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- Adaptive Control (4)
- Neurocontrollers (4)
- Nonlinear Control Systems (4)
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- Conflict Resolution (3)
- Discrete Time Systems (3)
- Learning (Artificial Intelligence) (3)
- Lyapunov Methods (3)
- Computational Argumentation (2)
- Feedback (2)
- Fuzzy Logic (2)
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- Adaptive Critic-Based Neural Network Controller (1)
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- Argumentation (1)
- Battery capacity fade modeling (1)
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- Chebyshev spectral method (1)
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- Mechanical and Aerospace Engineering Faculty Research & Creative Works (24)
- Electrical and Computer Engineering Faculty Research & Creative Works (8)
- Collaborative Research: Actively Controllable Microfluidics with Film-Confined Redox-Magnetohydrodynamics -- Video and Data (5)
- Computer Science Faculty Research & Creative Works (5)
- Chemistry Faculty Research & Creative Works (4)
Articles 1 - 30 of 55
Full-Text Articles in Physical Sciences and Mathematics
Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy
Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy
Computer Science Faculty Research & Creative Works
Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition of convolutional layers to combine the feature extraction power of convolutional networks with the computational efficiency of SNNs has been introduced. This paper studies the feasibility of using a convolutional spiking neural network (CSNN) to detect anticipatory slow cortical potentials (SCPs) related to braking intention in human participants using an electroencephalogram (EEG). Data was collected during an experiment wherein participants operated a remote-controlled vehicle on a testbed …
Kinetic Particle Simulations Of Plasma Charging At Lunar Craters Under Severe Conditions, David Lund, Xiaoming He, Daoru Frank Han
Kinetic Particle Simulations Of Plasma Charging At Lunar Craters Under Severe Conditions, David Lund, Xiaoming He, Daoru Frank Han
Mathematics and Statistics Faculty Research & Creative Works
This paper presents fully kinetic particle simulations of plasma charging at lunar craters with the presence of lunar lander modules using the recently developed Parallel Immersed-Finite-Element Particle-in-Cell (PIFE-PIC) code. The computation model explicitly includes the lunar regolith layer on top of the lunar bedrock, taking into account the regolith layer thickness and permittivity as well as the lunar lander module in the simulation domain, resolving a nontrivial surface terrain or lunar lander configuration. Simulations were carried out to study the lunar surface and lunar lander module charging near craters at the lunar terminator region under mean and severe plasma environments. …
Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley
Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional …
Aircraft Engine Particulate Matter Emissions From Sustainable Aviation Fuels: Results From Ground-Based Measurements During The Nasa/Dlr Campaign Eclif2/Nd-Max, Tobias Schripp, Bruce E. Anderson, Uwe Bauder, Bastian Rauch, Joel C. Corbin, Greg J. Smallwood, Prem Lobo, Ewan C. Crosbie, Michael A. Shook, Richard C. Miake-Lye, Zhenhong Yu, Andrew Freedman, Philip D. Whitefield, Claire E. Robinson
Aircraft Engine Particulate Matter Emissions From Sustainable Aviation Fuels: Results From Ground-Based Measurements During The Nasa/Dlr Campaign Eclif2/Nd-Max, Tobias Schripp, Bruce E. Anderson, Uwe Bauder, Bastian Rauch, Joel C. Corbin, Greg J. Smallwood, Prem Lobo, Ewan C. Crosbie, Michael A. Shook, Richard C. Miake-Lye, Zhenhong Yu, Andrew Freedman, Philip D. Whitefield, Claire E. Robinson
Chemistry Faculty Research & Creative Works
The use of alternative jet fuels by commercial aviation has increased substantially in recent years. Beside the reduction of carbon dioxide emission, the use of sustainable aviation fuels (SAF) may have a positive impact on the reduction of particulate emissions. This study summarizes the results from a ground-based measurement activity conducted in January 2018 as part of the ECLIF2/ND-MAX campaign in Ramstein, Germany. Two fossil reference kerosenes and three different blends with the renewable fuel component HEFA-SPK (Hydroprocessed Esters and Fatty Acids Synthetic Paraffinic Kerosene) were burned in an A320 with V2527-A5 engines to investigate the effect of fuel naphthalene/aromatic …
Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang
Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang
Mathematics and Statistics Faculty Research & Creative Works
We analyze a fully discrete finite element numerical scheme for the Cahn-Hilliard-Stokes-Darcy system that models two-phase flows in coupled free flow and porous media. To avoid a well-known difficulty associated with the coupling between the Cahn-Hilliard equation and the fluid motion, we make use of the operator-splitting in the numerical scheme, so that these two solvers are decoupled, which in turn would greatly improve the computational efficiency. The unique solvability and the energy stability have been proved in Chen et al. (2017, Uniquely solvable and energy stable decoupled numerical schemes for the Cahn-Hilliard-Stokes-Darcy system for two-phase flows in karstic geometry. …
An Accurate And Computationally Efficient Method For Battery Capacity Fade Modeling, D. M. Ajiboye, Jonathan W. Kimball, R.(Robert) G. Landers, John (T.) Park
An Accurate And Computationally Efficient Method For Battery Capacity Fade Modeling, D. M. Ajiboye, Jonathan W. Kimball, R.(Robert) G. Landers, John (T.) Park
Electrical and Computer Engineering Faculty Research & Creative Works
The Industry Demand for Accurate and Fast Algorithms that Model Vital Battery Parameters, E.g., State-Of-Health, State-Of-Charge, Pulse-Power Capability, is Substantial. One of the Most Critical Models is Battery Capacity Fade. the Key Challenge with Physics-Based Battery Capacity Fade Modeling is the High Numerical Cost in Solving Complex Models. in This Study, an Efficient and Fast Model is Presented to Capture Capacity Fade in Lithium-Ion Batteries. Here, the High-Order Chebyshev Spectral Method is Employed to Address the Associated Complexity with Physics-Based Capacity Fade Models. its Many Advantages, Such as Low Computational Memory, High Accuracy, Exponential Convergence, and Ease of Implementation, Allow …
Jointly-Learnt Networks For Future Action Anticipation Via Self-Knowledge Distillation And Cycle Consistency, Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ming-Chuan Leu, Ruwen Qin
Jointly-Learnt Networks For Future Action Anticipation Via Self-Knowledge Distillation And Cycle Consistency, Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ming-Chuan Leu, Ruwen Qin
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Future action anticipation aims to infer future actions from the observation of a small set of past video frames. In this paper, we propose a novel Jointly learnt Action Anticipation Network (J-AAN) via Self-Knowledge Distillation (Self-KD) and cycle consistency for future action anticipation. In contrast to the current state-of-the-art methods which anticipate the future actions either directly or recursively, our proposed J-AAN anticipates the future actions jointly in both direct and recursive ways. However, when dealing with future action anticipation, one important challenge to address is the future's uncertainty since multiple action sequences may come from or be followed by …
A Mathematical Model And Numerical Simulations Of Redox Electrochemical Systems With Mhd And Natural Convection, Kakkattukuzhy M. Isaac, Fangping Yuan
A Mathematical Model And Numerical Simulations Of Redox Electrochemical Systems With Mhd And Natural Convection, Kakkattukuzhy M. Isaac, Fangping Yuan
Collaborative Research: Actively Controllable Microfluidics with Film-Confined Redox-Magnetohydrodynamics -- Video and Data
A comprehensive mathematical model for redox electrochemical systems with magnetohydrodynamics (MHD) and natural convection are presented. The model is based on density changes in isothermal systems that accompany redox reaction at the electrode due to supporting electrolyte ions migrating into and out of the diffusion layer to satisfy electroneutrality. Numerical simulations have been performed for an axisymmetric, milli-electrode electrochemical cell with gravity directed along the axis in both directions to investigate the effect of the electrode orientation with respect to gravity. Results show that natural convection is significant in both cases, with the maximum velocity being an order of magnitude …
Natural Convection In Redox Electrochemistry: Model, Simulation And Experiments, Fangping Yuan, Kakkattukuzhy M. Isaac
Natural Convection In Redox Electrochemistry: Model, Simulation And Experiments, Fangping Yuan, Kakkattukuzhy M. Isaac
Collaborative Research: Actively Controllable Microfluidics with Film-Confined Redox-Magnetohydrodynamics -- Video and Data
No abstract provided.
