System Identification and Parameter Self-Tuning Controller on Deep-Sea Mining Vehicle

System identification is a quintessential measure for real-time analysis on kinematic characteristics for deep-sea mining vehicle, and thus to enhance the control performance and testing efficiency. In this study, the system identification algorithm, recursive least square method with instrumental variables(IV-RLS), is tailored to model ‘Pioneer I’, a deep-sea mining vehicle which recently completed a 1305-meter-deep sea trial in the Xisha area of the South China Sea in August, 2021. The algorithm operates on the sensor data collected from the trial to obtain the vehicle’s kinematic model and accordingly design the parameter self-tuning controller. The performances demonstrate the accuracy of the model, and prove its generalization capability. With this model, the optimal controller has been designed, the control parameters have been self-tuned, and the response time and robustness of the system have been optimized,which validates the high efficiency on digital modelling for precision control of deep-sea mining vehicles.

Winter wheat yield improvement by genetic gain across different provinces in China

The replacement of winter wheat varieties has contributed significantly to yield improvement worldwide,with remarkable progress in China.Drawing on two sets of data,production yield from the National Bureau of Statistics of China and experimental yield from literature,this study aims to(1)illustrate the increasing patterns of production yield among different provinces from 1978 to 2018 in China,(2)explore the genetic gain in yield and yield relevant traits through the variety replacement based on experimental yield from 1937 to 2016 in China,and(3)compare the yield gap between experimental yield and production yield.The results show that both the production and experimental yields significantly increased along with the variety replacement.The national annual yield increase ratio for the production yield was 1.67%from 1978 to 2018,varying from 0.96%in Sichuan Province to 2.78%in Hebei Province;such ratio for the experimental yield was 1.13%from 1937 to 2016.The yield gap between experimental and production yields decreased from the 1970s to the 2010s.This study reveals significant increases in some yield components consequent to variety replacement,including thousand-grain weight,kernel number per spike,and grain number per square meter;however,no change is shown in spike number per square meter.The biomass and harvest index consistently and significantly increased,whereas the plant height decreased significantly.

Cavitation Diagnostics Based on Self-Tuning VMD for Fluid Machinery with Low-SNR Conditions

Variational mode decomposition(VMD)is a suitable tool for processing cavitation-induced vibration signals and is greatly affected by two parameters:the decomposed number K and penalty factorαunder strong noise interference.To solve this issue,this study proposed self-tuning VMD(SVMD)for cavitation diagnostics in fluid machinery,with a special focus on low signal-to-noise ratio conditions.A two-stage progressive refinement of the coarsely located target penalty factor for SVMD was conducted to narrow down the search space for accelerated decomposition.A hybrid optimized sparrow search algorithm(HOSSA)was developed for optimalαfine-tuning in a refined space based on fault-type-guided objective functions.Based on the submodes obtained using exclusive penalty factors in each iteration,the cavitation-related characteristic frequencies(CCFs)were extracted for diagnostics.The power spectrum correlation coefficient between the SVMD reconstruction and original signals was employed as a stop criterion to determine whether to stop further decomposition.The proposed SVMD overcomes the blindness of setting the mode number K in advance and the drawback of sharing penalty factors for all submodes in fixed-parameter and parameter-optimized VMDs.Comparisons with other existing methods in simulation signal decomposition and in-lab experimental data demonstrated the advantages of the proposed method in accurately extracting CCFs with lower computational cost.SVMD especially enhances the denoising capability of the VMD-based method.

