Simulation based validity testing of an outlier accommodation method for minimax absolute error regression

1993 ◽  
Vol 20 (3) ◽  
pp. 349-353 ◽  
Author(s):  
Marvin D. Troutt ◽  
Suresh K. Tadisina
Author(s):  
Samir Kumar Hati ◽  
Nimai Pada Mandal ◽  
Dipankar Sanyal

Losses in control valves drag down the average overall efficiency of electrohydraulic systems to only about 22% from nearly 75% for standard pump-motor sets. For achieving higher energy efficiency in slower systems, direct pump control replacing fast-response valve control is being put in place through variable-speed motors. Despite the promise of a quicker response, displacement control of pumps has seen slower progress for exhibiting undesired oscillation with respect to the demand in some situations. Hence, a mechatronic simulation-based design is taken up here for a variable-displacement pump–controlled system directly feeding a double-acting single-rod cylinder. The most significant innovation centers on designing an axial-piston pump with an electrohydraulic compensator for bi-directional swashing. An accumulator is conceived to handle the flow difference in the two sides across the load piston. A solenoid-driven sequence valve with P control is proposed for charging the accumulator along with setting its initial gas pressure by a feedforward design. Simple proportional–integral–derivative control of the compensator valve is considered in this exploratory study. Appropriate setting of the gains and critical sizing of the compensator has been obtained through a detailed parametric study aiming low integral absolute error. A notable finding of the simulation is the achievement of the concurrent minimum integral absolute error of 3.8 mm s and the maximum energy saving of 516 kJ with respect to a fixed-displacement pump. This is predicted for the combination of the circumferential port width of 2 mm for the compensator valve and the radial clearance of 40 µm between each compensator cylinder and the paired piston.


Algorithms ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 296
Author(s):  
Lucy Blondell ◽  
Mark Z. Kos ◽  
John Blangero ◽  
Harald H. H. Göring

Statistical analysis of multinomial data in complex datasets often requires estimation of the multivariate normal (mvn) distribution for models in which the dimensionality can easily reach 10–1000 and higher. Few algorithms for estimating the mvn distribution can offer robust and efficient performance over such a range of dimensions. We report a simulation-based comparison of two algorithms for the mvn that are widely used in statistical genetic applications. The venerable Mendell-Elston approximation is fast but execution time increases rapidly with the number of dimensions, estimates are generally biased, and an error bound is lacking. The correlation between variables significantly affects absolute error but not overall execution time. The Monte Carlo-based approach described by Genz returns unbiased and error-bounded estimates, but execution time is more sensitive to the correlation between variables. For ultra-high-dimensional problems, however, the Genz algorithm exhibits better scale characteristics and greater time-weighted efficiency of estimation.


2020 ◽  
Vol 39 (3) ◽  
pp. 34-43
Author(s):  
Haaris Rasool ◽  
Aazim Rasool ◽  
Ataul Aziz Ikram ◽  
Urfa Rasool ◽  
Mohsin Jamil ◽  
...  

This work aims to tune multiple controllers at the same time for a HVDC system by using a self-generated (SG) simulation-based optimization technique. Online optimization is a powerful tool to improve performance of the system. Proportion integral (PI) controllers of Multi-infeed HVDC systems are optimized by the evaluation of objective functions in time simulation design (TSD). Model based simulation setup is applied for rapid selection of optimal PI control parameters, designed in PSCAD software. A multiple objective function (OF), i.e. Integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE), integral time square error (ITSE), and integral square time error (ISTE), is assembled for testing the compatibility of OFs with nonlinear self-generated simplex algorithm (SS-SA). Improved control parameters are achieved after multiple iterations. All OFs generate optimum responses and their results are compared with each other by their minimized numerical values. Disturbance rejection criteria are also proposed to assess the designed controller performance along with robustness of system. Results are displayed in form of graphs and tables in this paper.


Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo

The aim of this paper is to examine the beneficial impact of feedback information in the dynamics of production-inventory control systems. Two production-inventory control system models are analyzed: APIOBPCS and 2APIOBPCS models. The simulation-based experiment designs were conducted by using the state-space equations of the two models. The bullwhip effect as measured by the variance ratio between the order rate and the consumption rate, and inventory responsiveness as measured by the Integral of Absolute Error between the actual and the target levels of inventory, are two metrics used to evaluate the performance of the production-inventory control system in response to a random customer demand. To ensure that both models work under optimal performance, multi-objective particle swarm optimization (MOPSO) is employed to address the problem of tuning the controller’s parameters. The simulation results show the 2APIOBPCS model outperforms the APIOBPCS model at achieving the desired bullwhip effect and being able to provide better inventory responsiveness. The improvement in the inventory responsiveness becomes more significant when the system operates under mismatched lead time and/or an initial condition.


Author(s):  
Jonathan Camargo ◽  
Krishan Bhakta ◽  
Aaron Young

Developing controllers for powered prostheses is a daunting task that requires involvement from clinicians, patients and robotics experts. Difficulties arise for tuning prosthetic devices that perform in multiple conditions and provide more functionality to the user. For this reason, we propose the implementation of a simulation framework based on the open-source 3D simulation environment Gazebo, to reduce the burden of experimentation and aid in the early stages of development. In this study, we present a minimalist plugin for the simulator that allows the interfacing of a virtual model with the native prosthesis controller and renders the finding of impedance parameters as a pattern search problem. To demonstrate the functionality of this approach, we used the framework to obtain the parameters that offer the most similar joint trajectory to the respective biological counterpart during swing phase for ground level walking. The optimization results are compared against the response of a physical 2DOF knee-ankle prosthesis operating under the optimized parameters, showing congruence to our model-based results. We found that a simulation-based solution is capable of finding parameters that create an emerging behavior that approximates to the kinematic trajectory goals within a tolerance (mean absolute error ∼10%). This provides an appropriate method for development and evaluation of impedance-based controllers before deployment to the physical device.


