Effects Of Parameter Variations Research Articles

Effects of Mill Speed and Air Classifier Speed on Performance of an Industrial Ball Mill

Nowadays, ball mills are widely used in cement plants to grind clinker and gypsum to produce cement. The research focuses on the mill speed as well as air classifier speed effect on the two compartment Cement ball mill performance in terms of Blaine, Sulphur trioxide contents, mill power, mill residue and mill residence time. Special importance was assigned to the study of the specific surface area and the surface area production rate, both during the variation with the mill speed and the air classifier speed. Within the content of this work, sampling campaigns were organized around a cement grinding circuit and varying cement ball mill speed as well as an air classifier speed at various dosage feed rate. The fact that such an examination has not been made previously by using industrial data rather than lab scale makes this work unique. The fineness is measured in terms of Blaine number. Mill speed and air classifier speed were the investigating parameters. It was deduced that depending on the speed of mill and air classifier, their effects on Blaine, SO3, mill power and mill performance were varied, ultimately all of them improved the performance of grinding and classification operations. The rapid expansion of ceramic wastes in China has raised great many interests in their sustainable uses in building materials The micro ceramic powder can be taken as a supplementary cementitious material to replace cement up to 40% for tuning the microstructure and mechanical properties of blend cement materials. The Blaine quality dictates strength, setting time and overall performance of cement. Optimum performance of ball mill could potentially refine Blaine fineness, thereby improving the cement quality. This study investigates the effects of separator speed and mill speed on Blaine fineness, mill residue, consumed power. Five speed levels used in closed cycle grinding mill are 200, 400, 600, 800 and 1000 rpm. The capacities were determined to obtain product Blaine surface areas in the limits between 2000 cm2 / gram and Variations in clinker feed rate, mill speed and separator speed could proportionally impact the grain quality of Blaine. When the separator speed is increased from 850 to 900 rpm the Blaine is increased from 2800 to 3000 cm2/g and mill residue decrease from 15 to 10 microns. Therefore, optimum parametric combination could reduce power consumption while improving the cement quality. Knowledge of effects of parametric variations on the quality of end product could be helpful for controlling product quality. Furthermore, proper grinding of clinker produces fine Blaine at first place and reduces the need for recycling of coarse grains.

Unbalanced currents effect on the thermal characteristic and reliability of parallel connected power switches

In many industrial applications, parallel connection of power semiconductor switches is widely used to achieve higher power levels and fault-tolerant operation. But there is a current imbalance between parallel connected switches in practical applications. In this research, the impact of unbalanced currents on the junction temperature and the reliability of parallel connected switches are quantified and analyzed. Markov based reliability model is developed for quantitative assessment of reliability for parallel switches under different current sharing. The Mean Time to Failure (MTTF) is calculated for different conditions to be used as reliability metric for comparison of various conditions. A sensitivity analysis is also presented to show the effect of parameter variation on the junction temperatures of devices and reliability of the system. At last, a downscaled setup has been built up and tested. Experimental results verify the theoretical analysis and confirm procedure. Also, junction temperatures of power semiconductor devices are measured using thermal camera.

Suppression of Residual Vibration in Nonlinear Systems With Temporal Variation and Uncertainty in Parameters by Elimination of the Natural Frequency Component

Abstract A systematic approach is developed for determining a control input for the point-to-point control of an overhead crane that exhibits temporal variation of rope length in addition to damping and nonlinearity, without inducing residual vibration. Complete suppression of the residual vibration is achieved by eliminating the natural frequency component of the cargo from the apparent external force, which is defined to include the effects of damping, nonlinearity, and parameter variation. Furthermore, an effective technique previously proposed by the authors for improving robustness to the modeling error of the natural frequency is extended. Numerical simulation results show that, even when cargo is hoisted up or down during operation, the proposed method realizes accurate positioning of the cargo without inducing residual vibration and sufficiently improves robustness. To the best of our knowledge, this is the first frequency-domain robust open-loop control strategy that ensures a theoretical zero amplitude for residual vibration in the absence of modeling error in nonlinear crane hoisting operation. The developed method is not only a contribution to the realization of low-cost and efficient crane hoisting operation, but is also applicable to the control of other nonlinear damped systems that include time-varying parameters.

