Search results for: singular stochastic control model
25377 Meeting the Energy Balancing Needs in a Fully Renewable European Energy System: A Stochastic Portfolio Framework
Authors: Iulia E. Falcan
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The transition of the European power sector towards a clean, renewable energy (RE) system faces the challenge of meeting power demand in times of low wind speed and low solar radiation, at a reasonable cost. This is likely to be achieved through a combination of 1) energy storage technologies, 2) development of the cross-border power grid, 3) installed overcapacity of RE and 4) dispatchable power sources – such as biomass. This paper uses NASA; derived hourly data on weather patterns of sixteen European countries for the past twenty-five years, and load data from the European Network of Transmission System Operators-Electricity (ENTSO-E), to develop a stochastic optimization model. This model aims to understand the synergies between the four classes of technologies mentioned above and to determine the optimal configuration of the energy technologies portfolio. While this issue has been addressed before, it was done so using deterministic models that extrapolated historic data on weather patterns and power demand, as well as ignoring the risk of an unbalanced grid-risk stemming from both the supply and the demand side. This paper aims to explicitly account for the inherent uncertainty in the energy system transition. It articulates two levels of uncertainty: a) the inherent uncertainty in future weather patterns and b) the uncertainty of fully meeting power demand. The first level of uncertainty is addressed by developing probability distributions for future weather data and thus expected power output from RE technologies, rather than known future power output. The latter level of uncertainty is operationalized by introducing a Conditional Value at Risk (CVaR) constraint in the portfolio optimization problem. By setting the risk threshold at different levels – 1%, 5% and 10%, important insights are revealed regarding the synergies of the different energy technologies, i.e., the circumstances under which they behave as either complements or substitutes to each other. The paper concludes that allowing for uncertainty in expected power output - rather than extrapolating historic data - paints a more realistic picture and reveals important departures from results of deterministic models. In addition, explicitly acknowledging the risk of an unbalanced grid - and assigning it different thresholds - reveals non-linearity in the cost functions of different technology portfolio configurations. This finding has significant implications for the design of the European energy mix.Keywords: cross-border grid extension, energy storage technologies, energy system transition, stochastic portfolio optimization
Procedia PDF Downloads 16725376 Accurate and Repeatable Pressure Control for Critical Testing of Advanced Ceramics Using Proportional and Derivative Controller
Authors: Benchalak Muangmeesri
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The purpose of this paper is to discuss how to test the best control performance of a ceramics. Hydraulic press machine (HPM) is the most common shaping of advanced ceramic with products, dimensions, and ceramic products mainly from synthetic powders. A microcontroller can be achieved to control process and has set high standards in the shaping of raw materials in powder form. HPM was proposed to develop a position control system that linked to the embedded controller PIC16F877 via Proportional and Derivative (PD) controller. The model is performed using MATLAB/SIMULINK and the best control performance of an HPM. Finally, PD controller results, showing the best performance as it had the smallest overshoot and highest quality using a microcontroller control.Keywords: ceramics, hydraulic press, microcontroller, PD controller
Procedia PDF Downloads 35425375 The Analysis of One Million Reddit Confessions Corpus: The Use of Emotive Verbs and First Person Singular Pronoun as Linguistic Psychotherapy Features
Authors: Natalia Wojarnik
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The paper aims to present the analysis of a Reddit confessions corpus. The interpretation focuses on the use of emotional language, in particular emotive verbs, in the context of personal pronouns. The analysis of the linguistic properties answers the question of what the Reddit users confess about and who is the subject of confessions. The study reveals that the specific language patterns used in Reddit confessions reflect the language of depression and the language used by patients during different stages of their psychotherapy sessions. The paper concludes that Reddit users are more willing to confess about their own experiences, not rarely very private and intimate, extensively using the first person singular pronoun I. It indicates that the Reddit users use the language of depression and the language used by psychotherapy patients. The language they use is very emotionally impacted and includes many emotive verbs such as want, feel, need, hate, love. This finding in Reddit confessions correlates with the extensive use of stative affective verbs in the first stages of the psychotherapy sessions. Lastly, the paper refers to the positive and negative lexicon and helps determine how online posts can serve as a depression detector and “talking cure” for the users.Keywords: confessions, emotional language, emotive verbs, pronouns, first person pronoun, language of depression, depression detection, psychotherapy language