Preweaning period is a critical window for rumen microbial regulation of average daily gain in Holstein heifer calves

Background Rumen bacterial groups can affect growth performance,such as average daily gain(ADG),feed intake,and efficiency.The study aimed to investigate the inter-relationship of rumen bacterial composition,rumen fermentation indicators,serum indicators,and growth performance of Holstein heifer calves with different ADG.Twelve calves were chosen from a trail with 60 calves and divided into higher ADG(HADG,high pre-and post-weaning ADG,n=6)and lower ADG(LADG,low pre-and post-weaning ADG,n=6)groups to investigate differences in bacterial composition and functions and host phenotype.Results During the preweaning period,the relative abundances of propionate producers,including g_norank_f_Butyricicoccaceae,g_Pyramidobacter,and g_norank_f_norank_o_Clostridia_vadin BB60_group,were higher in HADG calves(LDA>2,P<0.05).Enrichment of these bacteria resulted in increased levels of propionate,a gluconeogenic precursor,in preweaning HADG calves(adjusted P<0.05),which consequently raised serum glucose concentrations(adjusted P<0.05).In contrast,the relative abundances of rumen bacteria in post-weaning HADG calves did not exert this effect.Moreover,no significant differences were observed in rumen fermentation parameters and serum indices between the two groups.Conclusions The findings of this study revealed that the preweaning period is the window of opportunity for rumen bacteria to regulate the ADG of calves.

Topological laser on square lattice with gain–loss-induced higher-order corner modes

We investigate the higher-order topological laser in the two-dimensional(2D) coupled-cavity array. By adding staggered on-site gain and loss to the 2D Hermitian array with a trivial phase, the system will emerge degenerate topological corner modes, which are protected by bulk band gap. For such a non-Hermitian model, by adjusting the parameters of the system and introducing the pumping into the cavity at the corner, a single-mode lasing with topological protection emerges.Furthermore, single-mode lasing exists over a wide range of pumping strengths. No matter where the cavity is initially stimulated, after enough time evolution, all the cavities belonging to the topological corner mode can emit a stable laser.

A Stroke-Limitation AMD Control System with Variable Gain and Limited Area for High-Rise Buildings

Collisions between a moving mass and an anti-collision device increase structural responses and threaten structural safety.An active mass damper(AMD)with stroke limitations is often used to avoid collisions.However,a strokelimited AMD control system with a fixed limited area shortens the available AMD stroke and leads to significant control power.To solve this problem,the design approach with variable gain and limited area(VGLA)is proposed in this study.First,the boundary of variable-limited areas is calculated based on the real-time status of the moving mass.The variable gain(VG)expression at the variable limited area is deduced by considering the saturation of AMD stroke.Then,numerical simulations of a stroke-limited AMD control system with VGLA are conducted on a high-rise building structure.These numerical simulations show that the proposed approach has superior strokelimitation performance compared with a stroke-limited AMD control system with a fixed limited area.Finally,the proposed approach is validated through experiments on a four-story steel frame.

基于GAIN-LSTM网络的雷达PRI序列还原及识别方法

开展脉冲重复间隔(Pulse Repetition Interval,PRI)模式识别工作是电子支援系统的一项重要任务。现代复杂电磁环境下,受雷达辐射源部署和接收设备本身影响,雷达脉冲丢失率极高,导致分选后PRI序列调制规律被破坏,现有的PRI模式识别方法准确率不足。针对上述问题,从PRI序列还原角度出发,并结合PRI序列本质是时序序列的特点,提出GAIN-LSTM(Generative Adversarial Imputation Nets and Long Short Term Memory)网络架构,其先对丢失脉冲位置进行补全操作,恢复PRI调制规律,然后对还原后PRI序列进行调制模式识别。仿真结果表明,提出的GAIN-LSTM网络架构在脉冲丢失率70%时仍保持95%的正确识别率。

ANovel Non-Isolated Cubic DC-DC Converter with High Voltage Gain for Renewable Energy Power Generation System

