ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- Genre: Masters Thesis
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
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
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
This dissertation is focused on developing an algorithm to provide current state estimation and future state predictions for biomechanical human walking features. The goal is to develop a system which is capable of evaluating the current action a subject is taking while walking and then use this to predict the future states of biomechanical features.
This work focuses on the exploration and analysis of Interaction Primitives (Amor er al, 2014) and their relevance to biomechanical prediction for human walking. Built on the framework of Probabilistic Movement Primitives, Interaction Primitives utilize an EKF SLAM algorithm to localize and map a distribution over the weights of a set of basis functions. The prediction properties of Bayesian Interaction Primitives were utilized to predict real-time foot forces from a 9 degrees of freedom IMUs mounted to a subjects tibias. This method shows that real-time human biomechanical features can be predicted and have a promising link to real-time controls applications.
This work focuses on the exploration and analysis of Interaction Primitives (Amor er al, 2014) and their relevance to biomechanical prediction for human walking. Built on the framework of Probabilistic Movement Primitives, Interaction Primitives utilize an EKF SLAM algorithm to localize and map a distribution over the weights of a set of basis functions. The prediction properties of Bayesian Interaction Primitives were utilized to predict real-time foot forces from a 9 degrees of freedom IMUs mounted to a subjects tibias. This method shows that real-time human biomechanical features can be predicted and have a promising link to real-time controls applications.
ContributorsClark, Geoffrey Mitchell (Author) / Ben Amor, Heni (Thesis advisor) / Si, Jennie (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2018
Description
Unmanned aerial vehicles (UAVs) are widely used in many applications because of their small size, great mobility and hover performance. This has been a consequence of the fast development of electronics, cheap lightweight flight controllers for accurate positioning and cameras. This thesis describes modeling, control and design of an oblique-cross-quadcopter platform for indoor-environments.
One contribution of the work was the design of a new printed-circuit-board (PCB) flight controller (called MARK3). Key features/capabilities are as follows:
(1) a Teensy 3.2 microcontroller with 168MHz overclock –used for communications, full-state estimation and inner-outer loop hierarchical rate-angle-speed-position control,
(2) an on-board MEMS inertial-measurement-unit (IMU) which includes an LSM303D (3DOF-accelerometer and magnetometer), an L3GD20 (3DOF-gyroscope) and a BMP180 (barometer) for attitude estimation (barometer/magnetometer not used),
(3) 6 pulse-width-modulator (PWM) output pins supports up to 6 rotors
(4) 8 PWM input pins support up to 8-channel 2.4 GHz transmitter/receiver for manual control,
(5) 2 5V servo extension outputs for other requirements (e.g. gimbals),
(6) 2 universal-asynchronous-receiver-transmitter (UART) serial ports - used by flight controller to process data from Xbee; can be used for accepting outer-loop position commands from NVIDIA TX2 (future work),
(7) 1 I2C-serial-protocol two-wire port for additional modules (used to read data from IMU at 400 Hz),
(8) a 20-pin port for Xbee telemetry module connection; permits Xbee transceiver on desktop PC to send position/attitude commands to Xbee transceiver on quadcopter.
The quadcopter platform consists of the new MARK3 PCB Flight Controller, an ATG-250 carbon-fiber frame (250 mm), a DJI Snail propulsion-system (brushless-three-phase-motor, electronic-speed-controller (ESC) and propeller), an HTC VIVE Tracker and RadioLink R9DS 9-Channel 2.4GHz Receiver. This platform is completely compatible with the HTC VIVE Tracking System (HVTS) which has 7ms latency, submillimeter accuracy and a much lower price compared to other millimeter-level tracking systems.
The thesis describes nonlinear and linear modeling of the quadcopter’s 6DOF rigid-body dynamics and brushless-motor-actuator dynamics. These are used for hierarchical-classical-control-law development near hover. The HVTS was used to demonstrate precision hover-control and path-following. Simulation and measured flight-data are shown to be similar. This work provides a foundation for future precision multi-quadcopter formation-flight-control.
