This dissertation is concerned with the development of two adaptive state estimators that are capable of tracking linear plants that undergo rapid configuration changes. The first is a modification of the Partitioned Adaptive Estimator, PAE, first introduced by Magill in 1965, improved and named by Lainiotis, and used in a number of applications, primarily aerospace. The PAE algorithm was derived for the problem of identifying which, of N, configurations that a linear plant is in; the key assumption being that the configuration is unknown but unchanging. There are two main difficulties in extending the PAE algorithm to the problem of estimating the state of a linear plant that can undergo configuration changes (the switched-linear plant problem). These two difficulties are addressed and solved in this dissertation. The result is called the modified PAE algorithm. The second adaptive estimator developed in this dissertation is the "Sliding Window Detector/Estimator” or SWDE algorithm. Unlike the modified PAE algorithm whose basic structure is designed to solve a different problem, the SWDE algorithm is designed specifically for the switched-linear plant problem. It uses a joint detection/estimation approach to give a very close approximation to the unrealizable optimum switched-linear estimator. The advantages and disadvantages of the two adaptive estimators are discussed, and it is found that a very reliable and accurate estimator can be constructed by combining both algorithms. Several different examples are given to clarify the operation of the estimator. A second contribution of this dissertation is in the application of the above estimators to the nonlinear estimation problem. The motivation for this approach is that a nonlinear plant can be approximated by a sequence of linear approximations, or configurations. Thus, an estimator that works for a switched-linear plant can perform as a sub-optimum nonlinear estimator. In addition, a stochastic nonlinear controller can be constructed using the nonlinear estimator as the observer. This approach has several significant implementation and design advantages which are discussed in the dissertation and illustrated by two examples, a set-point control example and a trajectory-following aircraft example. The above examples and algorithms were fully verified by extensive computer simulation. The implementation advantages afforded by these methods make them practical in a wide variety of applications. / Ph. D.

During the past decade, researchers have shown much interest in control and identification of Large Space Structures (LSS). Our inability to model these LSS accurately has generated extensive research into robust controllers capable of maintaining stability in the presence of large structural uncertainties as well as changing structural characteristics. In this work the performance of Model Reference Adaptive Control - (MRAC) is studied in numerical simulations and verified experimentally, to understand how differences between the plant and the reference model affect the control effort. MRAC is applied analytically and experimentally to a single-degree-of-freedom system and analytically to a multi-degree-of-freedom system with multi-inputs and multi-outputs. Good experimental and analytical agreement is demonstrated in control experiments and it is shown that MRAC does an excellent job of controlling the structures and achieving the desired performance even when large differences between the plant and ideal reference model exist. However, it is shown that reasonable differences between the reference model and the plant significantly increase the required control effort. The effects of increased damping in the reference model are considered, and it is shown that requiring the controller to provide increased damping actually decreases the required control effort when differences between the plant and reference model exist. This result is very useful because one of the first attempts to counteract the increased control effort due to differences between the plant and reference model might be to require less damping, however, this would actually increase the control effort. The use of optimization to successfully improve performance and reduce control effort is shown to be limited, because the actual control-structure system can not realize all the performance improvements of the analytical optimal system. Finally, it is shown that very large sampling rates may be required to accurately implement MRAC. / Ph. D.

The method of Pseudo-Linear Identification (PLID) is presented as an explicitly linear approach to the joint state and parameter estimation problem. The convergence properties of the algorithm in the stochastic case are investigated through simulation and comparisons with popular methods are made. The method is then extended to allow the tracking of time-varying system parameters. An adaptive control structure based upon this Tracking–PLID algorithm is proposed which utilizes pole–placement state variable feedback via Ackermann's formula. The capabilities of this adaptive control scheme are demonstrated by application to a full-order nonlinear aircraft simulation model where significant improvement is shown over fixed-gain controllers in the face of rapid plant changes. / Master of Science