Natural Convection And Forced Convection Model Based On Electroneutrality And Migration In Redox Mhd Systems, Fangping Yuan, Kakkattukuzhy M. Isaac
Natural Convection And Forced Convection Model Based On Electroneutrality And Migration In Redox Mhd Systems, Fangping Yuan, Kakkattukuzhy M. Isaac
Collaborative Research: Actively Controllable Microfluidics with Film-Confined Redox-Magnetohydrodynamics -- Video and Data
No abstract provided.
High-Frequency Instabilities Of Stationary Crossflow Vortices In A Hypersonic Boundary Layer, Fei Li, Meelan Choudhari, Pedro Paredes-Gonzalez, Lian Duan
High-Frequency Instabilities Of Stationary Crossflow Vortices In A Hypersonic Boundary Layer, Fei Li, Meelan Choudhari, Pedro Paredes-Gonzalez, Lian Duan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Hypersonic boundary layer flows over a circular cone at moderate incidence angle can support strong crossflow instability in between the windward and leeward rays on the plane of symmetry. Due to more efficient excitation of stationary crossflow vortices by surface roughness, such boundary layer flows may transition to turbulence via rapid amplification of the high-frequency secondary instabilities of finite-amplitude stationary crossflow vortices. The amplification characteristics of these secondary instabilities are investigated for crossflow vortices generated by an azimuthally periodic array of roughness elements over a 7° half-angle circular cone in a Mach 6 free stream. The analysis is based on …
Chaotic Advection-Driven Mixing In Unsteady Three-Dimensional Mhd Flows In Microfluidic Devices, Fangping Yuan, Kakkattukuzhy M. Isaac
Chaotic Advection-Driven Mixing In Unsteady Three-Dimensional Mhd Flows In Microfluidic Devices, Fangping Yuan, Kakkattukuzhy M. Isaac
Collaborative Research: Actively Controllable Microfluidics with Film-Confined Redox-Magnetohydrodynamics -- Video and Data
No abstract provided.
Ionic And Electronic Conductivities Of Atomic Layer Deposition Thin Film Coated Lithium Ion Battery Cathode Particles, Rajankumar L. Patel, Jonghyun Park, Xinhua Liang
Ionic And Electronic Conductivities Of Atomic Layer Deposition Thin Film Coated Lithium Ion Battery Cathode Particles, Rajankumar L. Patel, Jonghyun Park, Xinhua Liang
Mechanical and Aerospace Engineering Faculty Research & Creative Works
It is imperative to ascertain the ionic and electronic components of the total conductivity of an electrochemically active material. A blocking technique, called the “Hebb-Wagner method”, is normally used to explain the two components (ionic and electronic) of a mixed conductor, in combination with the complex ac impedance method and dc polarization measurements. CeO2 atomic layer deposition (ALD)-coated and uncoated, LiMn2O4 (LMO) and LiMn1.5Ni0.5O4 (LMNO) powders were pressed into pellets and then painted with silver to act as a blocking electrode. The electronic conductivities were derived from the currents obtained using …
Geometric Consideration Of Nanostructures For Energy Storage Systems, Jonghyun Park, Jie Li, Wei Lu, Ann Marie Sastry
Geometric Consideration Of Nanostructures For Energy Storage Systems, Jonghyun Park, Jie Li, Wei Lu, Ann Marie Sastry
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Battery performance and its fade are determined by various aspects such as the transport of ions and electrons through heterogeneous internal structures; kinetic reactions at the interfaces; and the corresponding interplay between mechanical, chemical, and thermal responses. The fundamental factor determining this complex multiscale and multiphysical nature of a battery is the geometry of active materials. In this work, we systematically consider the tradeoffs among a selection of limiting geometries of media designed to store ions or other species via a diffusion process. Specifically, we begin the investigation by considering diffusion in spheres, rods, and plates at the particle level, …
