IMPLICIT ITERATIVE METHODS WITH VARIABLE CONTROL PARAMETERS FOR ILL-POSED OPERATOR EQUATIONS

This paper discusses a kind of implicit iterative methods with some variable parameters, which are called control parameters, for solving ill-posed operator equations. The theoretical results show that the new methods always lead to optimal convergence rates and have some other important features, especially the methods can be implemented parallelly.

Integrated Optimization of Structure and Control Parameters for the Height Control System of a Vertical Spindle Cotton Picker

Vertical picking method is a predominate method used to harvest cotton crop.However,a vertical picking method may cause spindle bending of the cotton picker if spindles collide with stones on the cotton field.Thus,how to realize a precise height control of the cotton picker is a crucial issue to be solved.The objective of this study is to design a height control system to avoid the collision.To design it,the mathematical models are established first.Then a multi-objective optimization model represented by structure parameters and control parameters is proposed to take the pressure of chamber without piston,response time and displacement error of the height control system as the opti-mization objectives.An integrated optimization approach that combines optimization via simulation,particle swarm optimization and simulated annealing is proposed to solve the model.Simulation and experimental test results show that the proposed integrated optimization approach can not only reduce the pressure of chamber without piston,but also decrease the response time and displacement error of the height control system.

QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency

In recent years, tunnel boring machines (TBMs) have been widely used in tunnel construction. However, the TBM control parameters set based on operator experience may not necessarily be suitable for certain geological conditions. Hence, a method to optimize TBM control parameters using an improved loss function-based artificial neural network (ILF-ANN) combined with quantum particle swarm optimization (QPSO) is proposed herein. The purpose of this method is to improve the TBM performance by optimizing the penetration and cutterhead rotation speeds. Inspired by the regularization technique, a custom artificial neural network (ANN) loss function based on the penetration rate and rock-breaking specific energy as TBM performance indicators is developed in the form of a penalty function to adjust the output of the network. In addition, to overcome the disadvantage of classical error backpropagation ANNs, i.e., the ease of falling into a local optimum, QPSO is adopted to train the ANN hyperparameters (weight and bias). Rock mass classes and tunneling parameters obtained in real time are used as the input of the QPSO-ILF-ANN, whereas the cutterhead rotation speed and penetration are specified as the output. The proposed method is validated using construction data from the Songhua River water conveyance tunnel project. Results show that, compared with the TBM operator and QPSO-ANN, the QPSO-ILF-ANN effectively increases the TBM penetration rate by 14.85% and 13.71%, respectively, and reduces the rock-breaking specific energy by 9.41% and 9.18%, respectively.

Research on Anti-Fluctuation Control of Winding Tension System Based on Feedforward Compensation

In the fiber winding process,strong disturbance,uncertainty,strong coupling,and fiber friction complicate the winding constant tension control.In order to effectively reduce the influence of these problems on the tension output,this paper proposed a tension fluctuation rejection strategy based on feedforward compensation.In addition to the bias harmonic curve of the unknown state,the tension fluctuation also contains the influence of bounded noise.A tension fluctuation observer(TFO)is designed to cancel the uncertain periodic signal,in which the frequency generator is used to estimate the critical parameter information.Then,the fluctuation signal is reconstructed by a third-order auxiliary filter.The estimated signal feedforward compensates for the actual tension fluctuation.Furthermore,a time-varying parameters fractional-order PID controller(TPFOPID)is realized to attenuate the bounded noise in the fluctuation.Finally,TPFOPID is enhanced by TFO and applied to control a tension control system considering multi-source disturbances.The stability of the method is analyzed by using the Lyapunov theorem.Finally,numerical simulations verify that the proposed scheme improves the tracking ability and robustness of the system in response to tension fluctuations.

Optimization and Configuration of Control Parameters to Enhance Small-signal Stability of Hybrid LCC-MMC HVDC System

This paper investigates the small-signal stability of the hybrid high-voltage direct current(HVDC)transmission system.The system is composed of line commutated converter(LCC)as rectifier and modular multi-level converter(MMC)as inverter under weak AC grid condition.Firstly,the impact of short-circuit ratio(SCR)at inverter side on the system stability is investigated by eigen-analysis,and the key control parameters which have major impact on the dominant mode are identified by the participation factor and sensitivity analysis.Then,considering the quadratic index and damping ratio characteristic,an objective function for evaluating the system stability is developed,and an optimization and configuration method for control parameters is presented by the utilization of Monte Carlo method.The eigenvalue results and the electromagnetic transient(EMT)simulation results show that,with the optimized control parameters,the small-signal stability and the dynamic responses of the hybrid system are greatly improved,and the hybrid system can even operate under weak AC grid condition.

