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- Genre: Doctoral Dissertation
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Description
Robotic lower limb prostheses provide new opportunities to help transfemoral amputees regain mobility. However, their application is impeded by that the impedance control parameters need to be tuned and optimized manually by prosthetists for each individual user in different task environments. Reinforcement learning (RL) is capable of automatically learning from interacting with the environment. It becomes a natural candidate to replace human prosthetists to customize the control parameters. However, neither traditional RL approaches nor the popular deep RL approaches are readily suitable for learning with limited number of samples and samples with large variations. This dissertation aims to explore new RL based adaptive solutions that are data-efficient for controlling robotic prostheses.
This dissertation begins by proposing a new flexible policy iteration (FPI) framework. To improve sample efficiency, FPI can utilize either on-policy or off-policy learning strategy, can learn from either online or offline data, and can even adopt exiting knowledge of an external critic. Approximate convergence to Bellman optimal solutions are guaranteed under mild conditions. Simulation studies validated that FPI was data efficient compared to several established RL methods. Furthermore, a simplified version of FPI was implemented to learn from offline data, and then the learned policy was successfully tested for tuning the control parameters online on a human subject.
Next, the dissertation discusses RL control with information transfer (RL-IT), or knowledge-guided RL (KG-RL), which is motivated to benefit from transferring knowledge acquired from one subject to another. To explore its feasibility, knowledge was extracted from data measurements of able-bodied (AB) subjects, and transferred to guide Q-learning control for an amputee in OpenSim simulations. This result again demonstrated that data and time efficiency were improved using previous knowledge.
While the present study is new and promising, there are still many open questions to be addressed in future research. To account for human adaption, the learning control objective function may be designed to incorporate human-prosthesis performance feedback such as symmetry, user comfort level and satisfaction, and user energy consumption. To make the RL based control parameter tuning practical in real life, it should be further developed and tested in different use environments, such as from level ground walking to stair ascending or descending, and from walking to running.
This dissertation begins by proposing a new flexible policy iteration (FPI) framework. To improve sample efficiency, FPI can utilize either on-policy or off-policy learning strategy, can learn from either online or offline data, and can even adopt exiting knowledge of an external critic. Approximate convergence to Bellman optimal solutions are guaranteed under mild conditions. Simulation studies validated that FPI was data efficient compared to several established RL methods. Furthermore, a simplified version of FPI was implemented to learn from offline data, and then the learned policy was successfully tested for tuning the control parameters online on a human subject.
Next, the dissertation discusses RL control with information transfer (RL-IT), or knowledge-guided RL (KG-RL), which is motivated to benefit from transferring knowledge acquired from one subject to another. To explore its feasibility, knowledge was extracted from data measurements of able-bodied (AB) subjects, and transferred to guide Q-learning control for an amputee in OpenSim simulations. This result again demonstrated that data and time efficiency were improved using previous knowledge.
While the present study is new and promising, there are still many open questions to be addressed in future research. To account for human adaption, the learning control objective function may be designed to incorporate human-prosthesis performance feedback such as symmetry, user comfort level and satisfaction, and user energy consumption. To make the RL based control parameter tuning practical in real life, it should be further developed and tested in different use environments, such as from level ground walking to stair ascending or descending, and from walking to running.
ContributorsGao, Xiang (Author) / Si, Jennie (Thesis advisor) / Huang, He Helen (Committee member) / Santello, Marco (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2020
Description
Presented is a design approach and test of a novel compact waveguide that demonstrated the outer dimensions of a rectangular waveguide through the introduction of parallel raised strips, or flanges, which run the length of the rectangular waveguide along the direction of wave propagation. A 10GHz waveguide was created with outer dimensions of a=9.0mm and b=3.6mm compared to a WR-90 rectangular waveguide with outer dimensions of a=22.86mm and b=10.16mm which the area is over 7 times the area. The first operating bandwidth for a hollow waveguide of dimensions a=9.0mm and b=3.6mm starts at 16.6GHz a 40% reduction in cutoff frequency.