In recent years,switched inductor(SL)technology,switched capacitor(SC)technology,and switched inductor-capacitor(SL-SC)technology have been widely applied to optimize and improve DC-DC boost converters,which can effectively enhance voltage gain and reduce device stress.To address the issue of low output voltage in current renewable energy power generation systems,this study proposes a novel non-isolated cubic high-gain DC-DC converter based on the traditional quadratic DC-DC boost converter by incorporating a SC and a SL-SC unit.Firstly,the proposed converter’s details are elaborated,including its topology structure,operating mode,voltage gain,device stress,and power loss.Subsequently,a comparative analysis is conducted on the voltage gain and device stress between the proposed converter and other high-gain converters.Then,a closed-loop simulation system is constructed to obtain simulation waveforms of various devices and explore the dynamic performance.Finally,an experimental prototype is built,experimental waveforms are obtained,and the experimental dynamic performance and conversion efficiency are analyzed.The theoretical analysis’s correctness is verified through simulation and experimental results.The proposed converter has advantages such as high voltage gain,low device stress,high conversion efficiency,simple control,and wide input voltage range,achieving a good balance between voltage gain,device stress,and power loss.The proposed converter is well-suited for renewable energy systems and holds theoretical significance and practical value in renewable energy applications.It provides an effective solution to the issue of low output voltage in renewable energy power generation systems.

Design of a Low Power Low-Noise Amplifier with Improved Gain/Noise Ratio

This work details the development of a broad-spectrum LNA (Low Noise Amplifier) circuit using a 65 nm CMOS technology. The design incorporates an inductive degeneracy circuit, employing a theoretical approach to enhance gain, minimize noise levels, and uphold low power consumption. The progression includes a shift to a cascode structure to further refine LNA parameters. Ultimately, with a 1.8 V bias, the achieved performance showcases a gain-to-noise figure ratio of 16 dB/0.5 dB, an IIP3 linearity at 5.1 dBm, and a power consumption of 3 mW. This architecture is adept at operating across a wide frequency band spanning from 0.5 GHz to 6 GHz, rendering it applicable in diverse RF scenarios.

Analysis of the Effects of Maternal Body Mass Index and Gestational Weight Gain on Maternal and Neonatal Outcomes in Twin Pregnancy

Objective:To investigate the effects of maternal body mass index(BMI)and gestational weight gain on maternal and neonatal outcomes in twin pregnancies.Methods:Five hundred cases of twin pregnancies were divided into a low body weight group(68 cases),a normal weight group(355 cases),an overweight group(65 cases),and an obesity group(12 cases)according to the World Health Organization(WHO)Body Mass Index(BMI)classification guidelines Results:Comparison of weight gain during different pregnancies revealed that pregnant women were mainly of low weight and average weight.The higher the BMI before pregnancy,the higher the incidence of excessive weight gain during pregnancy.The incidences of gestational diabetes mellitus(GDM)and premature rupture of membranes in women with low weight gain were significantly higher than those in women with average weight gain and high weight gain(P<0.05).The incidences of gestational hypertension,preeclampsia,and anemia in women with high weight gain were significantly higher than those in women with low weight gain and average weight gain(P<0.05).The incidence of neonatal birth weight,fetal distress,and macrosomia in the high weight gain group was significantly higher than those in the low weight gain and average weight gain groups(P<0.05).The birth weight of newborns in low-weight gain mothers was significantly lower than that of normal-weight gain mothers(P<0.05).Conclusion:Poor maternal and infant outcomes were common in women with insufficient or excessive weight gain during pregnancy.Therefore,for women with twin pregnancies,weight management is crucial to ensure maternal and infant health.

Experimental investigation of a passive self-tuning resonator based on a beam-slider structure

This work investigates a self-tuning resonator composed of a slender clamped-clamped steel beam and a freely movable slider.The clamped-clamped beam exhibits hardening nonlinearity when it vibrates in large amplitude,providing a broad bandwidth of dynamic response.The moving slider changes the mass distribution of the whole structure,and provides a passive self-tuning approach for capturing the high-energy orbit of the structure.In the case without inclination,adequate inertial force that mainly depends on the vibration amplitude of the beam and the position of the slider can drive the slider to move from the side toward the centre of the beam.This movement amplifies the beam response when the excitation frequency is below 37 Hz in our prototyped device.In the multi-orbit frequency range(28-37 Hz),the self-tuning and magnification of beam response can be achieved when the slider is initially placed in an appropriate position on the beam.Once the beam is disturbed,however,the desired response in the high-energy orbit can be lost easily and cannot be reacquired without external assistance.In an improved design with a small inclination,the introduced small gravitational component enables the slider to move from the higher side toward the lower side when the beam amplitude is small.This property sacrifices the less efficient self-tuning region below 25 Hz,but can enable the beam to acquire and maintain the high-energy orbit response in the multi-orbit frequency range(28-39 Hz),which is resistant to disturbance.The proposed resonator in this paper not only broadens the frequency bandwidth of dynamic response,but also enables capture and maintenance of the high-energy orbit in a completely passive way.Such a passive self-tuning structure presents an advantage in the design of broadband vibration energy-harvesting systems.

