Matching Items (250)
Description
Lossy compression is a form of compression that slightly degrades a signal in ways that are ideally not detectable to the human ear. This is opposite to lossless compression, in which the sample is not degraded at all. While lossless compression may seem like the best option, lossy compression, which is used in most audio and video, reduces transmission time and results in much smaller file sizes. However, this compression can affect quality if it goes too far. The more compression there is on a waveform, the more degradation there is, and once a file is lossy compressed, this process is not reversible. This project will observe the degradation of an audio signal after the application of Singular Value Decomposition compression, a lossy compression that eliminates singular values from a signal’s matrix.
ContributorsHirte, Amanda (Author) / Kosut, Oliver (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
The theme for this work is the development of fast numerical algorithms for sparse optimization as well as their applications in medical imaging and source localization using sensor array processing. Due to the recently proposed theory of Compressive Sensing (CS), the $\ell_1$ minimization problem attracts more attention for its ability to exploit sparsity. Traditional interior point methods encounter difficulties in computation for solving the CS applications. In the first part of this work, a fast algorithm based on the augmented Lagrangian method for solving the large-scale TV-$\ell_1$ regularized inverse problem is proposed. Specifically, by taking advantage of the separable structure, the original problem can be approximated via the sum of a series of simple functions with closed form solutions. A preconditioner for solving the block Toeplitz with Toeplitz block (BTTB) linear system is proposed to accelerate the computation. An in-depth discussion on the rate of convergence and the optimal parameter selection criteria is given. Numerical experiments are used to test the performance and the robustness of the proposed algorithm to a wide range of parameter values. Applications of the algorithm in magnetic resonance (MR) imaging and a comparison with other existing methods are included. The second part of this work is the application of the TV-$\ell_1$ model in source localization using sensor arrays. The array output is reformulated into a sparse waveform via an over-complete basis and study the $\ell_p$-norm properties in detecting the sparsity. An algorithm is proposed for minimizing a non-convex problem. According to the results of numerical experiments, the proposed algorithm with the aid of the $\ell_p$-norm can resolve closely distributed sources with higher accuracy than other existing methods.
ContributorsShen, Wei (Author) / Mittlemann, Hans D (Thesis advisor) / Renaut, Rosemary A. (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Gelb, Anne (Committee member) / Ringhofer, Christian (Committee member) / Arizona State University (Publisher)
Created2011
Description
There is increasing interest in the medical and behavioral health communities towards developing effective strategies for the treatment of chronic diseases. Among these lie adaptive interventions, which consider adjusting treatment dosages over time based on participant response. Control engineering offers a broad-based solution framework for optimizing the effectiveness of such interventions. In this thesis, an approach is proposed to develop dynamical models and subsequently, hybrid model predictive control schemes for assigning optimal dosages of naltrexone, an opioid antagonist, as treatment for a chronic pain condition known as fibromyalgia. System identification techniques are employed to model the dynamics from the daily diary reports completed by participants of a blind naltrexone intervention trial. These self-reports include assessments of outcomes of interest (e.g., general pain symptoms, sleep quality) and additional external variables (disturbances) that affect these outcomes (e.g., stress, anxiety, and mood). Using prediction-error methods, a multi-input model describing the effect of drug, placebo and other disturbances on outcomes of interest is developed. This discrete time model is approximated by a continuous second order model with zero, which was found to be adequate to capture the dynamics of this intervention. Data from 40 participants in two clinical trials were analyzed and participants were classified as responders and non-responders based on the models obtained from system identification. The dynamical models can be used by a model predictive controller for automated dosage selection of naltrexone using feedback/feedforward control actions in the presence of external disturbances. The clinical requirement for categorical (i.e., discrete-valued) drug dosage levels creates a need for hybrid model predictive control (HMPC). The controller features a multiple degree-of-freedom formulation that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed loop system. The nominal and robust performance of the proposed control scheme is examined via simulation using system identification models from a representative participant in the naltrexone intervention trial. The controller evaluation described in this thesis gives credibility to the promise and applicability of control engineering principles for optimizing adaptive interventions.