The prototyped and tested compact waveguide demonstrated an operating close to the predicted 2GHz with predicted vs measured injection loss generally within 0.25dB and an overall measured injection loss of approximately 4.67dB/m within the operating bandwidth.
The prototyped and tested compact waveguide demonstrated an operating close to the predicted 2GHz with predicted vs measured injection loss generally within 0.25dB and an overall measured injection loss of approximately 4.67dB/m within the operating bandwidth.
ContributorsJones, Jimmy, Ph.D (Author) / Pan, George (Thesis advisor) / Palais, Joseph (Committee member) / Aberle, James T., 1961- (Committee member) / Young, William (Committee member) / Arizona State University (Publisher)
Created2019
Description
This dissertation explores thermal effects and electrical characteristics in metal-oxide-semiconductor field effect transistor (MOSFET) devices and circuits using a multiscale dual-carrier approach. Simulating electron and hole transport with carrier-phonon interactions for thermal transport allows for the study of complementary logic circuits with device level accuracy in electrical characteristics and thermal effects. The electrical model is comprised of an ensemble Monte Carlo solution to the Boltzmann Transport Equation coupled with an iterative solution to two-dimensional (2D) Poisson’s equation. The thermal model solves the energy balance equations accounting for carrier-phonon and phonon-phonon interactions. Modeling of circuit behavior uses parametric iteration to ensure current and voltage continuity. This allows for modeling of device behavior, analyzing circuit performance, and understanding thermal effects.
The coupled electro-thermal approach, initially developed for individual n-channel MOSFET (NMOS) devices, now allows multiple devices in tandem providing a platform for better comparison with heater-sensor experiments. The latest electro-thermal solver allows simulation of multiple NMOS and p-channel MOSFET (PMOS) devices, providing a platform for the study of complementary MOSFET (CMOS) circuit behavior. Modeling PMOS devices necessitates the inclusion of hole transport and hole-phonon interactions. The analysis of CMOS circuits uses the electro-thermal device simulation methodology alongside parametric iteration to ensure current continuity. Simulating a CMOS inverter and analyzing the extracted voltage transfer characteristics verifies the efficacy of this methodology. This work demonstrates the effectiveness of the dual-carrier electro-thermal solver in simulating thermal effects in CMOS circuits.
The coupled electro-thermal approach, initially developed for individual n-channel MOSFET (NMOS) devices, now allows multiple devices in tandem providing a platform for better comparison with heater-sensor experiments. The latest electro-thermal solver allows simulation of multiple NMOS and p-channel MOSFET (PMOS) devices, providing a platform for the study of complementary MOSFET (CMOS) circuit behavior. Modeling PMOS devices necessitates the inclusion of hole transport and hole-phonon interactions. The analysis of CMOS circuits uses the electro-thermal device simulation methodology alongside parametric iteration to ensure current continuity. Simulating a CMOS inverter and analyzing the extracted voltage transfer characteristics verifies the efficacy of this methodology. This work demonstrates the effectiveness of the dual-carrier electro-thermal solver in simulating thermal effects in CMOS circuits.
ContributorsDaugherty, Robin (Author) / Vasileska, Dragica (Thesis advisor) / Aberle, James T., 1961- (Committee member) / Ferry, David (Committee member) / Goodnick, Stephen (Committee member) / Arizona State University (Publisher)
Created2019
Description
Over the last decade, deep neural networks also known as deep learning, combined with large databases and specialized hardware for computation, have made major strides in important areas such as computer vision, computational imaging and natural language processing. However, such frameworks currently suffer from some drawbacks. For example, it is generally not clear how the architectures are to be designed for different applications, or how the neural networks behave under different input perturbations and it is not easy to make the internal representations and parameters more interpretable. In this dissertation, I propose building constraints into feature maps, parameters and and design of algorithms involving neural networks for applications in low-level vision problems such as compressive imaging and multi-spectral image fusion, and high-level inference problems including activity and face recognition. Depending on the application, such constraints can be used to design architectures which are invariant/robust to certain nuisance factors, more efficient and, in some cases, more interpretable. Through extensive experiments on real-world datasets, I demonstrate these advantages of the proposed methods over conventional frameworks.