Energy, exergy, exergoenvironmental, and economic assessments of the multigeneration system powered by geothermal energy

In this article, a new geothermal powered multigeneration system is proposed and analyzed via energy, exergy, economic, and exergoenvironmental points of view as well as parametric study to see the effects of main parameter variations. This multigeneration system includes a new configuration of the organic Rankine cycle with two evaporators and expanders, heater, NaClO system, and reverse osmosis. The products of this proposed system are electricity, hydrogen, heating, potable water, and salt. Due to theoretical analysis, this system produces 1.264 GWh of electrical energy, 15.93 GWh heating, 1919 Ton salt, 86400 m3 of potable water, and 4.397 × 107 m3 of hydrogen, annually with 60% and 21% of the system energy and exergy efficiencies. The organic Rankine cycle and reverse osmosis systems have the highest and lowest percentage of exergy destruction rates. The economic analysis reveals that the system payback period is 5.3 years. The system's net present value is 668.2 million US$. The exergoenvironmental analysis shows that the exergoenvironmental, environmental damage effectiveness, and the exergy stability factors for the proposed system are 0.86, 4.414, and 0.8, respectively. The parametric study shows that increasing the geo-fluid mass flow rate, increases the system's electrical power production and exergy efficiency while decreases the system exergy efficiency.

Expected seismic performance of gravity dams using machine learning techniques

Methods for the seismic analysis of dams have improved extensively in the last several decades. Advanced numerical models have become more feasible and constitute the basis of improved procedures for design and assessment. A probabilistic framework is required to manage the various sources of uncertainty that may impact system performance and fragility analysis is a promising approach for depicting conditional probabilities of limit state exceedance under such uncertainties. However, the effect of model parameter variation on the seismic fragility analysis of structures with complex numerical models, such as dams, is frequently overlooked due to the costly and time-consuming revaluation of the numerical model. To improve the seismic assessment of such structures by jointly reducing the computational burden, this study proposes the implementation of a polynomial response surface metamodel to emulate the response of the system. The latter will be computationally and visually validated and used to predict the continuous relative maximum base sliding of the dam in order to build fragility functions and show the effect of modelling parameter variation. The resulting fragility functions are used to assess the seismic performance of the dam and formulate recommendations with respect to the model parameters. To establish admissible ranges of the model parameters in line with the current guidelines for seismic safety, load cases corresponding to return periods for the dam classification are used to attain target performance limit states.

MRI-Based Radiomics Analysis for the Pretreatment Prediction of Pathologic Complete Tumor Response to Neoadjuvant Systemic Therapy in Breast Cancer Patients: A Multicenter Study.

Simple SummaryThe prediction of pathologic complete response (pCR) to neo-adjuvant systemic therapy (NST) based on radiological assessment of pretreatment MRI exams in breast cancer patients is not possible to date. In this study, we investigated the value of pretreatment MRI-based radiomics analysis for the prediction of pCR to NST. Radiomics, clinical, and combined models were developed and validated based on MRI exams containing 320 tumors collected from two hospitals. The clinical models significantly outperformed the radiomics models for the prediction of pCR to NST and were of similar or better performance than the combined models. This indicates poor performance of the radiomics features and that in these scenarios the radiomic features did not have an added value for the clinical models developed. Due to previous and current work, we tentatively attribute the lack of significant improvement in clinical models following the addition of radiomics features to the effects of variations in acquisition and reconstruction parameters. The lack of reproducibility data meant this effect could not be analyzed. These results indicate the need for reproducibility studies to preselect reproducible features in order to properly assess the potential of radiomics.This retrospective study investigated the value of pretreatment contrast-enhanced Magnetic Resonance Imaging (MRI)-based radiomics for the prediction of pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients. A total of 292 breast cancer patients, with 320 tumors, who were treated with neo-adjuvant systemic therapy and underwent a pretreatment MRI exam were enrolled. As the data were collected in two different hospitals with five different MRI scanners and varying acquisition protocols, three different strategies to split training and validation datasets were used. Radiomics, clinical, and combined models were developed using random forest classifiers in each strategy. The analysis of radiomics features had no added value in predicting pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients compared with the clinical models, nor did the combined models perform significantly better than the clinical models. Further, the radiomics features selected for the models and their performance differed with and within the different strategies. Due to previous and current work, we tentatively attribute the lack of improvement in clinical models following the addition of radiomics to the effects of variations in acquisition and reconstruction parameters. The lack of reproducibility data (i.e., test-retest or similar) meant that this effect could not be analyzed. These results indicate the need for reproducibility studies to preselect reproducible features in order to properly assess the potential of radiomics.

