Thesis supervisor: John D. Lee. Includes bibliographic references (p. 188-200).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1970. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1970. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--Mechanical Engineering, Georgia Institute of Technology, 2006. / Dr. Richard F. Salant, Committee Member ; Dr. Shreyes N. Melkote, Committee Member ; Dr. Francis M. Kolarits, Committee Member ; Dr. Jane C. Ammons, Committee Member ; Dr. Thomas R. Kurfess, Committee Chair.

Thesis (Ph. D.)--Ohio State University, 2005. / Title from first page of PDF file. Includes bibliographical references (p. 175-180).

The ball and beam system is a very simple and powerful control system problem. The easy construction of this system combined with its challenging control design requirement makes it one of the most favorable example models for control engineers. The model contains a horizontal beam which can pivot about its center; a DC Motor whose shaft is connected to the center of the beam; and a ball that can freely roll on top of the beam. The basic idea is to accurately tilt the beam about its center, using the motor, to indirectly control the position of the ball that freely rolls on the beam. In this thesis, the L1 adaptive control technique is considered for precise positioning of the rolling ball on the beam. Two different architectures of L1 adaptive control namely, the L1 adaptive state feedback control and the L1 adaptive output feedback control are designed and verified in simulation. L1 adaptive control guarantees transient performance and robustness in presence of fast adaptation without introducing or enforcing persistence of excitation.

No description available.

This thesis describes a novel approach to model and estimate systems of unknown delay. The a-priori knowledge available about the systems is fully utilized so that the number of parameters to be estimated equals the number of unknowns in the systems. Existing methods represent the single unknown system delay by a large number of unknown parameters in the system model. The purpose of this thesis is to develop new methods of modelling the systems so that the unknowns are directly estimated. The Variable Regression Estimation technique is developed to provide direct delay estimation. The delay estimation requires minimum excitation and is robust, bounded, and it converges to the true value for first-order and second-order systems. The delay estimation provides a good model approximation for high-order systems and the model is always stable and matches the frequency response of the system at any given frequency. The new delay estimation method is coupled with the Pole Placement, Dahlin and the Generalized Predictive Controller (GPC) design and adaptive versions of these controllers result. The new adaptive GPC has the same closed-loop performance for different values of system delay. This was not achievable in the original adaptive GPC. The adaptive controllers with direct delay estimation can regulate systems with dominant time delay with minimum parameters in the controller and the system model. The delay does not lose identifiability in closed-loop estimation. Experiments on the delay estimation show excellent agreement with the theoretical analysis of the proposed methods. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Adaptive Cruise Control (ACC) vehicles have a longer reaction time, and the on-board sensors have a limited detection range that adversely affects the freeway bottleneck capacity. These limitations can cause small speed fluctuations into larger stop-and-go waves at typical freeway bottlenecks. Microsimulation results revealed that flow instability increases with the increase in ACC market penetration for a single lane freeway. The ACC car following model was developed for higher speed ranges only; thus, it could not capture rapid deceleration to lower speeds, let alone complete stops. The algorithm applies collision avoidance and brake relatively late in those instances, which leads to vehicles clustered closer together when at complete stops (or lower speeds). Therefore, the jam density increases with ACC market penetration. Simulation results also represented that no change in capacity was observed with the introduction of ACC vehicles on a freeway without diverging off-ramp and merging on-ramp demand compared to manually driven vehicles. The result is owed to the fact that lane changes and disturbances are not prominent without merging and diverging sections. However, the situation aggravates more for ACC vehicles when there is diverging off-ramp demand and merging on-ramp demand. The effect becomes severe with the increase of ACC market penetration. The field experiments for the fundamental characteristics of traffic flow showed that maximum capacity can be achieved when all the vehicles are operating in ACC mode. However, that maximum flow is unstable, and a minor speed variation can cause severe capacity drop. The jam density is also more in all ACC scenario that might result in rapid queue propagation as the wave speed is larger compared to the mixed driving scenario. / Includes bibliography. / Thesis (MS)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

Lighter than air (LTA) vehicles have many advantageous capabilities over other aircraft, including low power consumption, high payload capacity, and long endurance. However, they exhibit manoeuvrability and control reliability challenges, and these limitations are particularly significant for smaller unmanned LTA. In this thesis, a 4 m length autonomous airship with a sliding gondola is presented. A rigid keel, mounted to the helium envelope, follows the helium envelope profile from the midsection to the nose of the vehicle. Moving the gondola along the keel produces upwards of 90-degree changes in pitch angle, thereby improving manoeuvrability and allowing for rapid changes in altitude. The longitudinal multi-body equations of motion were developed for this prototype using the Boltzmann–Hamel method. An adaptive PID controller was then designed to control the pitch inclination using the gondola’s position. This control system is capable of self-tuning the controller gains in real time by minimizing a pre-defined sliding condition. Experimental flight tests were carried out to evaluate the controller’s performance on the prototype.