ContributorsLohit, Suhas Anand (Author) / Turaga, Pavan (Thesis advisor) / Spanias, Andreas (Committee member) / Li, Baoxin (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2019
Description
The advent of commercial inexpensive sensors and the advances in information and communication technology (ICT) have brought forth the era of pervasive Quantified-Self. Automatic diet monitoring is one of the most important aspects for Quantified-Self because it is vital for ensuring the well-being of patients suffering from chronic diseases as well as for providing a low cost means for maintaining the health for everyone else. Automatic dietary monitoring consists of: a) Determining the type and amount of food intake, and b) Monitoring eating behavior, i.e., time, frequency, and speed of eating. Although there are some existing techniques towards these ends, they suffer from issues of low accuracy and low adherence. To overcome these issues, multiple sensors were utilized because the availability of affordable sensors that can capture the different aspect information has the potential for increasing the available knowledge for Quantified-Self. For a), I envision an intelligent dietary monitoring system that automatically identifies food items by using the knowledge obtained from visible spectrum camera and infrared spectrum camera. This system is able to outperform the state-of-the-art systems for cooked food recognition by 25% while also minimizing user intervention. For b), I propose a novel methodology, IDEA that performs accurate eating action identification within eating episodes with an average F1-score of 0.92. This is an improvement of 0.11 for precision and 0.15 for recall for the worst-case users as compared to the state-of-the-art. IDEA uses only a single wrist-band which includes four sensors and provides feedback on eating speed every 2 minutes without obtaining any manual input from the user.
ContributorsLee, Junghyo (Author) / Gupta, Sandeep K.S. (Thesis advisor) / Banerjee, Ayan (Committee member) / Li, Baoxin (Committee member) / Chiou, Erin (Committee member) / Kudva, Yogish C. (Committee member) / Arizona State University (Publisher)
Created2019
Description
A critical problem for airborne, ship board, and land based radars operating in maritime or littoral environments is the detection, identification and tracking of targets against backscattering caused by the roughness of the sea surface. Statistical models, such as the compound K-distribution (CKD), were shown to accurately describe two separate structures of the sea clutter intensity fluctuations. The first structure is the texture that is associated with long sea waves and exhibits long temporal decorrelation period. The second structure is the speckle that accounts for reflections from multiple scatters and exhibits a short temporal decorrelation period from pulse to pulse. Existing methods for estimating the CKD model parameters do not include the thermal noise power, which is critical for real sea clutter processing. Estimation methods that include the noise power are either computationally intensive or require very large data records.
This work proposes two new approaches for accurately estimating all three CKD model parameters, including noise power. The first method integrates, in an iterative fashion, the noise power estimation, using one-dimensional nonlinear curve fitting,
with the estimation of the shape and scale parameters, using closed-form solutions in terms of the CKD intensity moments. The second method is similar to the first except it replaces integer-based intensity moments with fractional moments which have been shown to achieve more accurate estimates of the shape parameter. These new methods can be implemented in real time without requiring large data records. They can also achieve accurate estimation performance as demonstrated with simulated and real sea clutter observation datasets. The work also investigates the numerically computed Cram\'er-Rao lower bound (CRLB) of the variance of the shape parameter estimate using intensity observations in thermal noise with unknown power. Using the CRLB, the asymptotic estimation performance behavior of the new estimators is studied and compared to that of other estimators.
This work proposes two new approaches for accurately estimating all three CKD model parameters, including noise power. The first method integrates, in an iterative fashion, the noise power estimation, using one-dimensional nonlinear curve fitting,
with the estimation of the shape and scale parameters, using closed-form solutions in terms of the CKD intensity moments. The second method is similar to the first except it replaces integer-based intensity moments with fractional moments which have been shown to achieve more accurate estimates of the shape parameter. These new methods can be implemented in real time without requiring large data records. They can also achieve accurate estimation performance as demonstrated with simulated and real sea clutter observation datasets. The work also investigates the numerically computed Cram\'er-Rao lower bound (CRLB) of the variance of the shape parameter estimate using intensity observations in thermal noise with unknown power. Using the CRLB, the asymptotic estimation performance behavior of the new estimators is studied and compared to that of other estimators.