Analytical Modeling and Performance Analysis of Surface Potential for Junctionless MOSFET

The advancement in semiconductor technology requires small devices with low power consumption. This paper presents an analytical modeling of surface potential for junctionless MOSFET. Parabolic approximation is utilized to find out the surface potential. The effect of device parameter variation on surface potential and electric field has been studied. The variation in gate work function has been investigated for surface potential. Moreover, the consequence of variations in device parameters like drain bias, gate length ratio, radius of silicon pillar and doping concentration are also inspected. It is found that present device shows an excellent behaviour for future VLSI chips. The analytical results are matched with the TCAD results which validates the model.

WITHDRAWN: Characterizing flow due to segmental contraction of the small intestine and their impact on digestion

Abstract A theoretical model for segmental contractions of the small intestine is developed using lubrication method. Here, the nonlinear partial differential equations governing the fluid flow were normalized in viscous regime and solved semi-analytically for a power law fluid under long wavelength approximation on a MatlabTM platform. The segmental contraction was defined as a sinusoid with choice for variation in the wavelength, occlusion and frequency of luminal closure to study the effects of parametric variation (base values of the parameters were chosen as – n = 1.0, f*=6 wave•min-1, t*=T*3/4 sec, L*=20 cm, R*=1 cm, λ*=2 cm, and pocc, max*=0.5) on the flow for fluid of different viscosity, and flow behavior index of 0.5 (pseudo-plastic), 1.0 (Newtonian), 1.2 (dilatants) and 1.5 (dilatants). Pressure was specified as Dirichlet boundary conditions at the ends of the intestinal segment and velocity as no-slip boundary condition on the wall. Flow was characterized by determining the spatial distribution of the pressure, shear stress and flow rate along the length of the intestine during luminal closure at its maximal radial velocity. Study indicates that segmentation leads to the pressurization of the lumen (with a formation of a plateau at the middle) during closure and generation of vacuum during opening of the lumen. For four-wave segmentation, shearing is highest at the 1st and 4th mid-occlusion in comparison to 2nd and 3rd mid-occlusion. Parametric study indicates that the flow is sensitive to – the span of segmentation or wavelength of the wave, occlusion of the wave and frequency of the contraction; with shearing being highest for dilatants. Wavelength has an effect of altering the flow to within the span of the wavelength of the wave with no change in magnitude of shearing. However, contractions show preference for an optimal value of wavelength; above and below this values leads to inefficiency. Shearing is more prominent at higher occlusion (>50%) and frequency (>6Hz). Further, mixing is more prominent at the steep regions of the wave; having intensity of mixing highest for the outer waves in comparison to waves at mid-region of the segmentation. The degree of friction offered to the non-Newtonian fluids increases for increase in frequency, wavelength and occlusion; but less sensitive to flow behavior index. Simulation indicate that the power demand is more when peristalsis is driven at higher frequency (f = 12wpm) in comparison to lower frequency (f = 1wpm). The power demand is found to be greater in segmentation and has the following precedence - frequency, wavelength, flow behavior index, and occlusion (up to 80%). The spatial variation of the mixing parameter, Rm, indicates that the mixing is confined, majorly, at the steep edges of the wave. Further, multiplicity of the wave gives rise to multiple zones of mixing which increases the rate of mixing of the contents. Suggesting that, the segmentation primarily serves the purpose of mixing. In conclusion, we speculate that the segmentation facilitates digestion of the contents by enhancing the mixing, developing to-and-fro motion of the contents during events of periodic opening and closing of the lumen, increasing the enzymatic breakdown by increasing the surface area of solutes and delivering them within the proximity of the enzymes, and absorption.

Dual-band fiber optical parametric amplification in a structure of highly nonlinear photonic crystal fiber

We investigate fiber optical parametric amplification (FOPA) in a structure of an As2S3 core and TeO2 cladding photonic crystal fiber (PCF). Various amplification features such as wavelength area, parametric gain value, and bandwidth are investigated. In order to design the FOPA system with optimal features, effects of different structural parameters variation on optical features of the PCF and parametric gain subsequently are also investigated numerically based on the finite-difference time domain numerical method. Using 15 cm of this fiber and a continuous wave pump laser of 1.1 W, we attain a gain spectrum of 350 nm with a maximum value of 37 dB around 1550 and 1310 nm, which are favored wavelengths in optical telecommunication systems. In fact, our structure ends in a wideband amplifier in an absolutely compact size, which is optimized exactly for optical telecommunication applications.

