Doctor of Philosophy, The Ohio State University, 2013, Aero/Astro Engineering

Future aircraft engine control systems will be based on a distributed architecture, in which, the sensors and actuators will be connected to the Full Authority Digital Engine Control (FADEC) through an engine area network. Distributed engine control architecture will allow the implementation of advanced, active control techniques along with achieving weight reduction, improvement in performance and lower life cycle cost. The performance of a distributed engine control system is predominantly dependent on the performance of the communication network. Due to the serial data transmission policy, network-induced time delays and sampling jitter are introduced between the sensor/actuator nodes and the distributed FADEC. Communication network faults and transient node failures may result in data dropouts, which may not only degrade the control system performance but may even destabilize the engine control system. Three different architectures for a turbine engine control system based on a distributed framework are presented. A partially distributed control system for a turbo-shaft engine is designed based on ARINC 825 communication protocol. Stability conditions and control design methodology are developed for the proposed partially distributed turbo-shaft engine control system to guarantee the desired performance under the presence of network-induced time delay and random data loss due to transient sensor/actuator failures. A fault tolerant control design methodology is proposed to benefit from the availability of an additional system bandwidth and from the broadcast feature of the data network. It is shown that a reconfigurable fault tolerant control design can help to reduce the performance degradation in presence of node failures. A T-700 turbo-shaft engine model is used to validate the proposed control methodology based on both single input and multiple-input multiple-output control design techniques.

Doctor of Philosophy (PhD), Wright State University, 2017, Engineering PhD

The research on distributed multi-agent systems has received increasing attention due to its broad applications in numerous areas, such as unmanned ground and aerial vehicles, smart grid, sensor networks, etc. Since such distributed multi-agent systems need to operate reliably at all time, despite the possible occurrence of faulty behaviors in some agents, the development of fault-tolerant control schemes is a crucial step in achieving reliable and safe operations. The objective of this research is to develop a distributed adaptive fault-tolerant control (FTC) scheme for nonlinear uncertain multi-agent systems under intercommunication graphs with asymmetric weights. Under suitable assumptions, the closed-loop system's stability and leader-follower cooperative tracking properties are rigorously established. First, a distributed adaptive fault-tolerant control method for nonlinear uncertain first-order multi-agent systems is developed. Second, this distributed FTC method is extended to nonlinear uncertain second-order multi-agent systems. Next, adaptive-approximation-based FTC algorithms are developed for two cases of high-order multi-agent systems, i.e., with full-state measurement and with only limited output measurement, respectively. Finally, the distributed adaptive fault-tolerant formation tracking algorithms for first-order multi-agent systems are implemented and demonstrated using Wright State's real-time indoor autonomous robots test environment. The experimental formation tracking results illustrate the effectiveness of the proposed methods.

Doctor of Philosophy (PhD), Ohio University, 2007, Electrical Engineering & Computer Science (Engineering and Technology)

Linear impulsive systems are a class of hybrid systems in which the state propagates according to linear continuous-time dynamics except for a countable set of times at which the state can change instantaneously. These systems are useful in representing a number of real world applications, including the problem of drug distribution in the human body, management of renewable resources, spacecraft guidance and control, and sampled-data control systems with consideration of inter-sample behavior. While in general the impulsive effects can be time-driven and/or event-driven, this work focuses on the time-driven case. This study of linear impulsive systems starts by addressing the fundamental concepts of reachability and observability, and shows that these properties depend on whether the impulse times are fixed or free. A geometric characterization of reachable and unobservable sets in terms of invariant subspaces is developed, and algorithms for their construction are established. In particular, the concept of strong reachability, introduced here, enables the formulation of a state-feedback stabilization method for linear impulsive systems that possess these properties. When the open-loop system is strongly reachable, the weighted reachability gramian can be guaranteed to be uniformly positive definite as long as each time interval under consideration contains a sufficient number of impulses, and its inverse can be used to formulate a state feedback law that stabilizes the impulsive system even when the impulse times are not uniformly spaced. An output stabilization problem is formulated and translated into geometric terms starting with the concepts of controlled-invariant and conditioned-invariant subspaces for linear impulsive systems, for which we provide definitions and algorithms for computation. By relating controlled-invariant and conditioned-invariant subspaces of the open-loop impulsive system to invariant subspaces of the corresponding closed-loop system, it (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2020, Mechanical Engineering