Silicon-Wall Interfacial Free Energy Via Thermodynamics Integration, Wan Shou, Heng Pan
Silicon-Wall Interfacial Free Energy Via Thermodynamics Integration, Wan Shou, Heng Pan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
We compute the interfacial free energy of a silicon system in contact with flat and structured walls by molecular dynamics simulation. The thermodynamics integration method, previously applied to Lennard-Jones potentials [R. Benjamin and J. Horbach, J. Chem. Phys. 137, 044707 (2012)], has been extended and implemented in Tersoff potentials with two-body and three-body interactions taken into consideration. The thermodynamic integration scheme includes two steps. In the first step, the bulk Tersoff system is reversibly transformed to a state where it interacts with a structureless flat wall, and in a second step, the flat structureless wall is reversibly transformed into an …
A Study Of Mixing In A Magnetohydrodynamic (Mhd) Microfluidic Cell By Numerical Simulations, Fangping Yuan, Kakkattukuzhy M. Isaac
A Study Of Mixing In A Magnetohydrodynamic (Mhd) Microfluidic Cell By Numerical Simulations, Fangping Yuan, Kakkattukuzhy M. Isaac
Collaborative Research: Actively Controllable Microfluidics with Film-Confined Redox-Magnetohydrodynamics -- Video and Data
No abstract provided.
Nonlinear Development And Secondary Instability Of Traveling Crossflow Vortices, Fei Li, Meelan M. Choudhari, Lian Duan, Chau-Lyan Chang
Nonlinear Development And Secondary Instability Of Traveling Crossflow Vortices, Fei Li, Meelan M. Choudhari, Lian Duan, Chau-Lyan Chang
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Building upon the prior research targeting the laminar breakdown mechanisms associated with stationary crossflow instability over a swept-wing configuration, this paper investigates the secondary instability of traveling crossflow modes as an alternate scenario for transition. For the parameter range investigated herein, this alternate scenario is shown to be viable unless the initial amplitudes of the traveling crossflow instability are lower than those of the stationary modes by considerably more than one order of magnitude. The linear growth predictions based on the secondary instability theory are found to agree well with both parabolized stability equations and direct numerical simulation, and the …
Crystallization In Nano-Confinement Seeded By A Nanocrystal -- A Molecular Dynamics Study, Heng Pan, Costas Grigoropoulos
Crystallization In Nano-Confinement Seeded By A Nanocrystal -- A Molecular Dynamics Study, Heng Pan, Costas Grigoropoulos
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Seeded crystallization and solidification in nanoscale confinement volumes have become an important and complex topic. Due to the complexity and limitations in observing nanoscale crystallization, computer simulation can provide valuable details for supporting and interpreting experimental observations. In this article, seeded crystallization from nano-confined liquid, as represented by the crystallization of a suspended gold nano-droplet seeded by a pre-existing gold nanocrystal seed, was investigated using molecular dynamics simulations in canonical (NVT) ensemble. We found that the crystallization temperature depends on nano-confinement volume, crystal orientation, and seed size as explained by classical two-sphere model and Gibbs-Thomson effect.