Parameter variations in personalized electrophysiological models of human heart ventricles.

The objectives of this study were to evaluate the accuracy of personalized numerical simulations of the electrical activity in human ventricles by comparing simulated electrocardiograms (ECGs) with real patients' ECGs and analyzing the sensitivity of the model output to variations in the model parameters. We used standard 12-lead ECGs and up to 224 unipolar body-surface ECGs to record three patients with cardiac resynchronization therapy devices and three patients with focal ventricular tachycardia. Patient-tailored geometrical models of the ventricles, atria, large vessels, liver, and spine were created using computed tomography data. Ten cases of focal ventricular activation were simulated using the bidomain model and the TNNP 2006 cellular model. The population-based values of electrical conductivities and other model parameters were used for accuracy analysis, and their variations were used for sensitivity analysis. The mean correlation coefficient between the simulated and real ECGs varied significantly (from r = 0.29 to r = 0.86) among the simulated cases. A strong mean correlation (r > 0.7) was found in eight of the ten model cases. The accuracy of the ECG simulation varied widely in the same patient depending on the localization of the excitation origin. The sensitivity analysis revealed that variations in the anisotropy ratio, blood conductivity, and cellular apicobasal heterogeneity had the strongest influence on transmembrane potential, while variation in lung conductivity had the greatest influence on body-surface ECGs. Futhermore, the anisotropy ratio predominantly affected the latest activation time and repolarization time dispersion, while the cellular apicobasal heterogeneity mainly affected the dispersion of action potential duration, and variation in lung conductivity mainly led to changes in the amplitudes of ECGs and cardiac electrograms. We also found that the effects of certain parameter variations had specific regional patterns on the cardiac and body surfaces. These observations are useful for further developing personalized cardiac models.

Trigonal warping, satellite Dirac points, and multiple field tuned topological transitions in twisted double bilayer graphene

We show that the valley Chern number of the low energy band in twisted double bilayer graphene can be tuned through two successive topological transitions, where the direct bandgap closes, by changing the electric field perpendicular to the plane of the graphene layers. The two transitions with Chern number changes of -3 and +1 can be explained by the formation of three satellite Dirac points around the central Dirac cone in the moir\'e Brillouin zone due to the presence of trigonal warping. The satellite cones have opposite chirality to the central Dirac cone. Considering the overlap of the bands in energy, which lead to metallic states, we construct the experimentally observable phase diagram of the system in terms of the indirect bandgap and the anomalous valley Hall conductivity. We show that while most of the intermediate phase becomes metallic, there is a narrow parameter regime where the transition through three insulating phases with different quantized valley Hall conductivity can be seen. We systematically study the effects of variations in the model parameters on the phase diagram of the system to reveal the importance of particle-hole asymmetry and trigonal warping in constructing the phase diagram. We also study the effect of changes in interlayer tunneling on this phase diagram.

A Mars Environment Chamber Coupled with Multiple In Situ Spectral Sensors for Mars Exploration.

Laboratory simulation is the only feasible way to achieve Martian environmental conditions on Earth, establishing a key link between the laboratory and Mars exploration. The mineral phases of some Martian surface materials (especially hydrated minerals), as well as their spectral features, are closely related to environmental conditions. Therefore, Martian environment simulation is necessary for Martian mineral detection and analysis. A Mars environment chamber (MEC) coupled with multiple in situ spectral sensors (VIS (visible)-NIR (near-infrared) reflectance spectroscopy, Raman spectroscopy, laser-induced breakdown spectroscopy (LIBS), and UV-VIS emission spectroscopy) was developed at Shandong University at Weihai, China. This MEC is a comprehensive research platform for Martian environmental parameter simulation, regulation, and spectral data collection. Here, the structure, function and performance of the MEC and the coupled spectral sensors were systematically investigated. The spectral characteristics of some geological samples were recorded and the effect of environmental parameter variations (such as gas pressure and temperature) on the spectral features were also acquired by using the in situ spectral sensors under various simulated Martian conditions. CO2 glow discharge plasma was generated and its emission spectra were assigned. The MEC and its tested functional units worked well with good accuracy and repeatability. China is implementing its first Mars mission (Tianwen-1), which was launched on 23 July 2020 and successfully entered into a Mars orbit on 10 February 2021. Many preparatory works such as spectral databases and prediction model building are currently underway using MECs, which will help us build a solid foundation for real Martian spectral data analysis and interpretation.