ContributorsDeśapāṇḍe, Sunīla (Author) / Rivera, Daniel E. (Thesis advisor) / Si, Jennie (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2011
Description
Due to restructuring and open access to the transmission system, modern electric power systems are being operated closer to their operational limits. Additionally, the secure operational limits of modern power systems have become increasingly difficult to evaluate as the scale of the network and the number of transactions between utilities increase. To account for these challenges associated with the rapid expansion of electric power systems, dynamic equivalents have been widely applied for the purpose of reducing the computational effort of simulation-based transient security assessment. Dynamic equivalents are commonly developed using a coherency-based approach in which a retained area and an external area are first demarcated. Then the coherent generators in the external area are aggregated and replaced by equivalenced models, followed by network reduction and load aggregation. In this process, an improperly defined retained area can result in detrimental impacts on the effectiveness of the equivalents in preserving the dynamic characteristics of the original unreduced system. In this dissertation, a comprehensive approach has been proposed to determine an appropriate retained area boundary by including the critical generators in the external area that are tightly coupled with the initial retained area. Further-more, a systematic approach has also been investigated to efficiently predict the variation in generator slow coherency behavior when the system operating condition is subject to change. Based on this determination, the critical generators in the external area that are tightly coherent with the generators in the initial retained area are retained, resulting in a new retained area boundary. Finally, a novel hybrid dynamic equivalent, consisting of both a coherency-based equivalent and an artificial neural network (ANN)-based equivalent, has been proposed and analyzed. The ANN-based equivalent complements the coherency-based equivalent at all the retained area boundary buses, and it is designed to compensate for the discrepancy between the full system and the conventional coherency-based equivalent. The approaches developed have been validated on a large portion of the Western Electricity Coordinating Council (WECC) system and on a test case including a significant portion of the eastern interconnection.
ContributorsMa, Feng (Author) / Vittal, Vijay (Thesis advisor) / Tylavsky, Daniel (Committee member) / Heydt, Gerald (Committee member) / Si, Jennie (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2011
Description
Proportional-Integral-Derivative (PID) controllers are a versatile category of controllers that are commonly used in the industry as control systems due to the ease of their implementation and low cost. One problem that continues to intrigue control designers is the matter of finding a good combination of the three parameters - P, I and D of these controllers so that system stability and optimum performance is achieved. Also, a certain amount of robustness to the process is expected from the PID controllers. In the past, many different methods for tuning PID parameters have been developed. Some notable techniques are the Ziegler-Nichols, Cohen-Coon, Astrom methods etc. For all these techniques, a simple limitation remained with the fact that for a particular system, there can be only one set of tuned parameters; i.e. there are no degrees of freedom involved to readjust the parameters for a given system to achieve, for instance, higher bandwidth. Another limitation in most cases is where a controller is designed in continuous time then converted into discrete-time for computer implementation. The drawback of this method is that some robustness due to phase and gain margin is lost in the process. In this work a method of tuning PID controllers using a loop-shaping approach has been developed where the bandwidth of the system can be chosen within an acceptable range. The loop-shaping is done against a Glover-McFarlane type ℋ∞ controller which is widely accepted as a robust control design method. The numerical computations are carried out entirely in discrete-time so there is no loss of robustness due to conversion and approximations near Nyquist frequencies. Some extra degrees of freedom owing to choice of bandwidth and capability of choosing loop-shapes are also involved and are discussed in detail. Finally, comparisons of this method against existing techniques for tuning PID controllers both in continuous and in discrete-time are shown. The results tell us that our design performs well for loop-shapes that are achievable through a PID controller.