Reinforcement-Learning-Based Output-Feedback Control Of Nonstrict Nonlinear Discrete-Time Systems With Application To Engine Emission Control, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Reinforcement-Learning-Based Output-Feedback Control Of Nonstrict Nonlinear Discrete-Time Systems With Application To Engine Emission Control, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning-based output adaptive neural network (NN) controller, which is also referred to as the adaptive-critic NN controller, is developed to deliver the desired tracking performance for a class of nonlinear discrete-time systems expressed in nonstrict feedback form in the presence of bounded and unknown disturbances. The adaptive-critic NN controller consists of an observer, a critic, and two action NNs. The observer estimates the states and output, and the two action NNs provide virtual and actual control inputs to the nonlinear discrete-time system. The critic approximates a certain strategic utility function, and the action NNs minimize the strategic utility …
Three-Dimensional Modeling Of The Plasma Arc In Arc Welding, Gu Xu, J. Hu, Hai-Lung Tsai
Three-Dimensional Modeling Of The Plasma Arc In Arc Welding, Gu Xu, J. Hu, Hai-Lung Tsai
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Most previous three-dimensional modeling on gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW) focuses on the weld pool dynamics and assumes the two-dimensional axisymmetric Gaussian distributions for plasma arc pressure and heat flux. In this article, a three-dimensional plasma arc model is developed, and the distributions of velocity, pressure, temperature, current density, and magnetic field of the plasma arc are calculated by solving the conservation equations of mass, momentum, and energy, as well as part of the Maxwell's equations. This three-dimensional model can be used to study the nonaxisymmetric plasma arc caused by external perturbations such as …
Incorporation Of Evidences Into An Intelligent Computational Argumentation Network For A Web-Based Collaborative Engineering Design System, Xiaoqing Frank Liu, Ekta Khudkhudia, Ming-Chuan Leu
Incorporation Of Evidences Into An Intelligent Computational Argumentation Network For A Web-Based Collaborative Engineering Design System, Xiaoqing Frank Liu, Ekta Khudkhudia, Ming-Chuan Leu
Computer Science Faculty Research & Creative Works
Conflicts among the stakeholders are unavoidable in the process of collaborative engineering design. Resolution of these conflicts is a challenging task. In our previous research, a web based intelligent collaborative system was developed which provides decision-making support, using computational argumentation techniques. Enhancements were done to this system to incorporate the priorities of the stakeholders and to detect arguments that self conflict. As an effort to make this system more effective and more objective in the process of decision making, we develop a method to assess the effect of evidences in the argumentation network, using Dempster-Shafer theory of evidence and fuzzy …
Output Feedback Controller For Operation Of Spark Ignition Engines At Lean Conditions Using Neural Networks, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Output Feedback Controller For Operation Of Spark Ignition Engines At Lean Conditions Using Neural Networks, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
Spark ignition (SI) engines operating at very lean conditions demonstrate significant nonlinear behavior by exhibiting cycle-to-cycle bifurcation of heat release. Past literature suggests that operating an engine under such lean conditions can significantly reduce NO emissions by as much as 30% and improve fuel efficiency by as much as 5%-10%. At lean conditions, the heat release per engine cycle is not close to constant, as it is when these engines operate under stoichiometric conditions where the equivalence ratio is 1.0. A neural network controller employing output feedback has shown ability in simulation to reduce the nonlinear cyclic dispersion observed under …
Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …
Management Of An Intelligent Argumentation Network For A Web-Based Collaborative Engineering Design Environment, Xiaoqing Frank Liu, Man Zheng, Ganesh K. Venayagamoorthy, Ming-Chuan Leu
Management Of An Intelligent Argumentation Network For A Web-Based Collaborative Engineering Design Environment, Xiaoqing Frank Liu, Man Zheng, Ganesh K. Venayagamoorthy, Ming-Chuan Leu
Computer Science Faculty Research & Creative Works
Conflict resolution is one of the most challenging tasks in collaborative engineering design. In our previous research, a web-based intelligent collaborative system was developed to address this challenge based on intelligent computational argumentation. However, two important issues were not resolved in that system: priority of participants and self-conflicting arguments. In this paper, we develop two methods for incorporating priorities of participants into the computational argumentation network: 1) weighted summation and 2) re-assessment of strengths of arguments based on priority of owners of the argument using fuzzy logic inference. In addition, we develop a method for detection of self-conflicting arguments. Incorporation …