Brake Noise Reduction Method Based on Monte Carlo Sampling and Particle Swarm Optimization

Brake noise is one of the principal components of vehicle noise and is also one of the most critical measures of vehicle quality. During the braking process, the occurrence of brake noise has a significant relationship with the working conditions of the brake system. In the present study, dynamometer test data and the finite element method (FEM) were used to analyze the direct and indirect effects of variations in the working parameters on the brake noise, and a brake noise reduction method was developed. With this method, Monte Carlo sampling was used to consider variations in the parameters of the brake lining during the braking procedure, and the particle swarm optimization method was used to calculate the optimal parameter combination for the brake lining. A dynamometer test was carried out to validate the effect of optimization on brake noise mitigation.

Repetitive Transcranial Magnetic Stimulation for Obsessive-Compulsive Disorder: A Meta-analysis of Randomized, Sham-Controlled Trials

BackgroundObsessive-compulsive disorder (OCD) is a chronic, disabling mental health condition with limited treatment options available to date. Numerous randomized controlled trials have explored the efficacy of repetitive transcranial magnetic stimulation (rTMS) in OCD. This meta-analysis synthesized data from selected randomized controlled trials and examined the impact of different treatment parameters to generate hypotheses that would direct future randomized controlled trials. MethodsA database search was performed to identify studies published in English up to October 2020. Randomized, sham-controlled studies that used rTMS to treat OCD were included. Effect sizes were calculated using Hedges’ g for pre- to post-treatment Yale-Brown Obsessive Compulsive Scale scores. Subgroup analyses were conducted to assess the effects of variations in rTMS treatment parameters. ResultsA total of 26 studies with 781 participants were included. Overall, rTMS demonstrated a modest effect on reduction of Yale-Brown Obsessive Compulsive Scale scores (Hedges’ g = 0.64, 95% confidence interval = 0.39–0.89; p < .0001). The largest significant effect size was obtained by targeting the bilateral dorsolateral prefrontal cortex. High- and low-frequency rTMS showed comparable effects. Studies with follow-up data suggested that the effects of active rTMS remain significantly superior to those of sham 4 weeks after treatment. ConclusionsThe therapeutic effects of rTMS are superior to those of sham in the treatment of OCD. Targeting the bilateral dorsolateral prefrontal cortex was the most favorable approach in administering rTMS. Further research is required to determine the optimal frequency, total pulses per session, and duration of treatment with rTMS for OCD.

Cotton Wastes Functionalized Biomaterials from Micro to Nano: A Cleaner Approach for a Sustainable Environmental Application.

The exponential increase in textile cotton wastes generation and the ineffective processing mechanism to mitigate its environmental impact by developing functional materials with unique properties for geotechnical applications, wastewater, packaging, and biomedical engineering have become emerging global concerns among researchers. A comprehensive study of a processed cotton fibres isolation technique and their applications are highlighted in this review. Surface modification of cotton wastes fibre increases the adsorption of dyes and heavy metals removal from wastewater. Cotton wastes fibres have demonstrated high adsorption capacity for the removal of recalcitrant pollutants in wastewater. Cotton wastes fibres have found remarkable application in slope amendments, reinforcement of expansive soils and building materials, and a proven source for isolation of cellulose nanocrystals (CNCs). Several research work on the use of cotton waste for functional application rather than disposal has been done. However, no review study has discussed the potentials of cotton wastes from source (Micro-Nano) to application. This review critically analyses novel isolation techniques of CNC from cotton wastes with an in-depth study of a parameter variation effect on their yield. Different pretreatment techniques and efficiency were discussed. From the analysis, chemical pretreatment is considered the most efficient extraction of CNCs from cotton wastes. The pretreatment strategies can suffer variation in process conditions, resulting in distortion in the extracted cellulose’s crystallinity. Acid hydrolysis using sulfuric acid is the most used extraction process for cotton wastes-based CNC. A combined pretreatment process, such as sonication and hydrolysis, increases the crystallinity of cotton-based CNCs. The improvement of the reinforced matrix interface of textile fibres is required for improved packaging and biomedical applications for the sustainability of cotton-based CNCs.

