Electrical & Computer Engineering Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2765
Browse
2 results
Search Results
Item THE DESIGN AND STUDY OF THE SUB-MILLIMETER WAVE LENGTH GYROTRON AND FUNDAMENTAL AND SECOND CYCLOTRON HARMONICS(2015) Pu, Ruifeng; Granatstein, Victor L.; Nusinovich, Gregory S.; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation documents research activities directed toward designing high power, high efficiency gyrotrons to operate in the sub-millimeter wavelength region. The gyrotron is to produce pulsed RF power at 670 GHz, with possible application to a novel scheme for detecting concealed radioactive materials. High efficiency is to be achieved by designing a cavity resonator in which the electrons interact with the high-order TE31,8 mode. The choice of resonating mode helps to alleviate Ohmic losses in the cavity walls, and simulation results show that the output efficiency could be more than 30%. The design study takes into account a variety of known effects that could affect efficiency, such as orbital velocity spread, voltage depression and after-cavity interaction. The 670GHz gyrotron was built using the resonator design; operation confirmed that record high efficiency was achieved at an output power level of about 200 kilowatts. In addition, the issue of radial spread in electron guiding centers, which is related to the design of the magnetron injection gun used in the 670GHz gyrotron, was also examined. This spread degrades the interaction between the electrons and the RF field. This often overlooked issue is important for future electron gun designs; this thesis presents analytical methods for estimating how much the degradation affects gyrotron efficiency. The analytical method was verified with numerical simulation, showing that the efficiency's sensitivity to spread in guiding centers is highly dependent on the location of an annular electron beam: when the beam is injected in the inner peak of the desired mode, the radial spread should be kept to less than 1/3 of the RF wavelength. Finally, the dissertation investigates the possibility of further extending the operating parameters of the gyrotron by using the second harmonic of the electron cyclotron resonance. An average output power could be increased by operating the gyrotron continuously rather than in pulses. Using the second cyclotron harmonic allows the magnetic field requirement for resonance condition to be reduced by a factor of two, so that in 670 GHz gyrotrons the pulsed solenoid can be replaced with a cryo-magnet. The investigation shows that for the TE31,8 mode at the second cyclotron harmonic, the operating mode has only one competing mode at the fundamental cyclotron harmonic that could present a mode stability issue. Numerical simulation shows that this mode is TE11,6, the operating mode can suppress this mode, while achieving 20% interaction efficiency. Results also reveal that the resonator for the operating mode at second cyclotron harmonic must be modified to increase the Q-factor. Continuously operating gyrotrons using cryo-magnets have been used for plasma heating in controlled thermonuclear fusion research, albeit at lower frequency than the 670 GHz of the current study.Item Model Based Optimization and Design of Secure Systems(2013) Malik, Waseem Ansar; Martins, Nuno C; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)ABSTRACT Title of dissertation: MODEL BASED OPTIMIZATION AND DESIGN OF SECURE SYSTEMS Waseem Ansar Malik, Doctor of Philosophy, 2013 Dissertation directed by: Prof. Nuno C. Martins Department of Electrical and Computer Engineering University of Maryland, College Park Dr. Ananthram Swami Computational and Information Sciences Directorate Army Research Laboratory Control systems are widely used in modern industry and find wide applications in power systems, nuclear and chemical plants, the aerospace industry, robotics, communication devices, and embedded systems. All these systems typically rely on an underlying computing and networking infrastructure which has considerable security vulnerabilities. The biggest threat, in this age and time, to modern systems are cyber attacks from adversaries. Recent cyber attacks have practically shut down government websites affecting government operation, undermined financial institutions, and have even infringed on public privacy. Thus it is extremely important to conduct studies on the design and analysis of secure systems. This work is an effort in this research direction and is mainly focused on incorporating security in the design of modern control systems. In the first part of this dissertation, we present a linear quadratic optimal control problem subjected to security constraints. We consider an adversary which can make partial noisy measurements of the state. The task of the controller is to generate control sequences such that the adversary is unable to estimate the terminal state. This is done by minimizing a quadratic cost while satisfying security constraints. The resulting optimization problems are shown to be convex and the optimal solution is computed using Lagrangian based techniques. For the case when the terminal state has a discrete distribution the optimal solution is shown to be nonlinear in the terminal state. This is followed by considering the case when the terminal state has a continuous distribution. The resulting infinite dimensional optimization problems are shown to be convex and the optimal solution is proven to be affine in the terminal state. In the next part of this dissertation, we analyze several team decision problems subjected to security constraints. Specifically, we consider problem formulations where there are two decision makers each controlling a different dynamical system. Each decision maker receives information regarding the respective terminal states that it is required to reach and applies a control sequence accordingly. An adversary makes partial noisy measurements of the states and tries to estimate the respective terminal states. It is shown that the optimal solution is affine in the terminal state when it is identical for both systems. We also consider the general case where the terminal states are correlated. The resulting infinite dimensional optimization problems are shown to convex programs and we prove that the optimal solution is affine in the information available to the decision makers. Next, a stochastic receding horizon control problem is considered and analyzed. Specifically, we consider a system with bounded disturbances and hard bounds on the control inputs. Utilizing a suboptimal disturbance feedback scheme, the optimization problem is shown to be convex. The problem of minimizing the empirical mean of the cost function is analyzed. We provide bounds on the disturbance sample size to compute the empirical minimum of the problem. Further, we consider the problem where there are hard computational constraints and complex on-line optimization is not feasible. This is addressed by randomly generating both the control inputs and the additive disturbances. Bounds on sample sizes are provided which guarantee a notion of a probable near minimum. Model uncertainty is also incorporated into the framework and relevant bounds are provided which guarantee a probable near minimax value. This work finds many applications in miniature devices and miniature robotics. In the final part of this dissertation, we consider a centralized intrusion detection problem with jointly optimal sensor placement. A team of sensors make measurements regarding the presence of an intruder and report their observations to a decision maker. The decision maker solves a jointly optimal detection and sensor placement problem. For the case when the number of sensors is equal to the number of placement points, we prove that uniform placement of sensors is not strictly optimal. We introduce and utilize a majorization based partial order for the placement of sensors. For the case when the number of sensors is less than or equal to six, we show that for a fixed local probability of detection (probability of false alarm) increasing the probability of false alarm (probability of detection) results in optimal placements that are higher on a majorization based partial order.