量由408个提高到503个,平均直径由1.37μm减小到1.10μm,显著提高了非均匀形核的比表面积,抑制了晶界铁素体的形成,使t8/5=300 s时粗晶区热模拟试样-20℃冲击吸收能量由43 J提升到127 J.