Procedia PDF Downloads 11925374 Non-Singular Gravitational Collapse of a Homogeneous Scalar Field in Deformed Phase Space
Authors: Amir Hadi Ziaie
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In the present work, we revisit the collapse process of a spherically symmetric homogeneous scalar field (in FRW background) minimally coupled to gravity, when the phase-space deformations are taken into account. Such a deformation is mathematically introduced as a particular type of noncommutativity between the canonical momenta of the scale factor and of the scalar field. In the absence of such deformation, the collapse culminates in a spacetime singularity. However, when the phase-space is deformed, we find that the singularity is removed by a non-singular bounce, beyond which the collapsing cloud re-expands to infinity. More precisely, for negative values of the deformation parameter, we identify the appearance of a negative pressure, which decelerates the collapse to finally avoid the singularity formation. While in the un-deformed case, the horizon curve monotonically decreases to finally cover the singularity, in the deformed case the horizon has a minimum value that this value depends on deformation parameter and initial configuration of the collapse. Such a setting predicts a threshold mass for black hole formation in stellar collapse and manifests the role of non-commutative geometry in physics and especially in stellar collapse and supernova explosion.Keywords: gravitational collapse, non-commutative geometry, spacetime singularity, black hole physics
Procedia PDF Downloads 34225373 T-S Fuzzy Modeling Based on Power Coefficient Limit Nonlinearity Applied to an Isolated Single Machine Load Frequency Deviation Control
Authors: R. S. Sheu, H. Usman, M. S. Lawal
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Takagi-Sugeno (T-S) fuzzy model based control of a load frequency deviation in a single machine with limit nonlinearity on power coefficient is presented in the paper. Two T-S fuzzy rules with only rotor angle variable as input in the premise part, and linear state space models in the consequent part involving characteristic matrices determined from limits set on the power coefficient constant are formulated, state feedback control gains for closed loop control was determined from the formulated Linear Matrix Inequality (LMI) with eigenvalue optimization scheme for asymptotic and exponential stability (speed of esponse). Numerical evaluation of the closed loop object was carried out in Matlab. Simulation results generated of both the open and closed loop system showed the effectiveness of the control scheme in maintaining load frequency stability.Keywords: T-S fuzzy model, state feedback control, linear matrix inequality (LMI), frequency deviation control
Procedia PDF Downloads 39625372 Joint Optimal Pricing and Lot-Sizing Decisions for an Advance Sales System under Stochastic Conditions
Authors: Maryam Ghoreishi, Christian Larsen
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In this paper, we investigate the effect of stochastic inputs on problem of joint optimal pricing and lot-sizing decisions where the inventory cycle is divided into advance and spot sales periods. During the advance sales period, customer can make reservations while customer with reservations can cancel their order. However, during the spot sales period customers receive the order as soon as the order is placed, but they cannot make any reservation or cancellation during that period. We assume that the inter arrival times during the advance sales and spot sales period are exponentially distributed where the arrival rate is decreasing function of price. Moreover, we assume that the number of cancelled reservations is binomially distributed. In addition, we assume that deterioration process follows an exponential distribution. We investigate two cases. First, we consider two-state case where we find the optimal price during the spot sales period and the optimal price during the advance sales period. Next, we develop a generalized case where we extend two-state case also to allow dynamic prices during the spot sales period. We apply the Markov decision theory in order to find the optimal solutions. In addition, for the generalized case, we apply the policy iteration algorithm in order to find the optimal prices, the optimal lot-size and maximum advance sales amount.Keywords: inventory control, pricing, Markov decision theory, advance sales system
Procedia PDF Downloads 32325371 Accelerated Structural Reliability Analysis under Earthquake-Induced Tsunamis by Advanced Stochastic Simulation
Authors: Sai Hung Cheung, Zhe Shao