Estimating parking generation rate for Karbala holy city using multi-variables approach

Car parking planning, design, and management processes are very important to all cities and places to ensure efficient traffic system. Estimating the demand of car parking represents the significant start point for the success of these processes. Generally, there are many local and international estimating criteria, but such criteria need continuing update due to many reasons related to socioeconomic factors, lifestyle changes, development in technology, etc. Moreover, the majority of these criteria depend on single parameter for the estimation of parking demand; such as bed or employee for hospital, gross floor area or employee for office, and so on. The main aim of this research is to estimate the park generation rate for specific land uses depend on multivariable to increase the accuracy and limiting the effect of variation in parameters. Statistical analysis was conducted to create predicting models for each land use. The collected data was nominated for Karbala holy city, where different parameters are scaled for different city sectors. Groups of statistical models (i.e., simple, multi linear and nonlinear statistical models, and Weighted Linear Regression (WLR)) were used to create best representative relationship between the number of demands for car parking and multivariable parameters or factors affecting these lands used demands. Resulted statistical models were tested for best fit using statistical indices for model verification. Results disclose the significant of multivariable model compare with simple models. Also, WLR model shows it validity compare with multi-regression model for almost land use models. Consequently, for more accurate estimation the multi variable models are initiated with continuous need for updating.

Buckling analysis of square Functionally Graded Material (FGM) plate using Discrete Kirchhoff Mindlin Triangular (DKMT) element

This paper presents the convergence behavior of Discrete Kirchhoff Mindlin Triangular (DKMT) element in buckling analysis under uniaxial compression of square plate problems. The DKMT element has a good result for a thin plate and a thick plate. For the Functionally Graded Material (FGM) problem, the DKMT element is reformulated. FGM is a graded composite material that has high-temperature and structural flexibility resistance. The numerical results of mechanical buckling of square FGM plate under uniaxial compression using the DKMT element are reported. The critical buckling of the square FGM plate is compared to the reference existing solutions. The effects of parametric variation, such as the type of meshing, boundary conditions, power-law index, and ratio L/h are presented. The results show that the DKMT element gives good results on the buckling analysis of square FGM plate problems.

Propagation of hyperbolic sinusoidal Gaussian beams in uniaxial crystals orthogonal to the optical axis

In this paper, hyperbolic sinusoidal Gaussian(HSG) beam propagates in uniaxial crystal orthogonal to the propagation axis. Received field expression is evaluated analytically based upon Huygens-Fresnel integration. Numerical results are plotted in order to analyze the effect of variations in source beam parameters, crystal refractive index features, and propagation distance. We investigate that beam size and peak intensity of received beam can be managed by adjusting crystal structure. We anticipate that our results will be useful for optical tracking applications.

Variable-Speed PICO Hydel Energy Storage With Synchronverter Control to Emulate Virtual Inertia in Autonomous Microgrids

Autonomous microgrids are potential alternative to grid connectivity for powering remote communities around the globe. A sustainable microgrid with renewables and energy storage having minimum operation and maintenance routines is the most sought option. Batteries are predominantly used to support the stochastic behavior of renewables in such microgrids. However, they are prone to frequent failure and require periodic maintenance, which demands an alternative. Thus, in this article, the renewable powered irrigation system in India was configured to form sustainable pico hydel energy storage (PHES). To enhance the inertia of the microgrid with static sources, virtual inertia capability was induced into PHES by modified synchronverter technology. First, the small-signal modeling approach was presented to derive the closed-loop transfer function of the system. Subsequently, the effect of control parameter variation on system stability and the interaction between the governor and the synchronverter was investigated using eigenvalue analysis. Next, the performance of synchronverter was compared with the established vector control through time-domain simulations in MATLAB/Simulink. The simulation results revealed that the proposed strategy improved the inertial response of PHES and outperformed vector control by reducing peak overshoot, settling time, and steady-state error.

Adaptive hierarchical sliding mode control for full nonlinear dynamics of uncertain ridable ballbots under input saturation

AbstractThis research proposes a nonlinear adaptive controller based on a hierarchical sliding mode control (HSMC) framework to stabilize the operation of a ridable ballbot based on the full nonlinear dynamics (FND). The FND of ballbots is a multiple‐input‐multiple‐output underactuated system with a non‐invertible input matrix. By applying a novel approach to transform the FND into two subsystems, the invertibility of the input matrix of the transformed subsystems can be guaranteed. Thus, an HSMC scheme can be applied to control the ridable ballbot system based on stabilizing the transformed subsystems. In addition, to improve the robustness of HSMC, a new adaptive law is proposed to deal with the effects of exogenous disturbances and parameter variations on the modeled dynamics. Chattering and actuator saturation phenomena are also reduced or avoided with the proposed controller. Comparative simulations are conducted to demonstrate the merit features of the proposed approach and the robustness of the developed control algorithm.