ContributorsShafique, Md. Ashfaque Bin (Author) / Tsakalis, Konstantinos S. (Thesis advisor) / Rodriguez, Armando A. (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2011
Description
This study focuses on state estimation of nonlinear discrete time systems with constraints. Physical processes have inherent in them, constraints on inputs, outputs, states and disturbances. These constraints can provide additional information to the estimator in estimating states from the measured output. Recursive filters such as Kalman Filters or Extended Kalman Filters are commonly used in state estimation; however, they do not allow inclusion of constraints in their formulation. On the other hand, computational complexity of full information estimation (using all measurements) grows with iteration and becomes intractable. One way of formulating the recursive state estimation problem with constraints is the Moving Horizon Estimation (MHE) approximation. Estimates of states are calculated from the solution of a constrained optimization problem of fixed size. Detailed formulation of this strategy is studied and properties of this estimation algorithm are discussed in this work. The problem with the MHE formulation is solving an optimization problem in each iteration which is computationally intensive. State estimation with constraints can be formulated as Extended Kalman Filter (EKF) with a projection applied to estimates. The states are estimated from the measurements using standard Extended Kalman Filter (EKF) algorithm and the estimated states are projected on to a constrained set. Detailed formulation of this estimation strategy is studied and the properties associated with this algorithm are discussed. Both these state estimation strategies (MHE and EKF with projection) are tested with examples from the literature. The average estimation time and the sum of square estimation error are used to compare performance of these estimators. Results of the case studies are analyzed and trade-offs are discussed.
ContributorsJoshi, Rakesh (Author) / Tsakalis, Konstantinos (Thesis advisor) / Rodriguez, Armando (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis discusses control and obstacle avoidance for non-holonomic differential drive mobile vehicles. The two important behaviors for the vehicle can be defined as go to goal and obstacle avoidance behavior. This thesis discusses both behaviors in detail. Go to goal behavior is the ability of the mobile vehicle to go from one particular co-ordinate to another. Cruise control, cartesian and posture stabilization problems are discussed as the part of this behavior. Control strategies used for the above three problems are explained in the thesis. Matlab simulations are presented to verify these controllers. Obstacle avoidance behavior ensures that the vehicle doesn't hit object in its path while going towards the goal. Three different techniques for obstacle avoidance which are useful for different kind of obstacles are described in the thesis. Matlab simulations are presented to show and discuss the three techniques. The controls discussed for the cartesian and posture stabilization were implemented on a low cost miniature vehicle to verify the results practically. The vehicle is described in the thesis in detail. The practical results are compared with the simulations. Hardware and matlab codes have been provided as a reference for the reader.
ContributorsChopra, Dhruv (Author) / Rodriguez, Armando A (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013
Description
The problem of systematically designing a control system continues to remain a subject of intense research. In this thesis, a very powerful control system design environment for Linear Time-Invariant (LTI) Multiple-Input Multiple-Output (MIMO) plants is presented. The environment has been designed to address a broad set of closed loop metrics and constraints; e.g. weighted H-infinity closed loop performance subject to closed loop frequency and/or time domain constraints (e.g. peak frequency response, peak overshoot, peak controls, etc.). The general problem considered - a generalized weighted mixed-sensitivity problem subject to constraints - permits designers to directly address and tradeoff multivariable properties at distinct loop breaking points; e.g. at plant outputs and at plant inputs. As such, the environment is particularly powerful for (poorly conditioned) multivariable plants. The Youla parameterization is used to parameterize the set of all stabilizing LTI proper controllers. This is used to convexify the general problem being addressed. Several bases are used to turn the resulting infinite-dimensional problem into a finite-dimensional problem for which there exist many efficient convex optimization algorithms. A simple cutting plane algorithm is used within the environment. Academic and physical examples are presented to illustrate the utility of the environment.