Development of a Novel Feedforward Neural Network Model Based on Controllable Parameters for Predicting Effluent Total Nitrogen

The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To achieve better prediction and control of effluent TN concentration,an efficient prediction model,based on controllable operation parameters,was constructed in a sequencing batch reactor process.Compared with previous models,this model has two main characteristics:①Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability,and②the model prediction accuracy is improved on the basis of a feedforward neural network(FFNN)with algorithm optimization.The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient,and the performance was excellent compared with other models in terms of the correlation coefficient(R).The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters.This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.

Simulation Study on the Controllable Dielectrophoresis Parameters of Graphene

The method of using dielectrophoresis(DEP) to assemble graphene between micro-electrodes has been proven to be simple and efficient. We present an optimization method for the kinetic formula of graphene DEP, and discuss the simulation of the graphene assembly process based on the finite element method. The simulated results illustrate that the accelerated motion of graphene is in agreement with the distribution of the electric field squared gradient. We also conduct research on the controllable parameters of the DEP assembly such as the alternating current(AC) frequency, the shape of micro-electrodes, and the ratio of the gap between electrodes to the characteristic/geometric length of graphene(λ). The simulations based on the Clausius—Mossotti factor reveal that both graphene velocity and direction are influenced by the AC frequency. When graphene is close to the electrodes, the shape of micro-electrodes will exert great influence on the velocity of graphene. Also, λ has a great infiuence on the velocity of graphene. Generally, the velocity of graphene would be greater when λ is in the range of 0.4-0.6. The study is of a theoretical guiding significance in improving the precision and efficiency of the graphene DEP assembly.

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.

A Mathematical Model of COVID-19: Analysis and Identification of Parameters for Better Decision Making

Since the onset of the COVID-19 epidemic, the world has been impressed by two things: The number of people infected and the number of deaths. Here, we propose a mathematical model of the spread of this disease, analyze this model mathematically and determine one or more dominant factors in the propagation of the COVID-19 epidemic. We consider the S-E-I-R epidemic model in the form of ordinary differential equations, in a population structured in susceptibles S, exposed E as caregivers, travelers and assistants at public events, infected I and recovered R classes. Here we decompose the recovered class into two classes: The deaths class D and the class of those who are truly healed H. After the model construction, we have calculated the basic reproduction number R0, which is a function of certain number of parameters like the size of the exposed class E. In our paper, the mathematical analysis, which consists in searching the equilibrium points and studying their stability, is done. The work identifies some parameters on which one can act to control the spread of the disease. The numerical simulations are done and they illustrate our theoretical analysis.

Evaluation of controlled attenuation parameter in assessing hepatic steatosis in patients with autoimmune liver diseases

BACKGROUND Hepatic steatosis commonly occurs in some chronic liver diseases and may affect disease progression.AIM To investigate the performance of controlled attenuation parameter(CAP)for the diagnosis of hepatic steatosis in patients with autoimmune liver diseases(AILDs).METHODS Patients who were suspected of having AILDs and underwent liver biopsy were consistently enrolled.Liver stiffness measurement(LSM)and CAP were performed by transient elastography.The area under the receiver operating characteristic(AUROC)curve was used to evaluate the performance of CAP for diagnosing hepatic steatosis compared with biopsy.RESULTS Among 190 patients with biopsy-proven hepatic steatosis,69 were diagnosed with autoimmune hepatitis(AIH),18 with primary biliary cholangitis(PBC),and 27 with AIH-PBC overlap syndrome.The AUROCs of CAP for the diagnosis of steatosis in AILDS were 0.878(0.791-0.965)for S1,0.764(0.676-0.853)for S2,and 0.821(0.716-0.926)for S3.The CAP value was significantly related to hepatic steatosis grade(P<0.001).Among 69 patients with AIH,the median CAP score was 205.63±47.36 dB/m for S0,258.41±42.83 dB/m for S1,293.00±37.18 dB/m for S2,and 313.60±27.89 dB/m for S3.Compared with patients with nonalcoholic fatty liver disease(NAFLD)presenting with autoimmune markers,patients with AIH concomitant with NAFLD were much older and had higher serum IgG levels and LSM values.CONCLUSION CAP can be used as a noninvasive diagnostic method to evaluate hepatic steatosis in patients with AILDs.Determination of LSM combined with CAP may help to identify patients with AIH concomitant with NAFLD from those with NAFLD with autoimmune phenomena.

