Yu-Chi Ho. / "January 17, 1955." "This report is based on a thesis submitted to the Department of Electrical Engineering, M.I.T., ... for the degree of Master of Science." / Bibliography: p. 33. / Army Signal Corps Contract DA36-039 sc-42607 Project 132B Dept. of the Army Project 3-99-12-022

Thesis (M.S.)--Brigham Young University. Dept. of Physics and Astronomy, 2006. / Includes bibliographical references (p. 67-69).

Real-time systems comprise computers that must generate correct results in a timely manner. This involves a wide spectrum of computing systems found in our everyday life ranging from computers in rockets to our mobile phones. The criticality of producing timely results defines the different types of realtime systems. On one hand, we have the so-called hard real-time systems, where failing to meet deadlines may result in a catastrophe. In this thesis we are, however, concerned with firm and soft real-time systems, where missing deadlines is acceptable at the expense of degraded system performance. The usage of firm and soft real-time systems has increased rapidly during the last years, mainly due to the advent of applications in multimedia, telecommunication, and e-commerce. These systems are typically data-intensive, with the data normally spanning from low-level control data, typically acquired from sensors, to high-level management and business data. In contrast to hard real-time systems, the environments in which firm and soft real-time systems operate in are typically open and highly unpredictable. For example, the workload applied on a web server or base station in telecommunication systems varies according to the needs of the users, which is hard to foresee. In this thesis we are concerned with quality of service (QoS) management of data services for firm and soft real-time systems. The approaches and solutions presented aim at providing a general understanding of how the QoS can be guaranteed according to a given specification, even if the workload varies unpredictably. The QoS specification determines the desired QoS during normal system operation, and the worst-case system performance and convergence rate toward the desired setting in the face of transient overloads. Feedback control theory is used to control QoS since little is known about the workload applied on the system. Using feedback control the difference between the measured QoS and the desired QoS is formed and fed into a controller, which computes a change to the operation of the real-time system. Experimental evaluation shows that using feedback control is highly effective in managing QoS such that a given QoS specification is satisfied. This is a key step toward automatic management of intricate systems providing real-time data services.

Force control is introduced to robots to solve the problem in machining applications due to the fact that the robot compliance might cause deviation between actual and desired robot path. Also large tolerances in the casting process as well as positioning errors from the clamping create deviations for which the force control technology can adept. Force control has also shown successful in automatic learning of paths along non linear surfaces. This study investigates the possibility of introducing robots equipped with force control at Volvo Aero Corporation in order to robotize polishing and deburring processes. These are today performed by manual labor. This study investigates more specifically the ABB Force Control machining application package. The polishing process has shown to be very complex and today’s version of the ABB force control package cannot give sufficiently robust results to be recommended for implementation. The major issue is the non-existing compliance of tool orientation needed to adapt to casting and positioning deviations due to varying work piece dimensions. The deburring process has however shown to be easier to handle, and a robot cell and methodology is proposed in this report.

This research focuses on developing comprehensive frameworks for developing robust parameter design methodology for dynamic systems with automatic control and for synthesis of nanostructures. In many automatically controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and vice versa and therefore an integrated approach is necessary. A parameter design methodology in the presence of feedback control is developed for processes of long duration under the assumption that experimental noise factors are uncorrelated over time. Systems that follow a pure-gain dynamic model are considered and the best proportional-integral and minimum mean squared error control strategies are developed by using robust parameter design. The proposed method is illustrated using a simulated example and a case study in a urea packing plant. This idea is also extended to cases with on-line noise factors. The possibility of integrating feedforward control with a minimum mean squared error feedback control scheme is explored. To meet the needs of large scale synthesis of nanostructures, it is critical to systematically find experimental conditions under which the desired nanostructures are synthesized reproducibly, at large quantity and with controlled morphology. The first part of the research in this area focuses on modeling and optimization of existing experimental data. Through a rigorous statistical analysis of experimental data, models linking the probabilities of obtaining specific morphologies to the process variables are developed. A new iterative algorithm for fitting a Multinomial GLM is proposed and used. The optimum process conditions, which maximize the above probabilities and make the synthesis process less sensitive to variations of process variables around set values, are derived from the fitted models using Monte-Carlo simulations. The second part of the research deals with development of an experimental design methodology, tailor-made to address the unique phenomena associated with nanostructure synthesis. A sequential space filling design called Sequential Minimum Energy Design (SMED) for exploring best process conditions for synthesis of nanowires. The SMED is a novel approach to generate sequential designs that are model independent, can quickly "carve out" regions with no observable nanostructure morphology, and allow for the exploration of complex response surfaces.

The Bolza-form of the finite-time constrained optimal control problem leads to the Hamilton-Jacobi-Bellman (HJB) equation with terminal boundary conditions and tobe- determined parameters. In general, it is a formidable task to obtain analytical and/or numerical solutions to the HJB equation. This dissertation presents two novel polynomial expansion methodologies for solving optimal feedback control problems for a class of polynomial nonlinear dynamical systems with terminal constraints. The first approach uses the concept of higher-order series expansion methods. Specifically, the Series Solution Method (SSM) utilizes a polynomial series expansion of the cost-to-go function with time-dependent coefficient gains that operate on the state variables and constraint Lagrange multipliers. A significant accomplishment of the dissertation is that the new approach allows for a systematic procedure to generate optimal feedback control laws that exactly satisfy various types of nonlinear terminal constraints. The second approach, based on modified Galerkin techniques for the solution of terminally constrained optimal control problems, is also developed in this dissertation. Depending on the time-interval, nonlinearity of the system, and the terminal constraints, the accuracy and the domain of convergence of the algorithm can be related to the order of truncation of the functional form of the optimal cost function. In order to limit the order of the expansion and still retain improved midcourse performance, a waypoint scheme is developed. The waypoint scheme has the dual advantages of reducing computational efforts and gain-storage requirements. This is especially true for autonomous systems. To illustrate the theoretical developments, several aerospace application-oriented examples are presented, including a minimum-fuel orbit transfer problem. Finally, the series solution method is applied to the solution of a class of partial differential equations that arise in robust control and differential games. Generally, these problems lead to the Hamilton-Jacobi-Isaacs (HJI) equation. A method is presented that allows this partial differential equation to be solved using the structured series solution approach. A detailed investigation, with several numerical examples, is presented on the Nash and Pareto-optimal nonlinear feedback solutions with a general terminal payoff. Other significant applications are also discussed for one-dimensional problems with control inequality constraints and parametric optimization.

Thesis (M. Ed.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 27-31).

Thesis (M.S.)--Brigham Young University. Dept. of Mechanical Engineering, 2008. / Includes bibliographical references (p. 217-226).

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published_or_final_version / Mathematics / Master / Master of Philosophy