ContributorsNorthrop, Judith (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Maurer, Alexander (Committee member) / Arizona State University (Publisher)
Created2019
Description
The open nature of the wireless communication medium makes it inherently vulnerable to an active attack, wherein a malicious adversary (or jammer) transmits into the medium to disrupt the operation of the legitimate users. Therefore, developing techniques to manage the presence of a jammer and to characterize the effect of an attacker on the fundamental limits of wireless communication networks is important. This dissertation studies various Gaussian communication networks in the presence of such an adversarial jammer.
First of all, a standard Gaussian channel is considered in the presence of a jammer, known as a Gaussian arbitrarily-varying channel, but with list-decoding at the receiver. The receiver decodes a list of messages, instead of only one message, with the goal of the correct message being an element of the list. The capacity is characterized, and it is shown that under some transmitter's power constraints the adversary is able to suspend the communication between the legitimate users and make the capacity zero.
Next, generalized packing lemmas are introduced for Gaussian adversarial channels to achieve the capacity bounds for three Gaussian multi-user channels in the presence of adversarial jammers. Inner and outer bounds on the capacity regions of Gaussian multiple-access channels, Gaussian broadcast channels, and Gaussian interference channels are derived in the presence of malicious jammers. For the Gaussian multiple-access channels with jammer, the capacity bounds coincide. In this dissertation, the adversaries can send any arbitrary signals to the channel while none of the transmitter and the receiver knows the adversarial signals' distribution.
Finally, the capacity of the standard point-to-point Gaussian fading channel in the presence of one jammer is investigated under multiple scenarios of channel state information availability, which is the knowledge of exact fading coefficients. The channel state information is always partially or fully known at the receiver to decode the message while the transmitter or the adversary may or may not have access to this information. Here, the adversary model is the same as the previous cases with no knowledge about the user's transmitted signal except possibly the knowledge of the fading path.
First of all, a standard Gaussian channel is considered in the presence of a jammer, known as a Gaussian arbitrarily-varying channel, but with list-decoding at the receiver. The receiver decodes a list of messages, instead of only one message, with the goal of the correct message being an element of the list. The capacity is characterized, and it is shown that under some transmitter's power constraints the adversary is able to suspend the communication between the legitimate users and make the capacity zero.
Next, generalized packing lemmas are introduced for Gaussian adversarial channels to achieve the capacity bounds for three Gaussian multi-user channels in the presence of adversarial jammers. Inner and outer bounds on the capacity regions of Gaussian multiple-access channels, Gaussian broadcast channels, and Gaussian interference channels are derived in the presence of malicious jammers. For the Gaussian multiple-access channels with jammer, the capacity bounds coincide. In this dissertation, the adversaries can send any arbitrary signals to the channel while none of the transmitter and the receiver knows the adversarial signals' distribution.
Finally, the capacity of the standard point-to-point Gaussian fading channel in the presence of one jammer is investigated under multiple scenarios of channel state information availability, which is the knowledge of exact fading coefficients. The channel state information is always partially or fully known at the receiver to decode the message while the transmitter or the adversary may or may not have access to this information. Here, the adversary model is the same as the previous cases with no knowledge about the user's transmitted signal except possibly the knowledge of the fading path.
ContributorsHosseinigoki, Fatemeh (Author) / Kosut, Oliver (Thesis advisor) / Zhang, Junshan (Committee member) / Sankar, Lalitha (Committee member) / Bliss, Daniel (Committee member) / Arizona State University (Publisher)
Created2019
Description
The emergence of perovskite and practical efficiency limit to silicon solar cells has opened door for perovskite and silicon based tandems with the possibility to achieve >30% efficiency. However, there are material and optical challenges that have to be overcome for the success of these tandems. In this work the aim is to understand and improve the light management issues in silicon and perovskite based tandems through comprehensive optical modeling and simulation of current state of the art tandems and by characterizing the optical properties of new top and bottom cell materials. Moreover, to propose practical solutions to mitigate some of the optical losses.