2020 ◽  
Vol 9 (2) ◽  
pp. 263-286
Author(s):  
Hagninou Elagnon Venance Donnou ◽  
Aristide Barthélémy Akpo ◽  
Guy Hervé Houngue ◽  
Basile Bruno Kounouhewa

The wind turbulence intensity observed on a site have an influence the wind turbine energy production and the lifetime of the blades. It is therefore primordial to master this parameter for the optimization of the production. So therefore, this study is interested on the modelling of the wind turbulence intensity at 10 m above the ground on the coast of Benin. Four years of wind data measured on the site of Cotonou Port Authority (PAC) from 2011 to 2014 and recorded with a temporal resolution of 10 min were used. From the transport equation of turbulent kinetic energy followed by a numerical simulation based on the Nelder-Mead algorithm developed under the Matlab software, we proposed five new models for estimating the wind turbulence intensity. The results of the different simulations reveal that four of proposed models and based on the roughness, the speed of friction and the length of Obukhov better fit the data, during the periods of January, April, June, July, August, September and December. The estimators of the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE) vary from (0.02; 0.01) in December to (0.09; 0.07) in August. As for the model  which is a function of roughness and the wind  shear coefficient (expressed only according to the wind speed), it gives better performance whatever the time of the year and the atmosphere stability conditions. The estimations errors are included between (0.02; 0.01) obtained in December and (0.08; 0.06) observed in March. A comparative study between the existing models in the literature and the best model proposed in this study showed that only this model gives the best adjustment with the data. It can therefore be used on the sites where turbulence is influenced by the roughness and the atmosphere stability. Finally, from this model a new wind turbine design class has been proposed for the site of Cotonou. It takes into account the actual levels of turbulence observed and thus allow to optimize the energy production. ©2020. CBIORE-IJRED. All rights reserved


2018 ◽  
Vol 23 (6) ◽  
pp. 14-15
Author(s):  
Lee H. Ensalada

Abstract Symptom validity testing (SVT), also known as forced-choice testing, is a means of assessing the validity of sensory and memory deficits, including tactile anesthesias, paresthesias, blindness, color blindness, tunnel vision, blurry vision, and deafness. The common feature among these symptoms is a claimed inability to perceive or remember a sensory signal. SVT comprises two elements: a specific ability is assessed by presenting a large number of items in a multiple-choice format, and then the examinee's performance is compared to the statistical likelihood of success based on chance alone. These tests usually present two alternatives; thus the probability of simply guessing the correct response (equivalent to having no ability at all) is 50%. Thus, scores significantly below chance performance indicate that the sensory cues must have been perceived, but the examinee chose not to report the correct answer—alternative explanations are not apparent. SVT also has the capacity to demonstrate that the examinee performed below the probabilities of chance. Scoring below a norm can be explained by fatigue, evaluation anxiety, inattention, or limited intelligence. Scoring below the probabilities of chance alone most likely indicates deliberate deceptions and is evidence of malingering because it provides strong evidence that the examinee received the sensory cues and denied the perception. Even so, malingering must be evaluated from the total clinical context.


1999 ◽  
Vol 4 (4) ◽  
pp. 4-4

Abstract Symptom validity testing, also known as forced-choice testing, is a way to assess the validity of sensory and memory deficits, including tactile anesthesias, paresthesias, blindness, color blindness, tunnel vision, blurry vision, and deafness—the common feature of which is a claimed inability to perceive or remember a sensory signal. Symptom validity testing comprises two elements: A specific ability is assessed by presenting a large number of items in a multiple-choice format, and then the examinee's performance is compared with the statistical likelihood of success based on chance alone. Scoring below a norm can be explained in many different ways (eg, fatigue, evaluation anxiety, limited intelligence, and so on), but scoring below the probabilities of chance alone most likely indicates deliberate deception. The positive predictive value of the symptom validity technique likely is quite high because there is no alternative explanation to deliberate distortion when performance is below the probability of chance. The sensitivity of this technique is not likely to be good because, as with a thermometer, positive findings indicate that a problem is present, but negative results do not rule out a problem. Although a compelling conclusion is that the examinee who scores below probabilities is deliberately motivated to perform poorly, malingering must be concluded from the total clinical context.


2011 ◽  
Vol 16 (5) ◽  
pp. 5-7
Author(s):  
Lee Ensalada

Abstract Illness behavior refers to the ways in which symptoms are perceived, understood, acted upon, and communicated and include facial grimacing, holding or supporting the affected body part, limping, using a cane, and stooping while walking. Illness behavior can be unconscious or conscious: In the former, the person is unaware of the mental processes and content that are significant in determining behavior; conscious illness behavior may be voluntary and conscious (the two are not necessarily associated). The first broad category of inappropriate illness behavior is defensiveness, which is characterized by denial or minimization of symptoms. The second category includes somatoform disorders, factitious disorders, and malingering and is characterized by exaggerating, fabricating, or denying symptoms; minimizing capabilities or positive traits; or misattributing actual deficits to a false cause. Evaluators can detect the presence of inappropriate illness behaviors based on evidence of consistency in the history or examination; the likelihood that the reported symptoms make medical sense and fit a reasonable disease pattern; understanding of the patient's current situation, personal and social history, and emotional predispositions; emotional reactions to symptoms; evaluation of nonphysiological findings; results obtained using standardized test instruments; and tests of dissimulation, such as symptom validity testing. Unsupported and insupportable conclusions regarding inappropriate illness behavior represent substandard practice in view of the importance of these conclusions for the assessment of impairment or disability.


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