Control for Underactuated Reentry Aircraft in Small Angle of Attack

The control problem for under-actuated reentry vehicle like HTV-2 is considered with small angle of attack.The control strategy for an aircraft with positive lateral control departure parameter relies on strong lateral stability,which declines with the decrease of the angle of attack.Thus,to control the lateral-directional motion in a stable state is hard and even impossible in some scenarios where the under-actuated reentry vehicle,like HTV-2,flies in a low angle of attack.To address this problem,the lateral-directional open-loop motion characteristics are analyzed.The results show that in an uncontrolled state,the lateral-directional motion can automatically converge to stabilization thanks to the aerodynamic damping effect.Therefore,a method of turning-off the lateral-directional control and inviting aerodynamic damping to control can achieve stability.The six-degree-of-freedom simulation show that the lateral-directional motion can be stabilized by the aerodynamic damping,and the lateral position error caused by the bank angle deviation is limited near the zero-rise angle of attack.The control strategy is effective.

INTELLIGENT INTEGRATION CONTROL OF ROTATING DISK VIBRATION

The rotating disk is a basic machine part that is u sed widely in industry. The motion equation is transformed into the dynamic equa tion in real modal space. The personating intelligent integration is introduced to improve the existing control method. These modes that affect the transverse vibration mainly are included to simulate the vibration of rotating disk, and two methods are applied separately on condition that the sensor and the ac tuator are collocated and non collocated. The results obtained by all sided si mulations show that the new method can obtain better control effect, especially when the sensor and the actuator are non collocated.

Multiple Elite Individual Guided Piecewise Search-Based Differential Evolution

The differential evolution(DE)algorithm relies mainly on mutation strategy and control parameters'selection.To take full advantage of top elite individuals in terms of fitness and success rates,a new mutation operator is proposed.The control parameters such as scale factor and crossover rate are tuned based on their success rates recorded over past evolutionary stages.The proposed DE variant,MIDE,performs the evolution in a piecewise manner,i.e.,after every predefined evolutionary stages,MIDE adjusts its settings to enrich its diversity skills.The performance of the MIDE is validated on two different sets of benchmarks:CEC 2014 and CEC 2017(special sessions&competitions on real-parameter single objective optimization)using different performance measures.In the end,MIDE is also applied to solve constrained engineering problems.The efficiency and effectiveness of the MIDE are further confirmed by a set of experiments.

Prospective study comparing hepatic steatosis assessment by magnetic resonance imaging and four ultrasound methods in 105 successive patients

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)is becoming a major health problem,resulting in hepatic,metabolic and cardio-vascular morbidity.AIM To evaluate new ultrasonographic tools to detect and measure hepatic steatosis.METHODS We prospectively included 105 patients referred to our liver unit for NAFLD suspicion or follow-up.They underwent ultrasonographic measurement of liver sound speed estimation(SSE)and attenuation coefficient(AC)using Aixplorer MACH 30(Supersonic Imagine,France),continuous controlled attenuation parameter(cCAP)using Fibroscan(Echosens,France)and standard liver ultrasound with hepato-renal index(HRI)calculation.Hepatic steatosis was then classified according to magnetic resonance imaging proton density fat fraction(PDFF).Receiver operating curve(ROC)analysis was performed to evaluate the diagnostic performance in the diagnosis of steatosis.RESULTS Most patients were overweight or obese(90%)and had metabolic syndrome(70%).One third suffered from diabetes.Steatosis was identified in 85 patients(81%)according to PDFF.Twenty-one patients(20%)had advanced liver disease.SSE,AC,cCAP and HRI correlated with PDFF,with respective Spearman correlation coefficient of-0.39,0.42,0.54 and 0.59(P<0.01).Area under the receiver operating characteristic curve(AUROC)for detection of steatosis with HRI was 0.91(0.83-0.99),with the best cut-off value being 1.3(Se=83%,Sp=98%).The optimal cCAP threshold of 275 dB/m,corresponding to the recent EASL-suggested threshold,had a sensitivity of 72%and a specificity of 80%.Corresponding AUROC was 0.79(0.66-0.92).The diagnostic accuracy of cCAP was more reliable when standard deviation was<15 dB/m with an AUC of 0.91(0.83-0.98).An AC threshold of 0.42 dB/cm/MHz had an AUROC was 0.82(0.70-0.93).SSE performed moderately with an AUROC of 0.73(0.62-0.84).CONCLUSION Among all ultrasonographic tools evaluated in this study,including new-generation tools such as cCAP and SSE,HRI had the best performance.It is also the simplest and most available method as most ultrasound scans are equipped with this module.