Highest efficiency single-junction silicon and bottom silicon sub-cell in silicon based tandems employ monocrystalline silicon wafer textured with random pyramids. Therefore, the light trapping performance of random pyramids in silicon solar cells is established. An accurate three-dimensional height map of random pyramids is captured and ray-traced to record the angular distribution of light inside the wafer which shows random pyramids trap light as well as Lambertian scatterer.
Second, the problem of front-surface reflectance common to all modules, planar solar cells and to silicon and perovskite based tandems is dealt. A nano-imprint lithography procedure is developed to fabricate polydimethylsiloxane (PDMS) scattering layer carrying random pyramids that effectively reduces the reflectance. Results show it increased the efficiency of planar semi-transparent perovskite solar cell by 10.6% relative.
Next a detailed assessment of light-management in practical two-terminal perovskite/silicon and perovskite/perovskite tandems is performed to quantify reflectance, parasitic and light-trapping losses. For this first a methodology based on spectroscopic ellipsometry is developed to characterize new absorber materials employed in tandems. Characterized materials include wide-bandgap (CH3NH3I3, CsyFA1-yPb(BrxI1-x)3) and low-bandgap (Cs0.05FA0.5MA0.45(Pb0.5Sn0.5)I3) perovskites and wide-bandgap CdTe alloys (CdZnSeTe). Using this information rigorous optical modeling of two-terminal perovskite/silicon and perovskite/perovskite tandems with varying light management schemes is performed. Thus providing a guideline for further development.
Highest efficiency single-junction silicon and bottom silicon sub-cell in silicon based tandems employ monocrystalline silicon wafer textured with random pyramids. Therefore, the light trapping performance of random pyramids in silicon solar cells is established. An accurate three-dimensional height map of random pyramids is captured and ray-traced to record the angular distribution of light inside the wafer which shows random pyramids trap light as well as Lambertian scatterer.
Second, the problem of front-surface reflectance common to all modules, planar solar cells and to silicon and perovskite based tandems is dealt. A nano-imprint lithography procedure is developed to fabricate polydimethylsiloxane (PDMS) scattering layer carrying random pyramids that effectively reduces the reflectance. Results show it increased the efficiency of planar semi-transparent perovskite solar cell by 10.6% relative.
Next a detailed assessment of light-management in practical two-terminal perovskite/silicon and perovskite/perovskite tandems is performed to quantify reflectance, parasitic and light-trapping losses. For this first a methodology based on spectroscopic ellipsometry is developed to characterize new absorber materials employed in tandems. Characterized materials include wide-bandgap (CH3NH3I3, CsyFA1-yPb(BrxI1-x)3) and low-bandgap (Cs0.05FA0.5MA0.45(Pb0.5Sn0.5)I3) perovskites and wide-bandgap CdTe alloys (CdZnSeTe). Using this information rigorous optical modeling of two-terminal perovskite/silicon and perovskite/perovskite tandems with varying light management schemes is performed. Thus providing a guideline for further development.
ContributorsManzoor, Salman (Author) / Holman, Zachary C (Thesis advisor) / King, Richard (Committee member) / Goryll, Michael (Committee member) / Zhao, Yuji (Committee member) / Arizona State University (Publisher)
Created2019
Description
Wurtzite (In, Ga, Al) N semiconductors, especially InGaN material systems, demonstrate immense promises for the high efficiency thin film photovoltaic (PV) applications for future generation. Their unique and intriguing merits include continuously tunable wide band gap from 0.70 eV to 3.4 eV, strong absorption coefficient on the order of ∼105 cm−1, superior radiation resistance under harsh environment, and high saturation velocities and high mobility. Calculation from the detailed balance model also revealed that in multi-junction (MJ) solar cell device, materials with band gaps higher than 2.4 eV are required to achieve PV efficiencies greater than 50%, which is practically and easily feasible for InGaN materials. Other state-of-art modeling on InGaN solar cells also demonstrate great potential for applications of III-nitride solar cells in four-junction solar cell devices as well as in the integration with a non-III-nitride junction in multi-junction devices.