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.

SELF-TUNING WEIGHTED MEASUREMENT FUSION WHITE NOISE DECONVOLUTION ESTIMATOR

For the multi-sensor linear discrete time-invariant stochastic systems with correlated measurement noises and unknown noise statistics,an on-line noise statistics estimator is obtained using the correlation method.Substituting it into the optimal weighted fusion steady-state white noise deconvolution estimator based on the Kalman filtering,a self-tuning weighted measurement fusion white noise deconvolution estimator is presented.By the Dynamic Error System Analysis(DESA) method,it proved that the self-tuning fusion white noise deconvolution estimator converges to the steady-state optimal fusion white noise deconvolution estimator in a realization.Therefore,it has the asymptotically global optimality.A simulation example for the tracking system with 3 sensors and the Bernoulli-Gaussian input white noise shows its effectiveness.

Self-tuning weighted measurement fusion Kalman filter and its convergence

For multisensor systems,when the model parameters and the noise variances are unknown,the consistent fused estimators of the model parameters and noise variances are obtained,based on the system identification algorithm,correlation method and least squares fusion criterion.Substituting these consistent estimators into the optimal weighted measurement fusion Kalman filter,a self-tuning weighted measurement fusion Kalman filter is presented.Using the dynamic error system analysis （DESA） method,the convergence of the self-tuning weighted measurement fusion Kalman filter is proved,i.e.,the self-tuning Kalman filter converges to the corresponding optimal Kalman filter in a realization.Therefore,the self-tuning weighted measurement fusion Kalman filter has asymptotic global optimality.One simulation example for a 4-sensor target tracking system verifies its effectiveness.

Stabilization of CSTR w ith Self-tuning Sliding Mode Controller Using T-S Fuzzy Linearization

A self-tuning reaching law based sliding mode control(SMC)theory is proposed to stabilize the nonlinear continuous stirred tank reactor(CSTR).T-S fuzzy logic is used to build a global fuzzy state-space linear model.Combing the traits of SMC and CSTR,three fuzzy rules can meet the requirements of controlled system.The self-tuning switch control law which can drive the state variables to the sliding surface as soon as possible is designed to ensure the robustness of uncertain fuzzy system.Lyapunov equation is applied to proving the stability of the sliding surface.The simulations show that the proposed approach can achieve desired performance with less chattering problem.

A Design of a PID Self-Tuning Controller Using LabVIEW

In this paper a trial has been made to design a simple self-tuning LabVIEW-based PID controller. The controller uses an open-loop relay test, calculates the tuned parameters in an open loop mode of operation before it updates controller parameters and runs the process as a closed-loop system. The controller reacts on a persistent offset error value as a result of load disturbance or a set point change. Practical results show that such a controller may be recommended to control a variety of industrial processes. A GUI was developed to facilitate control-mode selection, the setting of controller parameters, and the display of control system variables. GUI makes it possible to put the controller in manual or self-tuning mode.