Iterative learning control (ILC) has been growing in applicability, along with growth in theory for classes of linear and nonlinear systems. The current study extends the theory of ILC to hybrid systems, primarily motivated by the need to develop efficient automated procedures for the calibration of gearshift controllers. A lifted form representation of hybrid systems with input-output dependent switching rules is developed, and the proposed lifted form representation used for control design. Causality of hybrid systems in the time domain results in a (lower) triangular structure of hybrid Markov matrices in the trial domain, the triangular structure enabling systematic and efficient control design. Specifically, a solution to the required set of linear matrix inequalities (LMIs) is guaranteed to exist under mild assumptions, which is in contrast to many other studies proposing LMI based solutions in general controls literature. In addition to extending the theory of ILC to hybrid systems, and developing systematic design methods for computation of the required learning controllers, ILC of linear and hybrid systems with uncertain trial duration and linear and hybrid systems with shape-constrained control inputs, which often result from the parameterization of feedforward control inputs using look-up tables, is also studied. Robustness to system uncertainty is explicitly incorporated using the interval systems formulation, and robust learning controllers are designed for linear and hybrid systems. In addition, for ILC of systems with large variations in the operating conditions such as the initial conditions and/or external forces, a novel idea of parametric learning is introduced, the resulting ILC being termed as parametric-ILC or P-ILC. The design methods presented for the computation of learning controllers are first validated numerically for several motion control applications, and then are used for developing automated procedures for the calibration of ge (open full item for complete abstract)

Doctor of Engineering, Cleveland State University, 2015, Washkewicz College of Engineering

In this dissertation a three-bus, radial distribution system is proposed to be used as a benchmark for the study of power quality problems (PQPs) and their compensation. To mitigate PQPs in distribution systems, Custom Power Systems (CUPS) devices such as Distribution Static Compensator (D-STATCOM), Dynamic Voltage Restorer (DVR), and Unified Power Quality Conditioner (UPQC) are required. An increasingly popular and practical control technique based on Active Disturbance Rejection Control (ADRC), which is simple and has good disturbance rejection capabilities, is implemented to control CUPS devices. Its performance is compared with the highly dominating Proportional-Integral-Derivative (PID) controller. Modelling of the DVR and the D-STATCOM, together with their respective ADRC and PID controllers, were developed under the MATLAB /Simulink© environment. Simulation results, which included voltage sag/swell, voltage imbalance and current imbalance, proved that the ADRC controllers are attractive for their use with CUPS devices to mitigate the PQPs and can be considered as effective replacements for the PID controller.

Master of Science, The Ohio State University, 2015, Aero/Astro Engineering

A large number of physical continuous-time systems are controlled using digital controllers. These systems are often referred to as sample data systems or hybrid systems and they have become the norm for many real world applications. With this in mind, the impact of modeling uncertainties and time delay are considered. Maintaining stability in a system is of the upmost importance for any control system but the models which are used to develop the control laws which control the actual system are not perfect, being subject to a variety of uncertainties and errors. The goal of a robust control law is to guarantee the stability despite the uncertainty that may exist in the system while a nominal control law is designed with only single perfectly modeled design point in mind. Despite the drive toward hybrid systems in application, the focus in developing robust control methods for uncertain systems, especially as it applies to input-delayed sample data systems, has been more geared toward strictly continuous-times systems or strictly discrete-time systems. Here a methodology for designing robust digital controllers to stabilize uncertain continuous-time systems when subject to a given range of elemental uncertainty an input-delay is set forth. The inspiration for this research grew out of the challenges of implementing a distributed engine control system for gas turbine engines on aerospace vehicles. As a precursor to the development of the robust control methodology presented in this document, a study was conducted to better understand the impact of uncertainty and time delay on gas turbine engines with a vision toward implementing distributed engine control. Simulation results using linearized models of the GE T700 Turboshaft Engine and the NASA developed generic twin-spool engine model C-MAPSS40k suggest that the gas turbine engine is inherently robust in its ability to maintain stability but still no guarantee of its stability can be made using strictly nominal contr (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2008, Electrical and Computer Engineering