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Recent earthquake-induced tsunamis in Padang, 2004 and Tohoku, 2011 brought huge losses of lives and properties. Maintaining vertical evacuation systems is the most crucial strategy to effectively reduce casualty during the tsunami event. Thus, it is of our great interest to quantify the risk to structural dynamic systems due to earthquake-induced tsunamis. Despite continuous advancement in computational simulation of the tsunami and wave-structure interaction modeling, it still remains computationally challenging to evaluate the reliability (or its complement failure probability) of a structural dynamic system when uncertainties related to the system and its modeling are taken into account. The failure of the structure in a tsunami-wave-structural system is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this paper, an approach based on a novel integration of the Subset Simulation algorithm and a recently proposed moving least squares response surface approach for stochastic sampling is proposed. The effectiveness of the proposed approach is discussed by comparing its results with those obtained from the Subset Simulation algorithm without using the response surface approach.Keywords: response surface model, subset simulation, structural reliability, Tsunami risk
Procedia PDF Downloads 38125370 Model Predictive Control Applied to Thermal Regulation of Thermoforming Process Based on the Armax Linear Model and a Quadratic Criterion Formulation
Authors: Moaine Jebara, Lionel Boillereaux, Sofiane Belhabib, Michel Havet, Alain Sarda, Pierre Mousseau, Rémi Deterre
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Energy consumption efficiency is a major concern for the material processing industry such as thermoforming process and molding. Indeed, these systems should deliver the right amount of energy at the right time to the processed material. Recent technical development, as well as the particularities of the heating system dynamics, made the Model Predictive Control (MPC) one of the best candidates for thermal control of several production processes like molding and composite thermoforming to name a few. The main principle of this technique is to use a dynamic model of the process inside the controller in real time in order to anticipate the future behavior of the process which allows the current timeslot to be optimized while taking future timeslots into account. This study presents a procedure based on a predictive control that brings balance between optimality, simplicity, and flexibility of its implementation. The development of this approach is progressive starting from the case of a single zone before its extension to the multizone and/or multisource case, taking thus into account the thermal couplings between the adjacent zones. After a quadratic formulation of the MPC criterion to ensure the thermal control, the linear expression is retained in order to reduce calculation time thanks to the use of the ARMAX linear decomposition methods. The effectiveness of this approach is illustrated by experiment and simulation.Keywords: energy efficiency, linear decomposition methods, model predictive control, mold heating systems
Procedia PDF Downloads 27025369 Informed Urban Design: Minimizing Urban Heat Island Intensity via Stochastic Optimization
Authors: Luis Guilherme Resende Santos, Ido Nevat, Leslie Norford
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The Urban Heat Island (UHI) is characterized by increased air temperatures in urban areas compared to undeveloped rural surrounding environments. With urbanization and densification, the intensity of UHI increases, bringing negative impacts on livability, health and economy. In order to reduce those effects, it is required to take into consideration design factors when planning future developments. Given design constraints such as population size and availability of area for development, non-trivial decisions regarding the buildings’ dimensions and their spatial distribution are required. We develop a framework for optimization of urban design in order to jointly minimize UHI intensity and buildings’ energy consumption. First, the design constraints are defined according to spatial and population limits in order to establish realistic boundaries that would be applicable in real life decisions. Second, the tools Urban Weather Generator (UWG) and EnergyPlus are used to generate outputs of UHI intensity and total buildings’ energy consumption, respectively. Those outputs are changed based on a set of variable inputs related to urban morphology aspects, such as building height, urban canyon width and population density. Lastly, an optimization problem is cast where the utility function quantifies the performance of each design candidate (e.g. minimizing a linear combination of UHI and energy consumption), and a set of constraints to be met is set. Solving this optimization problem is difficult, since there is no simple analytic form which represents the UWG and EnergyPlus models. We therefore cannot use any direct optimization techniques, but instead, develop an indirect “black box” optimization algorithm. To this end we develop a solution that is based on stochastic optimization method, known as the Cross Entropy method (CEM). The CEM translates the deterministic optimization problem into an associated stochastic optimization problem which is simple to solve analytically. We illustrate our model on a typical residential area in Singapore. Due to fast growth in population and built area and land availability generated by land reclamation, urban planning decisions are of the most importance for the country. Furthermore, the hot and humid climate in the country raises the concern for the impact of UHI. The problem presented is highly relevant to early urban design stages and the objective of such framework is to guide decision makers and assist them to include and evaluate urban microclimate and energy aspects in the process of urban planning.Keywords: building energy consumption, stochastic optimization, urban design, urban heat island, urban weather generator