Convergence Track Based Adaptive Differential Evolution Algorithm(CTbADE)

One of the challenging problems with evolutionary computing algorithms is to maintain the balance between exploration and exploitation capability in order to search global optima.A novel convergence track based adaptive differential evolution(CTbADE)algorithm is presented in this research paper.The crossover rate and mutation probability parameters in a differential evolution algorithm have a significant role in searching global optima.A more diverse population improves the global searching capability and helps to escape from the local optima problem.Tracking the convergence path over time helps enhance the searching speed of a differential evolution algorithm for varying problems.An adaptive powerful parameter-controlled sequences utilized learning period-based memory and following convergence track over time are introduced in this paper.The proposed algorithm will be helpful in maintaining the equilibrium between an algorithm’s exploration and exploitation capability.A comprehensive test suite of standard benchmark problems with different natures,i.e.,unimodal/multimodal and separable/non-separable,was used to test the convergence power of the proposed CTbADE algorithm.Experimental results show the significant performance of the CTbADE algorithm in terms of average fitness,solution quality,and convergence speed when compared with standard differential evolution algorithms and a few other commonly used state-of-the-art algorithms,such as jDE,CoDE,and EPSDE algorithms.This algorithm will prove to be a significant addition to the literature in order to solve real time problems and to optimize computationalmodels with a high number of parameters to adjust during the problem-solving process.

Comparative Study of the Effects of Thermal and Photochemical Accelerated Oxidations on Quality of “Green Type” and “Black Type” French Olive Oils

Oxidative stability of two commercial olive oils of different specificity (green type and black type) has been studied during thermal and photochemical accelerated processes through the evolution of quality indices. It might help to assure a good utilisation of olive oil. In most of works described in literature, they are measured individually. In this study, a Principal Component Analysis (PCA) has been performed to emphasize their variation and describe in concise way the quality and the safety of extra-virgin olive oil after two oxidative stresses. No difference had been detected between both type oils when they are heated. Peroxides, aldehydes and conjugated dienes and trienes were formed but rapidly degraded into final oxidation compounds, mainly acid compounds. During the photochemical process, similar changes occurred slower and the green type oil had shown better stability because of its higher phenolic content. The fatty acids had been more impacted (higher disappearance of monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA)) when the oils were heated than when irradiated. Saturated fatty acids (SFA), MUFA and PUFA were the most relevant indicators to characterize non-oxidized oils and PV characterized the early stage of oil oxidation.

Prevalence and predictors of nonalcoholic fatty liver disease in South Asian women with polycystic ovary syndrome