Hypersonic air-breathing vehicles are a promising and cost-efficient technology for launching low-earth-orbit satellites and providing rapid global-response capabilities. Modeling and control of such vehicles has been an active subject of research in recent years. A first-principle, physics-based model (FPM) of the vehicle's longitudinal dynamics has been developed at the Air Force Research Laboratory, and made available to the academic community for control systems design. This model, while suitable for simulation, is intractable for model-based control, thus requiring further control-oriented modeling. A typical control objective is to track a velocity and altitude reference while maintaining physical feasibility of the control input and the state. Two control strategies are presented in this work. The first is a linear time invariant (LTI) design based on a novel formulation of a robust servo-mechanism using singular perturbation arguments. This approach does not rely on state reconstruction but does require an analysis of a family of linearized models from the FPM. The second design relies on reduced-complexity modeling of the FPM. Intractable expressions of the forces and moment in the FPM are replaced with a curve-fit model (CFM). The CFM is expressed as a linear parameter varying (LPV) system, where the scheduling variables depend on the system output. A novel LPV regulator design methodology is developed, which explicitly addresses the case of over-actuated models (i.e., models with more inputs than performance outputs). This is a non-trivial extension of the analysis and design of output regulators for LTI systems. The LPV regulator separates the control problem into a steady-state controller and a stabilizing controller. The steady-state controller produces a non-unique approximate steady-state using receding horizon constrained optimization, while the stabilizer renders the steady-state attractive. The steady-state controller represents an approach to add (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2008, Mechanical Engineering

The gradual decline of oil reserves and the increasing demandfor energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall tank-to-wheel vehicle energy conversion efficiencies is the hybridization of electrical and conventional drive systems. Sophisticated hybrid powertrain configurations require careful coordination of the actuators and the onboard energy sources for optimum use of the energy saving benefits. The term optimality is often associated with fuel economy, although other measures such as drivability and exhaust emissions are also equally important. This dissertation focuses on the design of hybrid-electric vehicle (HEV) control strategies that aim to minimize fuel consumption while maintaining good vehicle drivability. In order to facilitate the design of controllers based on mathematical models of the HEV system, a dynamic model that is capable of predicting longitudinal vehicle responses in the low-to-mid frequency region (up to 10 Hz) is developed for a parallel HEV configuration. The model is validated using experimental data from various driving modes including electric only, engine only and hybrid. The high fidelity of the model makes it possible to accurately identify critical drivability issues such as time lags, shunt, shuffle, torque holes and hesitation. Using the information derived from the vehicle model, an energy management strategy is developed and implemented on a test vehicle. The resulting control strategy has a hybrid structure in the sense that the main mode of operation (the hybrid mode) is occasionally interrupted by event-based rules to enable the use of the engine start-stop function. The changes in the driveline dynamics during this transition further contribute to the hybrid nature of the system. To address the unique characteristics of the HEV driv (open full item for complete abstract)

Master of Science, The Ohio State University, 2003, Electrical Engineering

This thesis serves as a guideline for the development of a full one-term undergraduate laboratory course in control systems. The work presented here is mainly of experimental nature with emphasis on measurement, data acquisition and control design and analysis. The challenge behind this project was the adaptation of classical teaching and experiments in control systems to the state-of-the art implementation technologies used in the industry worldwide, while maintaining and improving the pedagogical aspects of the methodology previously followed in the Department of Electrical Engineering at The Ohio State University. First we introduce the hardware and software used in the laboratory, i.e. Quanser Consulting equipment, dSPACE computer cards and software packages, and Matlab and Simulink (Chapter 1). Then we present two laboratory experiments (Chapters 2 & 3) that serve as a tutorial introduction to these hardware and software and to digital signal processing. The next two experiments (Chapters 4 & 5) deal with system identification and basic control design using gain compensation. We then develop a series of experiments on DC servomotors to treat classical design methods such as root locus, lead, lag and PID control design (Chapters 6 through 8). We follow that with a set of experiments on more advanced apparatus such as flexible links and flexible joints (Chapters 9 &10). Chapters 11, 12, and 13 are dedicated to linear quadratic regulator (LQR) control design for the flexible joint, the flexible link and the two-degree-of-freedom helicopter; even though these chapters are not intended for use in an undergraduate laboratory course, their content can be used to develop demonstration experiments that can be presented at the beginning or the end of the term. Finally we conclude with general comments and recommendations for the future, along with an Appendix that contains an instructor's guide.

