This thesis describes discrete robust adaptive control methods based on using slow sampling and slow adaptation. For the stability analysis, we consider that the plant model order is not exactly known and assume that the estimation model order is lower than the plant model order. A stability condition is derived with a given upper limit for the adaptation gain which is related to a strictly positive real operator. Discussion of the relation between sampling and stability condition is then given. For the robust adaptive control design, we study slow adaptation and predictive control. For the slow adaptation, the main idea is to use only good estimates and use a compensation filter. Some frequency domain information on the plant is necessary for this method. For predictive control, we discuss the relationship between the extended control horizon and the critical sampling. For a simple case, it is shown that the larger extended control horizon brings more robust adaptive control. The purpose of this thesis is to provide robust discrete adaptive controller design guidelines, especially in such cases as using slow sampling frequency, slow adaptation rate. It is true that in practice, for various discrete adaptive control algorithms, slow sampling and slow adaptation rate will bring more robustness. The use of slow sampling and slow adaptation rate is simple and economic, thus a careful choice of sampling rate and adaptation rate is highly recommended. This thesis provides such guidelines for choosing proper sampling rate and adaptation rate for robust discrete adaptive control. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

This thesis discusses the use of genetic algorithms as a global search technique to solve three optimization problems: a sixth-order polynomial problem, a single-degree-of-freedom spring-mass-damper (SDOF SMD) system problem, and a loading bridge regulator problem. Genetic algorithms are iterative global search techniques based on the principles of natural selection and population genetics. The theory, design and implementation of the algorithm is discussed in detail. The Simple Genetic Algorithm (SGA) is presented to solve a sixth-order polynomial optimization problem. Results from two traditional numerical techniques will be compared with the SGA results as well as the analytical calculus solution. In addition, the effect of different parametric sizes of the genetic operators are investigated. In the second problem, genetic algorithms are used to design a two-state feedback optimal gain set for a SDOF SMD model with a given initial condition. An improved selection scheme called the stochastic remainder selection without replacement is introduced. An improved GA-based (IGA) feedback controller is designed to control the system. Lastly, a regulator control problem is presented using advanced genetic algorithms (AGA). Two-point crossover and inversion operators are employed. A loading bridge is chosen as the control model. An advanced GA-based full-state feedback controller is designed to control the loading bridge with the given reference input voltage. The conclusions show that SGA is more robust than traditional numerical techniques to solve multi-modal functions. Among the three GA approaches considered, AGA is the most robust one for the design of adaptive feedback controllers. / Master of Science

Precise machining of bearing rings is integral to finished bearing assembly quality. The output accuracy of center-based machining systems such as lathes or magnetic chuck grinders relates directly to the accuracy of part centering before machining. Traditional tooling and methods for centering on such machines are subject to wear, dimensional inaccuracy, setup time (hard tooling) and human error (manual centering).A flexible system for initial part centering is developed based on a single measurement system and actuator, whereby the part is placed by hand onto the machine table, rotated and measured to identify center of geometry offset from center of rotation, then moved by a series of controlled impacts or pushes to align the centers. The prototype centering system is developed as a demonstration platform for research in a number of mechanical engineering areas, particularly: Characterization of optimal state estimators through analysis of accuracy and computational efficiency; Distributed communication and control, efficient transfer of information in a real-time environment, and information sharing between processes; Modeling of sliding dynamics and the interaction of friction with compliant body dynamic models; Motion path planning through both deterministic geometric transforms and through frequency domain command manipulation.A vision is created for future work not only in the described areas, but also in the areas of advanced controller design incorporating multiple variables, derived machine diagnostic information, and application of the distributed communication architecture to information flow throughout the manufacturing organization. The guiding motivation for this research is reduction of manufacturing processing costs in the face of global competition. The technologies researched, developments made, and directions prescribed for future research aid in enabling this goal.

This thesis presents the design of various controllers for a highly maneuverable, high performance aircraft, namely the modified F-18. The aircraft was required to perform high angle-of-attack maneuvers, for which the aircraft behaves in as a highly nonlinear system. An adaptive PID controller was used to control the aircraft through these high angle-of-attack maneuvers. Several nonlinear controllers were then developed based on the adaptive PID control, and were tested for robustness. This thesis also looks at an improvement in the aircraft which may improve performance in high angle-of-attack maneuvers. The contributions of this thesis are in the areas of control, in general, and specifically in the area of aircraft control. Successful application of linear adaptive control and nonlinear control were presented. In the area of aircraft control, controllers were presented which produce good performance for high angle-of-attack maneuvers, while maintaining implementability. Also, some insight is gained into what aircraft changes could improve performance. / Graduation date: 1995

Future wireless networks will be required to support multimedia traffic in addition to traditional best-effort network services. Supporting multimedia traffic on wired networks presents a large number of design problems, particularly for networks that run connectionless data transport protocols such as the TCP/IP protocol suite. These problems are magnified for wireless links, as the quality of such links varies widely and uncontrollably. This dissertation presents new tools developed for the design and realization of wireless networks including, for the first time, analytical channel models for predicting the efficacy of error control codes, interleaving schemes, and signalling protocols, and several novel algorithms for matching and adapting system parameters (such as error control and frame length) to time-varying channels and Quality of Service (QoS) requirements.