This dissertation first theoretically analyzed loss mechanisms and studied the theoretical limit of PV performance of InGaN solar cells with a semi-analytical model. Then three device design strategies are proposed to study and improve PV performance: band polarization engineering, structural design and band engineering. Moreover, three physical mechanisms related to high temperature performance of InGaN solar cells have been thoroughly investigated: thermal reliability issue, enhanced external quantum efficiency (EQE) and conversion efficiency with rising temperatures and carrier dynamics and localization effects inside nonpolar m-plane InGaN quantum wells (QWs) at high temperatures. In the end several future work will also be proposed.
Although still in its infancy, past and projected future progress of device design will ultimately achieve this very goal that III-nitride based solar cells will be indispensable for today and future’s society, technologies and society.
This dissertation first theoretically analyzed loss mechanisms and studied the theoretical limit of PV performance of InGaN solar cells with a semi-analytical model. Then three device design strategies are proposed to study and improve PV performance: band polarization engineering, structural design and band engineering. Moreover, three physical mechanisms related to high temperature performance of InGaN solar cells have been thoroughly investigated: thermal reliability issue, enhanced external quantum efficiency (EQE) and conversion efficiency with rising temperatures and carrier dynamics and localization effects inside nonpolar m-plane InGaN quantum wells (QWs) at high temperatures. In the end several future work will also be proposed.
Although still in its infancy, past and projected future progress of device design will ultimately achieve this very goal that III-nitride based solar cells will be indispensable for today and future’s society, technologies and society.
ContributorsHuang, Xuanqi (Author) / Zhao, Yuji (Thesis advisor) / Goodnick, Stephen M. (Committee member) / King, Richard R. (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2020
Description
A model of self-heating is incorporated into a Cellular Monte Carlo (CMC) particle-based device simulator through the solution of an energy balance equation (EBE) for phonons. The EBE self-consistently couples charge and heat transport in the simulation through a novel approach to computing the heat generation rate in the device under study. First, the moments of the Boltzmann Transport equation (BTE) are discussed, and subsequently the EBE of for phonons is derived. Subsequently, several tests are performed to verify the applicability and accuracy of a nonlinear iterative method for the solution of the EBE in the presence of convective boundary conditions, as compared to a finite element analysis solver as well as using the Kirchhoff transformation. The coupled electrothermal characterization of a GaN/AlGaN high electron mobility transistor (HEMT) is then performed, and the effects of non-ideal interfaces and boundary conditions are studied.
The proposed thermal model is then applied to a novel $\Pi$-gate architecture which has been suggested to reduce hot electron generation in the device, compared to the conventional T-gate. Additionally, small signal ac simulations are performed for the determination of cutoff frequencies using the thermal model as well.
Finally, further extensions of the CMC algorithm used in this work are discussed, including 1) higher-order moments of the phonon BTE, 2) coupling to phonon Monte Carlo simulations, and 3) application to other large-bandgap, and therefore high-power, materials such as diamond.
The proposed thermal model is then applied to a novel $\Pi$-gate architecture which has been suggested to reduce hot electron generation in the device, compared to the conventional T-gate. Additionally, small signal ac simulations are performed for the determination of cutoff frequencies using the thermal model as well.
Finally, further extensions of the CMC algorithm used in this work are discussed, including 1) higher-order moments of the phonon BTE, 2) coupling to phonon Monte Carlo simulations, and 3) application to other large-bandgap, and therefore high-power, materials such as diamond.
ContributorsMerrill, Ky (Author) / Saraniti, Marco (Thesis advisor) / Goodnick, Stephen (Committee member) / Smith, David (Committee member) / Wang, Robert (Committee member) / Arizona State University (Publisher)
Created2020