BACKGROUND Polycystic ovary disease(PCOS)may be a risk factor for nonalcoholic fatty liver disease(NAFLD)due to common pathogenetic pathways,including insulin resistance and obesity.Both PCOS and NAFLD are more severe in South Asian women.Data on NAFLD in South Asian women with PCOS are lacking.AIM To investigate prevalence and predictors of NAFLD and liver fibrosis in PCOS patients from South Asia.METHODS We conducted an observational routine screening program by means of transient elastography(TE)with associated controlled attenuation parameter(CAP).NAFLD was defined as CAP≥288 decibels per meter.Significant liver fibrosis(stage 2 and higher out of 4)was defined as TE measurement≥8.0 kilopascals.Elevated alanine aminotransferase(ALT)was defined as ALT>24 IU/L,as per upper limit of normal reported in South Asian women.Biochemical hyperandrogenism was defined as free androgen index>5.Predictors of NAFLD were determined by logistic regression analysis.RESULTS 101 PCOS patients(mean age 36.3 years)with no significant alcohol intake or viral hepatitis were included.Prevalence of NAFLD and significant liver fibrosis was 39.6% and 6.9%,respectively.Elevated ALT was observed in 40%and 11.5%of patients with and without NAFLD,respectively.After adjusting for duration of PCOS and insulin resistance measured by homeostasis model for assessment of insulin resistance,independent predictors of NAFLD were higher body mass index[adjusted odds ratio(aOR)1.30,95% confidence interval(CI):1.13-1.52],hyperandrogenism(aOR:5.32,95%CI:1.56-18.17)and elevated ALT(aOR:3.54,95%CI:1.10-11.47).Lifetime cardiovascular risk was higher in patients with NAFLD compared to those without NAFLD(0.31±0.11 vs 0.26±0.13).CONCLUSION Despite their young age,NAFLD diagnosed by TE with CAP is a frequent comorbidity in South Asian women with PCOS and is strongly associated with higher body mass index and hyperandrogenism.Non-invasive screening strategies could help early diagnosis and initiation of interventions,including counselling on weight loss,cardiovascular risk stratification and linkage to hepatology care where appropriate.

Creation of radially polarized optical fields with multiple controllable parameters using a vectorial optical field generator

A vectorial optical field generator(VOF-Gen) based on two reflective phase-only liquid crystal spatial light modulators enables the creation of an arbitrary optical complex field. In this work, the capabilities of the VOF-Gen in terms of manipulating the spatial distributions of phase, amplitude, and polarization are experimentally demonstrated by generating a radially polarized optical field consisted of five annular rings, the focusing properties of which are also numerically studied with vectorial diffraction theory. By carefully adjusting the relative amplitude and phase between the adjacent rings, an optical needle field with purely longitudinal polarization can be produced in the focal region of a high numerical aperture lens. The versatile method presented in this work can be easily extended to the generation of a vectorial optical field with any desired complex distributions.

Auto-Tuning Parameters of Fractional PID Controller Design for Air-Conditioning Fan Coil Unit

The traditional integer order PID controller manipulates the air-conditioning fan coil unit(FCU)that offers cooliug and heatins loads to each air-conditioning room in summer and winter,respectivelv.In order to maintain a steady indoor temperature in summer and winter,the control quality cannot meet the related requirements of air-conditioning automation,such as large overshoot,large steady state error.long regulating time,etc.In view of these factors,this paper develops a fractional order PID controller to deal with such problem associated with FCU.Then,by varving mutation factor and crossover rate of basic differential evolution algorithmadaptivelv,a modified differential evolution algorithm(MDEA)is designed to tune the satisfactory values of five parameters of indoor temperature fractional order PID controller.This fractional order PID coutrol system is configured and the corresponding mumerical simulation is conducted by means of MATLAB software.The results indicate that the proposed fractional order PID control svstem and MDEA are reliable and the related control performance indexes meet with the related requirements of comfortable air-conditioning design and control criteria.

Solution and Analysis of the Fuzzy Volterra Integral Equations viaHomotopy Analysis Method

Homotopy Analysis Method(HAM)is semi-analytic method to solve the linear and nonlinear mathematical models which can be used to obtain the approximate solution.The HAM includes an auxiliary parameter,which is an efficient way to examine and analyze the accuracy of linear and nonlinear problems.The main aim of this work is to explore the approximate solutions of fuzzy Volterra integral equations(both linear and nonlinear)with a separable kernel via HAM.This method provides a reliable way to ensure the convergence of the approximation series.A new general form of HAM is presented and analyzed in the fuzzy domain.A qualitative convergence analysis based on the graphical method of a fuzzy HAM is discussed.The solutions sought by the proposed method show that the HAM is easy to implement and computationally quite attractive.Some solutions of fuzzy second kind Volterra integral equations are solved as numerical examples to show the potential of the method.The results also show that HAM provides an easy way to control and modify the convergence area in order to obtain accurate solutions.