One contribution of the work was the design of a new printed-circuit-board (PCB) flight controller (called MARK3). Key features/capabilities are as follows:
(1) a Teensy 3.2 microcontroller with 168MHz overclock –used for communications, full-state estimation and inner-outer loop hierarchical rate-angle-speed-position control,
(2) an on-board MEMS inertial-measurement-unit (IMU) which includes an LSM303D (3DOF-accelerometer and magnetometer), an L3GD20 (3DOF-gyroscope) and a BMP180 (barometer) for attitude estimation (barometer/magnetometer not used),
(3) 6 pulse-width-modulator (PWM) output pins supports up to 6 rotors
(4) 8 PWM input pins support up to 8-channel 2.4 GHz transmitter/receiver for manual control,
(5) 2 5V servo extension outputs for other requirements (e.g. gimbals),
(6) 2 universal-asynchronous-receiver-transmitter (UART) serial ports - used by flight controller to process data from Xbee; can be used for accepting outer-loop position commands from NVIDIA TX2 (future work),
(7) 1 I2C-serial-protocol two-wire port for additional modules (used to read data from IMU at 400 Hz),
(8) a 20-pin port for Xbee telemetry module connection; permits Xbee transceiver on desktop PC to send position/attitude commands to Xbee transceiver on quadcopter.
The quadcopter platform consists of the new MARK3 PCB Flight Controller, an ATG-250 carbon-fiber frame (250 mm), a DJI Snail propulsion-system (brushless-three-phase-motor, electronic-speed-controller (ESC) and propeller), an HTC VIVE Tracker and RadioLink R9DS 9-Channel 2.4GHz Receiver. This platform is completely compatible with the HTC VIVE Tracking System (HVTS) which has 7ms latency, submillimeter accuracy and a much lower price compared to other millimeter-level tracking systems.
The thesis describes nonlinear and linear modeling of the quadcopter’s 6DOF rigid-body dynamics and brushless-motor-actuator dynamics. These are used for hierarchical-classical-control-law development near hover. The HVTS was used to demonstrate precision hover-control and path-following. Simulation and measured flight-data are shown to be similar. This work provides a foundation for future precision multi-quadcopter formation-flight-control.
ContributorsLu, Shi (Author) / Rodriguez, Armando A. (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2018
Description
This thesis addresses control design for fixed-wing air-breathing aircraft. Four aircraft with distinct dynamical properties are considered: a scram-jet powered hypersonic (100foot long, X-43 like, wedge shaped) aircraft with flexible modes operating near Mach 8, 85k ft, a NASA HiMAT (Highly Maneuverable Aircraft Technology) F-18 aircraft,
a McDonnell Douglas AV-8A Harrier aircraft, and a Vought F-8 Crusader aircraft. A two-input two-output (TITO) longitudinal LTI (linear time invariant) dynamical model is used for each aircraft. Control design trade studies are conducted for each of the aircraft. Emphasis is placed on the hypersonic vehicle because of its complex nonlinear (unstable, non-minimum phase, flexible) dynamics and uncertainty associated with hypersonic flight (Mach $>$ 5, shocks and high temperatures on leading edges). Two plume models are used for the hypersonic vehicle – an old plume model and a new plume model. The old plume model is simple and assumes a typical decaying pressure distribution for aft nozzle. The new plume model uses Newtonian impact theory and a nonlinear solver to compute the aft nozzle pressure distribution. Multivariable controllers were generated using standard weighted $H_{\inf}$ mixed-sensitivity optimization as well as a new input disturbance weighted mixed-sensitivity framework that attempts to achieve good multivariable properties at both the controls (plant inputs) as well as the errors (plant outputs). Classical inner-outer (PD-PI) structures (partially centralized and decentralized) were also used. It is shown that while these classical (sometimes partially centralized PD-PI) structures could be used to generate comparable results to the multivariable controllers (e.g. for the hypersonic vehicle, Harrier, F-8), considerable tuning (iterative optimization) is often essential. This is especially true for the highly coupled hypersonic vehicle – thus justifying the need for a good multivariable control design tool. Fundamental control design tradeoffs for each aircraft are presented – comprehensively for the hypersonic aircraft. In short, the thesis attempts to shed light on when complex controllers are essential and when simple structures are sufficient for achieving control designs with good multivariable loop properties at both the errors (plant outputs) and the controls (plant inputs).