Neural Model-Based Self-Tuning PID Strategy Applied to PEMFC

This paper illustrates the benefits of a self-tuning PID strategy applied to a proton exchange membrane fuel cell system. Controller parameters are updated on-line, at each sampling time, based on an instantaneous linearization of an artificial neural network model of the process and a General Minimum Variance control law. The self-tuning PID scheme allows managing nonlinear behaviors of the system while avoiding heavy computations. The applicability, efficiency and robustness of the proposed control strategy are experimentally confirmed using varying control scenarios. In this aim, the original built-in controller is overridden and the self-tuning PID controller is implemented externally and executed on-line. Experimental results show good performance in setpoint tracking accuracy and robustness against plant/model mismatch. The proposed strategy appears to be a promising alternative to heavy computation nonlinear control strategies and not optimal linear control strategies.

Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement

Background Genomic selection involves choosing as parents those elite individuals with the higher genomic estimated breeding values(GEBV)to accelerate the speed of genetic improvement in domestic animals.But after multi-generation selection,the rate of inbreeding and the occurrence of homozygous harmful alleles might increase,which would reduce performance and genetic diversity.To mitigate the above problems,we can utilize genomic mating(GM)based upon optimal mate allocation to construct the best genotypic combinations in the next generation.In this study,we used stochastic simulation to investigate the impact of various factors on the efficiencies of GM to optimize pairing combinations after genomic selection of candidates in a pig population.These factors included:the algorithm used to derive inbreeding coefficients;the trait heritability(0.1,0.3 or 0.5);the kind of GM scheme(focused average GEBV or inbreeding);the approach for computing the genomic relationship matrix(by SNP or runs of homozygosity(ROH)).The outcomes were compared to three traditional mating schemes(random,positive assortative or negative assortative matings).In addition,the performance of the GM approach was tested on real datasets obtained from a Large White pig breeding population.Results Genomic mating outperforms other approaches in limiting the inbreeding accumulation for the same expected genetic gain.The use of ROH-based genealogical relatedness in GM achieved faster genetic gains than using relatedness based on individual SNPs.The GROH-based GM schemes with the maximum genetic gain resulted in 0.9%-2.6%higher rates of genetic gainΔG,and 13%-83.3%lowerΔF than positive assortative mating regardless of heritability.The rates of inbreeding were always the fastest with positive assortative mating.Results from a purebred Large White pig population,confirmed that GM with ROH-based GRM was more efficient than traditional mating schemes.Conclusion Compared with traditional mating schemes,genomic mating can not only achieve sustainable genetic progress but also effectively control the rates of inbreeding accumulation in the population.Our findings demonstrated that breeders should consider using genomic mating for genetic improvement of pigs.

Self-Tuning Control Techniques for Wind Turbine and Hydroelectric Plant Systems

The interest on the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this aim, self-tuning control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Some of the considered methods were already verified on wind turbine systems, and important advantages may thus derive from the appropriate implementation of the same control schemes for hydroelectric plants. This represents the key point of the work, which provides some guidelines on the design and the application of these control strategies to these energy conversion systems. In fact, it seems that investigations related with both wind and hydraulic energies present a reduced number of common aspects, thus leading to little exchange and share of possible common points. This consideration is particularly valid with reference to the more established wind area when compared to hydroelectric systems. In this way, this work recalls the models of wind turbine and hydroelectric system, and investigates the application of different control solutions. Another important point of this investigation regards the analysis of the exploited benchmark models, their control objectives, and the development of the control solutions. The working conditions of these energy conversion systems will also be taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many installations.

Self-Tuning Control for MIMO Network Systems

The advances in MIMO systems and networking technologies introduced a revolution in recent times, especially in wireless and wired multi-cast (multi-point-to-multi-point) transmission field. In this work, the distributed versions of self-tuning proportional integral plus derivative (SPID) controller and self-tuning proportional plus integral (SPI) controller are described. An explicit rate feedback mechanism is used to design a controller for regulating the source rates in wireless and wired multi-cast networks. The control parameters of the SPID and SPI controllers are determined to ensure the stability of the control loop. Simulations are carried out with wireless and wired multi-cast models, to evaluate the performance of the SPID and SPI controllers and the ensuing results show that SPID scheme yields better performance than SPI scheme;however, it requires more computing time and central processing unit (CPU) resources.