Procedia PDF Downloads 13025368 Convergence Analysis of Reactive Power Based Schemes Used in Sensorless Control of Induction Motors
Authors: N. Ben Si Ali, N. Benalia, N. Zerzouri
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Many electronic drivers for the induction motor control are based on sensorless technologies. Speed and torque control is usually attained by application of a speed or position sensor which requires the additional mounting space, reduce the reliability and increase the cost. This paper seeks to analyze dynamical performances and sensitivity to motor parameter changes of reactive power based technique used in sensorless control of induction motors. Validity of theoretical results is verified by simulation.Keywords: adaptive observers, model reference adaptive system, RP-based estimator, sensorless control, stability analysis
Procedia PDF Downloads 54425367 Black Box Model and Evolutionary Fuzzy Control Methods of Coupled-Tank System
Authors: S. Yaman, S. Rostami
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In this study, a black box modeling of the coupled-tank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutionary computation method, genetic algorithm. All tuned controllers are applied to the fuzzy model of the coupled-tank experimental setup and analyzed under the different reference input values. According to the results, it is seen that function tuner method demonstrates better robust control performance and guarantees the closed loop stability.Keywords: function tuner method (FTM), fuzzy modeling, fuzzy PID controller, genetic algorithm (GA)
Procedia PDF Downloads 30725366 A TgCNN-Based Surrogate Model for Subsurface Oil-Water Phase Flow under Multi-Well Conditions
Authors: Jian Li
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The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase
Procedia PDF Downloads 8525365 Realization of a Temperature Based Automatic Controlled Domestic Electric Boiling System
Authors: Shengqi Yu, Jinwei Zhao
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This paper presents a kind of analog circuit based temperature control system, which is mainly composed by threshold control signal circuit, synchronization signal circuit and trigger pulse circuit. Firstly, the temperature feedback signal function is realized by temperature sensor TS503F3950E. Secondly, the main control circuit forms the cycle controlled pulse signal to control the thyristor switching model. Finally two reverse paralleled thyristors regulate the output power by their switching state. In the consequence, this is a modernized and energy-saving domestic electric heating system.Keywords: time base circuit, automatic control, zero-crossing trigger, temperature control
Procedia PDF Downloads 47825364 Fractional-Order PI Controller Tuning Rules for Cascade Control System
Authors: Truong Nguyen Luan Vu, Le Hieu Giang, Le Linh
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The fractional–order proportional integral (FOPI) controller tuning rules based on the fractional calculus for the cascade control system are systematically proposed in this paper. Accordingly, the ideal controller is obtained by using internal model control (IMC) approach for both the inner and outer loops, which gives the desired closed-loop responses. On the basis of the fractional calculus, the analytical tuning rules of FOPI controller for the inner loop can be established in the frequency domain. Besides, the outer loop is tuned by using any integer PI/PID controller tuning rules in the literature. The simulation study is considered for the stable process model and the results demonstrate the simplicity, flexibility, and effectiveness of the proposed method for the cascade control system in compared with the other methods.Keywords: Bode’s ideal transfer function, fractional calculus, fractional–order proportional integral (FOPI) controller, cascade control system
Procedia PDF Downloads 37525363 Circadian Disruption in Polycystic Ovary Syndrome Model Rats
Authors: Fangfang Wang, Fan Qu
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Polycystic ovary syndrome (PCOS), the most common endocrinopathy among women of reproductive age, is characterized by ovarian dysfunction, hyperandrogenism and reduced fecundity. The aim of this study is to investigate whether the circadian disruption is involved in pathogenesis of PCOS in androgen-induced animal model. We established a rat model of PCOS using single subcutaneous injection with testosterone propionate on the ninth day after birth, and confirmed their PCOS-like phenotypes with vaginal smears, ovarian hematoxylin and eosin (HE) staining and serum androgen measurement. The control group rats received the vehicle only. Gene expression was detected by real-time quantitative PCR. (1) Compared with control group, PCOS model rats of 10-week group showed persistently keratinized vaginal cells, while all the control rats showed at least two consecutive estrous cycles. (2) Ovarian HE staining and histological examination showed that PCOS model rats of 10-week group presented many cystic follicles with decreased numbers of granulosa cells and corpora lutea in their ovaries, while the control rats had follicles with normal layers of granulosa cells at various stages of development and several generations of corpora lutea. (3) In the 10-week group, serum free androgen index was notably higher in PCOS model rats than controls. (4) Disturbed mRNA expression patterns of core clock genes were found in ovaries of PCOS model rats of 10-week group. Abnormal expression of key genes associated with circadian rhythm in ovary may be one of the mechanisms for ovarian dysfunction in PCOS model rats induced by androgen.Keywords: polycystic ovary syndrome, androgen, animal model, circadian disruption