Neural Network Controller Development And Implementation For Spark Ignition Engines With High Egr Levels, Jonathan B. Vance, Atmika Singh, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Neural Network Controller Development And Implementation For Spark Ignition Engines With High Egr Levels, Jonathan B. Vance, Atmika Singh, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
Past research has shown substantial reductions in the oxides of nitrogen (NOx) concentrations by using 10% -25% exhaust gas recirculation (EGR) in spark ignition (SI) engines (see Dudek and Sain, 1989). However, under high EGR levels, the engine exhibits strong cyclic dispersion in heat release which may lead to instability and unsatisfactory performance preventing commercial engines to operate with high EGR levels. A neural network (NN)-based output feedback controller is developed to reduce cyclic variation in the heat release under high levels of EGR even when the engine dynamics are unknown by using fuel as the control input. A separate …
Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …
An Internet Based Intelligent Argumentation System For Collaborative Engineering Design, Xiaoqing Frank Liu, Samir Raorane, Man Zheng, Ming-Chuan Leu
An Internet Based Intelligent Argumentation System For Collaborative Engineering Design, Xiaoqing Frank Liu, Samir Raorane, Man Zheng, Ming-Chuan Leu
Computer Science Faculty Research & Creative Works
Modern product design is a very complicated process which involves groups of designers, manufacturers, suppliers, and customer representatives. Conflicts are unavoidable in collaboration among multiple stakeholders, who have different objectives, requirements, and priorities. Unfortunately, current web-based collaborative engineering design systems do not support collaborative conflict resolution. In this paper, we will develop an intelligent computational argumentation model to enable management of a large scale argumentation network, and resolution of conflicts based on argumentation from many participants. A web-based intelligent argumentation tool is developed as a part of a web-based collaborative engineering design system based on the above model to resolve …
Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He
Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He
Electrical and Computer Engineering Faculty Research & Creative Works
Spark ignition (SI) engines running at very lean conditions demonstrate significant nonlinear behavior by exhibiting cycle-to-cycle dispersion of heat release even though such operation can significantly reduce NOx emissions and improve fuel efficiency by as much as 5-10%. A suite of neural network (NN) controller without and with reinforcement learning employing output feedback has shown ability to reduce the nonlinear cyclic dispersion observed under lean operating conditions. The neural network controllers consists of three NN: a) A NN observer to estimate the states of the engine such as total fuel and air; b) a second NN for generating virtual input; …
Effect Of Polymer-Surface Mobility On Adhesion In Poly(Methyl Methacrylate)-Tape System, Bhavesh C. Gandhi, Frank D. Blum, Lokeswarappa R. Dharani
Effect Of Polymer-Surface Mobility On Adhesion In Poly(Methyl Methacrylate)-Tape System, Bhavesh C. Gandhi, Frank D. Blum, Lokeswarappa R. Dharani
Chemistry Faculty Research & Creative Works
The interaction between two polymer layers, especially adhesion between them, plays an important role in polymer processing and other applications. Detailed knowledge of the molecular structure and dynamics of polymer interfaces, and how they relate to macroscopic mechanical properties, should help designers construct more functional systems. Unfortunately, there have been few studies where both molecular and macroscopic studies have been performed on similar systems. In previous studies from our group, we have probed the dynamics of poly(methyl acrylate) (PMA) and thermal behavior of poly(methyl methacrylate) (PMMA) on silica. These studies helped us paint a picture for strongly bound molecules on …
Adaptive Critic-Based Neural Network Controller For Uncertain Nonlinear Systems With Unknown Deadzones, Pingan He, Jagannathan Sarangapani, S. N. Balakrishnan
Adaptive Critic-Based Neural Network Controller For Uncertain Nonlinear Systems With Unknown Deadzones, Pingan He, Jagannathan Sarangapani, S. N. Balakrishnan
Electrical and Computer Engineering Faculty Research & Creative Works
A multilayer neural network (NN) controller in discrete-time is designed to deliver a desired tracking performance for a class of nonlinear systems with input deadzones. This multilayer NN controller has an adaptive critic NN architecture with two NNs for compensating the deadzone nonlinearity and a third NN for approximating the dynamics of the nonlinear system. A reinforcement learning scheme in discrete-time is proposed for the adaptive critic NN deadzone compensator, where the learning is performed based on a certain performance measure, which is supplied from a critic. The adaptive generating NN rejects the errors induced by the deadzone whereas a …