a McDonnell Douglas AV-8A Harrier aircraft, and a Vought F-8 Crusader aircraft. A two-input two-output (TITO) longitudinal LTI (linear time invariant) dynamical model is used for each aircraft. Control design trade studies are conducted for each of the aircraft. Emphasis is placed on the hypersonic vehicle because of its complex nonlinear (unstable, non-minimum phase, flexible) dynamics and uncertainty associated with hypersonic flight (Mach $>$ 5, shocks and high temperatures on leading edges). Two plume models are used for the hypersonic vehicle – an old plume model and a new plume model. The old plume model is simple and assumes a typical decaying pressure distribution for aft nozzle. The new plume model uses Newtonian impact theory and a nonlinear solver to compute the aft nozzle pressure distribution. Multivariable controllers were generated using standard weighted $H_{\inf}$ mixed-sensitivity optimization as well as a new input disturbance weighted mixed-sensitivity framework that attempts to achieve good multivariable properties at both the controls (plant inputs) as well as the errors (plant outputs). Classical inner-outer (PD-PI) structures (partially centralized and decentralized) were also used. It is shown that while these classical (sometimes partially centralized PD-PI) structures could be used to generate comparable results to the multivariable controllers (e.g. for the hypersonic vehicle, Harrier, F-8), considerable tuning (iterative optimization) is often essential. This is especially true for the highly coupled hypersonic vehicle – thus justifying the need for a good multivariable control design tool. Fundamental control design tradeoffs for each aircraft are presented – comprehensively for the hypersonic aircraft. In short, the thesis attempts to shed light on when complex controllers are essential and when simple structures are sufficient for achieving control designs with good multivariable loop properties at both the errors (plant outputs) and the controls (plant inputs).
ContributorsMondal, Kaustav (Author) / Rodriguez, Armando Antonio (Thesis advisor) / Tsakalis, Kostas (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2015
Description
A systematic top down approach to minimize risk and maximize the profits of an investment over a given period of time is proposed. Macroeconomic factors such as Gross Domestic Product (GDP), Consumer Price Index (CPI), Outstanding Consumer Credit, Industrial Production Index, Money Supply (MS), Unemployment Rate, and Ten-Year Treasury are used to predict/estimate asset (sector ETF`s) returns. Fundamental ratios of individual stocks are used to predict the stock returns. An a priori known cash-flow sequence is assumed available for investment. Given the importance of sector performance on stock performance, sector based Exchange Traded Funds (ETFs) for the S&P; and Dow Jones are considered and wealth is allocated. Mean variance optimization with risk and return constraints are used to distribute the wealth in individual sectors among the selected stocks. The results presented should be viewed as providing an outer control/decision loop generating sector target allocations that will ultimately drive an inner control/decision loop focusing on stock selection. Receding horizon control (RHC) ideas are exploited to pose and solve two relevant constrained optimization problems. First, the classic problem of wealth maximization subject to risk constraints (as measured by a metric on the covariance matrices) is considered. Special consideration is given to an optimization problem that attempts to minimize the peak risk over the prediction horizon, while trying to track a wealth objective. It is concluded that this approach may be particularly beneficial during downturns - appreciably limiting downside during downturns while providing most of the upside during upturns. Investment in stocks during upturns and in sector ETF`s during downturns is profitable.
ContributorsChitturi, Divakar (Author) / Rodriguez, Armando (Thesis advisor) / Tsakalis, Konstantinos S (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2010
Description
This thesis presents a multi-modal motion tracking system for stroke patient rehabilitation. This system deploys two sensor modules: marker-based motion capture system and inertial measurement unit (IMU). The integrated system provides real-time measurement of the right arm and trunk movement, even in the presence of marker occlusion. The information from the two sensors is fused through quaternion-based recursive filters to promise robust detection of torso compensation (undesired body motion). Since this algorithm allows flexible sensor configurations, it presents a framework for fusing the IMU data and vision data that can adapt to various sensor selection scenarios. The proposed system consequently has the potential to improve both the robustness and flexibility of the sensing process. Through comparison between the complementary filter, the extended Kalman filter (EKF), the unscented Kalman filter (UKF) and the particle filter (PF), the experimental part evaluated the performance of the quaternion-based complementary filter for 10 sensor combination scenarios. Experimental results demonstrate the favorable performance of the proposed system in case of occlusion. Such investigation also provides valuable information for filtering algorithm and strategy selection in specific sensor applications.
ContributorsLiu, Yangzi (Author) / Qian, Gang (Thesis advisor) / Olson, Loren (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2010