Procedia PDF Downloads 22925362 Risk-Based Regulation as a Model of Control in the South African Meat Industry
Authors: R. Govender, T. C. Katsande, E. Madoroba, N. M. Thiebaut, D. Naidoo
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South African control over meat safety is managed by the Department of Agriculture, Forestry and Fisheries (DAFF). Veterinary services department in each of the nine provinces in the country is tasked with overseeing the farm and abattoir segments of the meat supply chain. Abattoirs are privately owned. The number of abattoirs over the years has increased. This increase has placed constraints on government resources required to monitor these abattoirs. This paper presents empirical research results on the hygienic processing of meat in high and low throughout abattoirs. This paper presents a case for the adoption of risk-based regulation as a method of government control over hygiene and safe meat processing at abattoirs in South Africa. Recommendations are made to the DAFF regarding policy considerations on risk-based regulation as a model of control in South Africa.Keywords: risk-based regulation, abattoir, food control, meat safety
Procedia PDF Downloads 31125361 Technical Efficiency of Small-Scale Honey Producer in Ethiopia: A Stochastic Frontier Analysis
Authors: Kaleb Shiferaw, Berhanu Geberemedhin
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Ethiopian farmers have a long tradition of beekeeping and the country has huge potential for honey production. However traditional mode of production still dominates the sub sector which negatively affect the total production and productivity. A number of studies have been conducted to better understand the working honey production, however, none of them systematically investigate the extent of technical efficiency of the sub-sector. This paper uses Stochastic Frontier production model to quantifying the extent of technical efficiency and identify exogenous determinant of inefficiency. The result showed that consistent with other studies traditional practice dominate small scale honey production in Ethiopia. The finding also revealed that use of purchased inputs such as bee forage and other supplement is very limited among honey producers indicating that natural bee forage is the primary source of bee forage. The immediate consequence of all these is low production and productivity. The number of hives the household owns, whether the household used improved apiculture technologies, availability of natural forest which is the primary sources of nectar for bees and amount of land owned by the households were found to have a significant influence on the amount of honey produced by beekeeper. Our result further showed that the mean technical efficiency of honey producers is 0.79 implying that, on average honey producer produce 80 percent of the maximum output. The implication is that 20 percent of the potential output is lost due to technical inefficiency. Number of hives owned by a honey produces, distance to district town-a proxy to market access, household wealth, and whether the household head has a leadership role in the PA affect the technical efficiency of honey producers. The finding suggest that policies that aim to expand the use of improved hives is expected to increase the honey production at household level. The result also suggest that investment on rural infrastructure would be instrumental in improving technical efficiency of honey producer.Keywords: small-scale honey producer, Ethiopia, technical efficiency in apiculture, stochastic frontier analysis
Procedia PDF Downloads 23425360 Implemented Cascade with Feed Forward by Enthalpy Balance Superheated Steam Temperature Control for a Boiler with Distributed Control System
Authors: Kanpop Saion, Sakreya Chitwong
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Control of superheated steam temperature in the steam generation is essential for the efficiency safety and increment age of the boiler. Conventional cascade PID temperature control in the super heater is known to be efficient to compensate disturbance. However, the complex of thermal power plant due to nonlinearity, load disturbance and time delay of steam of superheater system is bigger than other control systems. The cascade loop with feed forward steam temperature control with energy balance compensator using thermodynamic model has been used for the compensation the complex structure of superheater. In order to improve the performance of steam temperature control. The experiment is implemented for 100% load steady and load changing state. The cascade with feed forward with energy balance steam temperature control has stabilized the system as well.Keywords: cascade with feed forward, boiler, superheated steam temperature control, enthalpy balance
Procedia PDF Downloads 30525359 Controlling the Expense of Political Contests Using a Modified N-Players Tullock’s Model