Master of Science (M.S.), University of Dayton, 2024, Aerospace Engineering

This research introduces an Origami-inspired dynamic spacecraft radiator, capable of adjusting heat rejection in response to orbital variations and extreme temperature fluctuations in lunar environments. The research centers around the square twist origami tessellation, an adaptable geometric structure with significant potential for revolutionizing radiative heat control in space. The investigative involves simulations of square twist origami tessellation panels using vector math and algebra. This study examines both a two-dimensional (2- D), infinitely thin tessellation, and a three-dimensional (3-D), rigidly-foldable tessellation, each characterized by an adjustable closure or actuation angle “φ”. Meticulously analyzed the heat loss characteristics of both the 2D and 3D radiators over a 180-degree range of actuation. Utilizing Monte Carlo Ray Tracing and the concept of “view factors”, the study quantifies radiative heat loss, exploring the interplay of emitted, interrupted, and escaped rays as the geometry adapts to various positions. This method allowed for an in-depth understanding of the changing radiative heat loss behavior as the tessellation actuates from fully closed to fully deployed. The findings reveal a significant divergence between the 2D and 3D square twist origami radiators. With an emissivity of 1, the 3D model demonstrated a slower decrease in the ratio of escaped to emitted rays (Ψ) as the closure/actuation angle increased, while the 2D model exhibited a more linear decline. This divergence underscores the superior radiative heat loss control capabilities of the 2D square twist origami geometry, offering a promising turndown ratio of 4.42, validating the model's efficiency and practicality for radiative heat loss control. Further exploration involved both non-rigidly and rigidly foldable radiator models. The non-rigidly foldable geometry, initially a theoretical concept, is realized through 3D modeling and physica (open full item for complete abstract)

Master of Science, The Ohio State University, 2017, Electrical and Computer Engineering

Modern control systems are increasingly becoming decentralized in nature, where supervision and monitoring happens remotely. An attack on the control system can cause large scale economic impact and claim human lives. Security becomes an essential part for these systems. In the thesis, we solve a decentralized control problem by modeling it as a team. An agent directly observes certain state variables. Other members may communicate to the agent some information that are not observed by the agent. The objective of the team members is to optimize a common cost function under asymmetric information. In particular, we are interested in computing the optimal strategies that the agents must adopt for minimizing a common cost function. We show that the optimization problem for static team can be reduced to a convex quadratic program under certain information structure. We identify the optimal strategies if the agents have incomplete information of states or if certain links are broken. We show that the results derived for static team can be extended to solving dynamic team with partially nested information structure. By numerical simulation studies, we identify links that can be eliminated with minimum deterioration in overall performance. Elimination of redundant links can conserve internet bandwidth for faster communication, thus reducing the effect of delay. We also identify links that are critical for better performance and which must be protected from an attack by having longer keys in encryption and decryption.

Doctor of Philosophy, Case Western Reserve University, 2004, Systems and Control Engineering

Cruse's model of leg coordination (CCM) was derived to account for gaits and gait transitions in arthropods (analogous to, e.g. walktrotgallop in some quadrupeds). It has also been adapted to control locomotion in a series of hexapod robots. CCM is a systems-level, kinematic model that abstracts key physiological and dynamical properties in favor of tractability. A key feature is that gaits emerge from interaction among pairs of legs as effected by a set of coordination mechanisms acting at discrete points in time. We represent CCM networks as systems of coupled hybrid oscillators. Gaits are quantified by a temporal (discrete) phase vector. System trajectories are polyhedral, hence solvable over finite-time, but the presence of the switching automaton renders infinite horizon properties harder to analyze. Via numerical and symbolic simulations, we have mapped out the synchronization behavior of CCM networks of various topologies parametrically. We have developed a section-map analysis approach that exploits the polyhedral geometry of the hybrid state space. Our approach is constructive. Once switching boundaries are appropriately parameterized, we can extract periodic orbits, their domains of admissibility and stability, as well as expressions for the period of oscillation and relative phase of each cycle, parametrically. Applied to 2-oscillator networks, our approach yields excellent agreement with simulation results. A key emergent concept is that of a virtual periodic orbit (VPO). Distinguished from admissible periodic orbits, VPOs do not correspond to any in the underlying hybrid dynamics. However, when stable and close to being admissible, they are canonical precursors for a class of nonsmooth bifurcations and predictive of long transient behavior. Last, we take into consideration the possibility and difficulties of extending our approach to larger networks and to related oscillator-like hybrid dynamical systems with polyhedral trajectories.

Master of Science, The Ohio State University, 1985, Graduate School

Master of Science, The Ohio State University, 1983, Graduate School

Master of Science, The Ohio State University, 1984, Graduate School

Master of Science, The Ohio State University, 1986, Graduate School

Master of Science, The Ohio State University, 1986, Graduate School

Master of Science, The Ohio State University, 1985, Graduate School

Master of Science, The Ohio State University, 1985, Graduate School

Master of Science, The Ohio State University, 1979, Graduate School