ContributorsPuttannaiah, Karan (Author) / Rodriguez, Armando A (Thesis advisor) / Tsakalis, Konstantinos S (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013
Description
Radio frequency (RF) transceivers require a disproportionately high effort in terms of test development time, test equipment cost, and test time. The relatively high test cost stems from two contributing factors. First, RF transceivers require the measurement of a diverse set of specifications, requiring multiple test set-ups and long test times, which complicates load-board design, debug, and diagnosis. Second, high frequency operation necessitates the use of expensive equipment, resulting in higher per second test time cost compared with mixed-signal or digital circuits. Moreover, in terms of the non-recurring engineering cost, the need to measure complex specfications complicates the test development process and necessitates a long learning process for test engineers. Test time is dominated by changing and settling time for each test set-up. Thus, single set-up test solutions are desirable. Loop-back configuration where the transmitter output is connected to the receiver input are used as the desirable test set- up for RF transceivers, since it eliminates the reliance on expensive instrumentation for RF signal analysis and enables measuring multiple parameters at once. In-phase and Quadrature (IQ) imbalance, non-linearity, DC offset and IQ time skews are some of the most detrimental imperfections in transceiver performance. Measurement of these parameters in the loop-back mode is challenging due to the coupling between the receiver (RX) and transmitter (TX) parameters. Loop-back based solutions are proposed in this work to resolve this issue. A calibration algorithm for a subset of the above mentioned impairments is also presented. Error Vector Magnitude (EVM) is a system-level parameter that is specified for most advanced communication standards. EVM measurement often takes extensive test development efforts, tester resources, and long test times. EVM is analytically related to system impairments, which are typically measured in a production test i environment. Thus, EVM test can be eliminated from the test list if the relations between EVM and system impairments are derived independent of the circuit implementation and manufacturing process. In this work, the focus is on the WLAN standard, and deriving the relations between EVM and three of the most detrimental impairments for QAM/OFDM based systems (IQ imbalance, non-linearity, and noise). Having low cost test techniques for measuring the RF transceivers imperfections and being able to analytically compute EVM from the measured parameters is a complete test solution for RF transceivers. These techniques along with the proposed calibration method can be used in improving the yield by widening the pass/fail boundaries for transceivers imperfections. For all of the proposed methods, simulation and hardware measurements prove that the proposed techniques provide accurate characterization of RF transceivers.
ContributorsNassery, Afsaneh (Author) / Ozev, Sule (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Kiaei, Sayfe (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
Description
Synchronous buck converters have become the obvious choice of design for high efficiency voltage down-conversion applications and find wide scale usage in today's IC industry. The use of digital control in synchronous buck converters is becoming increasingly popular because of its associated advantages over traditional analog counterparts in terms of design flexibility, reduced use of off-chip components, and better programmability to enable advanced controls. They also demonstrate better immunity to noise, enhances tolerance to the process, voltage and temperature (PVT) variations, low chip area and as a result low cost. It enables processing in digital domain requiring a need of analog-digital interfacing circuit viz. Analog to Digital Converter (ADC) and Digital to Analog Converter (DAC). A Digital to Pulse Width Modulator (DPWM) acts as time domain DAC required in the control loop to modulate the ON time of the Power-MOSFETs. The accuracy and efficiency of the DPWM creates the upper limit to the steady state voltage ripple of the DC - DC converter and efficiency in low load conditions. This thesis discusses the prevalent architectures for DPWM in switched mode DC - DC converters. The design of a Hybrid DPWM is presented. The DPWM is 9-bit accurate and is targeted for a Synchronous Buck Converter with a switching frequency of 1.0 MHz. The design supports low power mode(s) for the buck converter in the Pulse Frequency Modulation (PFM) mode as well as other fail-safe features. The design implementation is digital centric making it robust across PVT variations and portable to lower technology nodes. Key target of the design is to reduce design time. The design is tested across large Process (+/- 3σ), Voltage (1.8V +/- 10%) and Temperature (-55.0 °C to 125 °C) and is in the process of tape-out.
ContributorsKumar, Amit (Author) / Bakkaloglu, Bertan (Thesis advisor) / Song, Hongjiang (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013