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This work introduces a generalization of the classical Tullock’s model of one-stage contests under complete information with multiple unlimited numbers of contestants. In classical Tullock’s model, the contest winner is not necessarily the highest bidder. Instead, the winner is determined according to a draw in which the winning probabilities are the relative contestants’ efforts. The Tullock modeling fits well political contests, in which the winner is not necessarily the highest effort contestant. This work presents a modified model which uses a simple non-discriminating rule, namely, a parameter to influence the total costs planned for an election, for example, the contest designer can control the contestants' efforts. The winner pays a fee, and the losers are reimbursed the same amount. Our proposed model includes a mechanism that controls the efforts exerted and balances competition, creating a tighter, less predictable and more interesting contest. Additionally, the proposed model follows the fairness criterion in the sense that it does not alter the contestants' probabilities of winning compared to the classic Tullock’s model. We provide an analytic solution for the contestant's optimal effort and expected reward.Keywords: contests, Tullock's model, political elections, control expenses
Procedia PDF Downloads 14325358 A Kolmogorov-Smirnov Type Goodness-Of-Fit Test of Multinomial Logistic Regression Model in Case-Control Studies
Authors: Chen Li-Ching
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The multinomial logistic regression model is used popularly for inferring the relationship of risk factors and disease with multiple categories. This study based on the discrepancy between the nonparametric maximum likelihood estimator and semiparametric maximum likelihood estimator of the cumulative distribution function to propose a Kolmogorov-Smirnov type test statistic to assess adequacy of the multinomial logistic regression model for case-control data. A bootstrap procedure is presented to calculate the critical value of the proposed test statistic. Empirical type I error rates and powers of the test are performed by simulation studies. Some examples will be illustrated the implementation of the test.Keywords: case-control studies, goodness-of-fit test, Kolmogorov-Smirnov test, multinomial logistic regression
Procedia PDF Downloads 45525357 Performance Investigation of UAV Attitude Control Based on Modified PI-D and Nonlinear Dynamic Inversion
Authors: Ebrahim Hassan Kapeel, Ahmed Mohsen Kamel, Hossan Hendy, Yehia Z. Elhalwagy
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Interest in autopilot design has been raised intensely as a result of recent advancements in Unmanned Aerial vehicles (UAVs). Due to the enormous number of applications that UAVs can achieve, the number of applied control theories used for them has increased in recent years. These small fixed-wing UAVs are suffering high non-linearity, sensitivity to disturbances, and coupling effects between their channels. In this work, the nonlinear dynamic inversion (NDI) control lawisdesigned for a nonlinear small fixed-wing UAV model. The NDI is preferable for varied operating conditions, there is no need for a scheduling controller. Moreover, it’s applicable for high angles of attack. For the designed flight controller validation, a nonlinear Modified PI-D controller is performed with our model. A comparative study between both controllers is achieved to evaluate the NDI performance. Simulation results and analysis are proposed to illustrate the effectiveness of the designed controller based on NDI.Keywords: UAV dynamic model, attitude control, nonlinear PID, dynamic inversion
Procedia PDF Downloads 10825356 Joint Space Hybrid Force/Position Control of 6-DoF Robot Manipulator Using Neural Network
Authors: Habtemariam Alemu
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It has been known that the performance of position and force control is highly affected by both robot dynamic and environment stiffness uncertainties. In this paper, joint space hybrid force and position control strategy with self-selecting matrix using artificial neural network compensator is proposed. The objective of the work is to improve controller robustness by applying a neural network technique in order to compensate the effect of uncertainties in the robot model. Simulation results for a 6 degree of freedom (6-DoF) manipulator and different types of environments showed the effectiveness of the suggested approach. 6-DoF Puma 560 family robot manipulator is chosen as industrial robot and its efficient dynamic model is designed using Matlab/SimMechanics library.Keywords: robot manipulator, force/position control, artificial neural network, Matlab/Simulink
Procedia PDF Downloads 51125355 Stochastic Response of an Airfoil and Its Effects on Limit Cycle Oscillations’ Behavior under Stall Flutter Regime
Authors: Ketseas Dimitris
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In this work, we investigate the effect of noise on a classical two-degree-of-freedom pitch-plunge aeroelastic system. The inlet velocity of the flow is modelled as a stochastically varying parameter by the Ornstein-Uhlenbeck (OU) stochastic process. The system is a 2D airfoil, and the elastic problem is simulated using linear springs. We study the manifestation of Limit Cycle Oscillations (LCO) that correspond to the varying fluid velocity under the dynamic stall regime. We aim to delve into the unexplored facets of the classical pitch-plunge aeroelastic system, seeking a comprehensive understanding of how parametric noise influences the occurrence of LCO and expands the boundaries of its known behavior.Keywords: aerodynamics, aeroelasticity, computational fluid mechanics, stall flutter, stochastical processes, limit cycle oscillation
Procedia PDF Downloads 6025354 PID Control of Quad-Rotor Unnamed Vehicle Based on Lagrange Approach Modelling
Authors: A. Benbouali, H. Saidi, A. Derrouazin, T. Bessaad
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Aerial robotics is a very exciting research field dealing with a variety of subjects, including the attitude control. This paper deals with the control of a four rotor vertical take-off and landing (VTOL) Unmanned Aerial Vehicle. The paper presents a mathematical model based on the approach of Lagrange for the flight control of an autonomous quad-rotor. It also describes the controller architecture which is based on PID regulators. The control method has been simulated in closed loop in different situations. All the calculation stages and the simulation results have been detailed.Keywords: quad-rotor, lagrange approach, proportional integral derivate (PID) controller, Matlab/Simulink
Procedia PDF Downloads 39825353 Mobile Robot Manipulator Kinematics Motion Control Analysis with MATLAB/Simulink
Authors: Wayan Widhiada, Cok Indra Partha, Gusti Ngurah Nitya Santhiarsa
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The purpose of this paper is to investigate the sophistication of the use of Proportional Integral and Derivative Control to control the kinematic motion of the mobile robot manipulator. Simulation and experimental methods will be used to investigate the sophistication of PID control to control the mobile robot arm in the collection and placement of several kinds of objects quickly, accurately and correctly. Mathematical modeling will be done by utilizing the integration of Solidworks and MATLAB / Simmechanics software. This method works by converting the physical model file into the xml file. This method is easy, fast and accurate done in modeling and design robotics. The automatic control design of this robot manipulator will be validated in simulations and experimental in control labs as evidence that the mobile robot manipulator gripper control design can achieve the best performance such as the error signal is lower than 5%, small overshoot and get steady signal response as quickly.Keywords: control analysis, kinematics motion, mobile robot manipulator, performance
Procedia PDF Downloads 40425352 Effects of Transtheoretical Model in Obese and Overweight Women Nutritional Behavior Change and Lose Weight
Authors: Abdmohammad Mousavi, Mohsen Shams, Mehdi Akbartabar Toori, Ali Mousavizadeh, Mohammad Ali Morowatisharifabad
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The effectiveness of Transtheoretical Model (TTM) on nutritional behavior change and lose weight has been subject to questions by some studies. The objective of this study was to determine the effect of nutritional behavior change and lose weight interventions based on TTM in obese and overweight women. This experimental study that was a 8 months trial nutritional behavior change and weight loss program based on TTM with two conditions and pre–post intervention measurements weight mean. 299 obese and overweight 20-44 years old women were selected from two health centers include training (142) and control (157) groups in Yasuj, a city in south west of Iran. Data were analyzed using paired T-test and One–Way ANOVA tests. In baseline, adherence with nutritional healthy behavior in training group(9.4%) compare with control(38.8%) were different significantly(p=.003), weight mean of training(Mean=78.02 kg, SD=11.67) compared with control group(Mean=77.23 kg, SD=10.25) were not (P=.66). In post test, adherence with nutritional healthy behavior in training group(70.1%) compare with control (37.4%) were different significantly (p=.000), weight mean of training (Mean=74.65 kg, SD=10.93, p=.000) compare with pre test were different significantly and control (Mean=77.43 kg, SD=10.43, p=.411) were not. The training group has lost 3.37 kg weight, whereas the control group has increased .2 kg weight. These results supported the applicability of the TTM for women weight lose intervention.Keywords: nutritional behavior, Transtheoretical Model, weight lose, women
Procedia PDF Downloads 48225351 On Energy Condition Violation for Shifting Negative Mass Black Holes
Authors: Manuel Urueña Palomo
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In this paper, we introduce the study of a new solution to gravitational singularities by violating the energy conditions of the Penrose Hawking singularity theorems. We consider that a shift to negative energies, and thus, to negative masses, takes place at the event horizon of a black hole, justified by the original, singular and exact Schwarzschild solution. These negative energies are supported by relativistic particle physics considering the negative energy solutions of the Dirac equation, which states that a time transformation shifts to a negative energy particle. In either general relativity or full Newtonian mechanics, these negative masses are predicted to be repulsive. It is demonstrated that the model fits actual observations, and could possibly clarify the size of observed and unexplained supermassive black holes, when considering the inflation that would take place inside the event horizon where massive particles interact antigravitationally. An approximated solution of the model proposed could be simulated in order to compare it with these observations.Keywords: black holes, CPT symmetry, negative mass, time transformation
Procedia PDF Downloads 14825350 Parametrical Simulation of Sheet Metal Forming Process to Control the Localized Thinning
Authors: Hatem Mrad, Alban Notin, Mohamed Bouazara
Abstract:
Sheet metal forming process has a multiple successive steps starting from sheets fixation to sheets evacuation. Often after forming operation, the sheet has defects requiring additional corrections steps. For example, in the drawing process, the formed sheet may have several defects such as springback, localized thinning and bends. All these defects are directly dependent on process, geometric and material parameters. The prediction and elimination of these defects requires the control of most sensitive parameters. The present study is concerned with a reliable parametric study of deep forming process in order to control the localized thinning. The proposed approach will be based on stochastic finite element method. Especially, the polynomial Chaos development will be used to establish a reliable relationship between input (process, geometric and material parameters) and output variables (sheet thickness). The commercial software Abaqus is used to conduct numerical finite elements simulations. The automatized parametrical modification is provided by coupling a FORTRAN routine, a PYTHON script and input Abaqus files.Keywords: sheet metal forming, reliability, localized thinning, parametric simulation
Procedia PDF Downloads 42125349 Efficient Chiller Plant Control Using Modern Reinforcement Learning
Authors: Jingwei Du
Abstract:
The need of optimizing air conditioning systems for existing buildings calls for control methods designed with energy-efficiency as a primary goal. The majority of current control methods boil down to two categories: empirical and model-based. To be effective, the former heavily relies on engineering expertise and the latter requires extensive historical data. Reinforcement Learning (RL), on the other hand, is a model-free approach that explores the environment to obtain an optimal control strategy often referred to as “policy”. This research adopts Proximal Policy Optimization (PPO) to improve chiller plant control, and enable the RL agent to collaborate with experienced engineers. It exploits the fact that while the industry lacks historical data, abundant operational data is available and allows the agent to learn and evolve safely under human supervision. Thanks to the development of language models, renewed interest in RL has led to modern, online, policy-based RL algorithms such as the PPO. This research took inspiration from “alignment”, a process that utilizes human feedback to finetune the pretrained model in case of unsafe content. The methodology can be summarized into three steps. First, an initial policy model is generated based on minimal prior knowledge. Next, the prepared PPO agent is deployed so feedback from both critic model and human experts can be collected for future finetuning. Finally, the agent learns and adapts itself to the specific chiller plant, updates the policy model and is ready for the next iteration. Besides the proposed approach, this study also used traditional RL methods to optimize the same simulated chiller plants for comparison, and it turns out that the proposed method is safe and effective at the same time and needs less to no historical data to start up.Keywords: chiller plant, control methods, energy efficiency, proximal policy optimization, reinforcement learning
Procedia PDF Downloads 2525348 Hybrid Lateral-Directional Robust Flight Control with Propulsive Systems
Authors: Alexandra Monteiro, K. Bousson, Fernando J. O. Moreira, Ricardo Reis
Abstract:
Fixed-wing flying vehicles are usually controlled by means of control surfaces such as elevators, ailerons, and rudders. The failure of these systems may lead to severe or even fatal crashes. These failures resulted in increased popularity for research activities on propulsion control in the last decades. The present work deals with a hybrid control architecture in which the propulsion-controlled vehicle maintains its traditional control surfaces, addressing the issue of robust lateral-directional dynamics control. The challenges stem from the parameter uncertainties in the stability and control derivatives and some unknown terms in the flight dynamics model. Two approaches are implemented and tested: linear quadratic regulation with robustness characteristics and H∞ control. The problem is centered on roll-yaw controller design with full state-feedback, which is able to deal with a standalone propulsion control mode as well as a hybrid mode combining both propulsion control and conventional control surface concepts while maintaining the original flight maneuverability characteristics. The results for both controllers emphasized very good control performances; however, the H∞ controller showed higher stabilization rates and robustness albeit with a slightly higher control magnitude than using the linear quadratic regulator.Keywords: robust propulsion control, h-infinity control, lateral-directional flight dynamics, parameter uncertainties
Procedia PDF Downloads 153