This paper presents a theoretical development of adaptive cruise control models and platoon operation logic for Automated Highway Systems in the Advanced Vehicle Control Systems (AVeS). Three control modes, constant speed, emergency and vehicle-following, are defined based on the minimum safe stopping distance, and applied to the platoon operations. Desired acceleration model is built for the different cruise control mode by considering the relative velocity, the difference between the relative distance and desired spacing, and the acceleration of the preceding vehicle. A control system model is proposed based on the analysis of vehicle dynamics. The contribution of uncontrolled forces from the air, slop and friction to the vehicle acceleration is considered. Application of control models for two successive vehicles is simulated under the situations of speed transition and emergency stopping. Proper control parameters are determined for different operation mode subject to the conditions: collision avoidance and stability. Same criteria are utilized to the platoon simulation in which the operation logic is regulated so that the platoon leader is operated under either emergency mode or constant speed mode depending upon the . distance from the downstream vehicle, while the intraplatoon vehicles are forced to operate under vehicle-following mode. Three cases under speed transition, emergency stopping and platoon leader splitting are simulated to determine the stable control parameters. Lane capacity analysis shows the tradeoff between safety and efficiency for platoon. modal operations on freeway with guideline or automated highway. / Master of Science

This study investigates an adaptive control scheme designed to maintain accurate motor speed control in spite of high-frequency periodic variations in load torque, load inertia, and motor parameters. The controller adapts, stores and replays a schedule of torques to be delivered at discrete points throughout the periodic load cycle. The controller also adapts to non-periodic changes in load conditions which occur over several load cycles and contains inherent integrator control action to drive speed error to zero. Using computer simulations, the control method was successfully applied to a 3Φ synchronous motor and a permanent magnet D.C. motor. The D.C. motor (or A.C. servo-motor) controller has superior characteristics and this system performance was compared to P, PI and PID control for two severe load cases - a periodic step load and a four-bar linkage load. Simulation studies showed the schedule control method to be stable and in comparison to the PID controller to have 1) nearly the same speed of response but without the overshoot found in PID control, 2) nearly the same mean speed error (~ O), 3) 12-50 times better reduction in speed fluctuation, and 4) the schedule controller gains were much easier to find than PID gains for this low-order, highly responsive system. / Master of Science

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M.Ing. (Electrical and Electronic Engineering) / Adaptive Cruise Control (ACC) is proposed to assist drivers tedious manual acceleration or braking of the vehicle, as well as with maintaining a safe headway time gap. This thesis proposes, simulates, and implements a vision-based ACC system which uses a single camera to obtain the clearance distance between the preceding vehicle and the ACC vehicle. A three-step vehicle detection framework is used to obtain the position of the lead vehicle in the image. The vehicle coordinates are used in conjunction with the lane width at that point to estimate the longitudinal clearance range. A Kalman filter filters this range signal and tracks the vehicle’s longitudinal position. Since image processing algorithms are computationally intensive, this document addresses how adaptive image cropping improves the update frequency of the vision-based range sensor. A basic model of a vehicle is then derived for which a Proportional-Integral (PI) controller with gain scheduling is used for ACC. A simulation of the system determines whether the ACC algorithm will work on an actual vehicle.

This report describes the development of a low cost open source semiautonomous robotic car and a way to communicate with it. It is a continuation of prior research done by other students at FAU and published in recent ASEE conferences. The objective of this project was the development of a new robotic platform with improved precision over the original, while still keeping the cost down. It was developed with the aim to allow a hands-on approach to the teaching of mathematics topics that are taught in the K-12 syllabus. Improved robustness and reliability of the robotic platform for visually solving math problems was achieved using a combination of PID loops to keep track of distance and rotation. The precision was increased by changing the position of the encoders to the shafts of each motor. A mobile application was developed to allow the student to draw the geometric shapes on the screen before the car draws them. The mobile application consists of two parts, the canvas that the user uses to draw the figure and the configure section that lets the user change the parameters of the controller. Results show that the robot can draw standard geometric and complex geometric shapes. It has high precision and sufficient accuracy, the accuracy can be improved with some mechanical adjustments. During testing a Pythagorean triangle was drawn to show visually the key mathematics concept. The eventual goal of this project will be a K-12 class room study to obtain the feedback of the teachers and students on the feasibility of using a robotic car to teach math. Subsequent to that necessary changes will be made to manufacture a unit that is easy to assemble by the teacher. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

As humans explore greater depths of Earth’s oceans, there is a growing need for the installation of subsea structures. 71% of the earth’s surface is ocean but there are limitations inherent in current detection instruments for marine applications leading to the need for the development of underwater platforms that allow research of deeper subsea areas. Several underwater platforms including Autonomous Underwater Vehicles (AUVs), Remote Operated Vehicles (ROVs), and wave gliders enable more efficient deployment of marine structures. Deployable structures are able to be compacted and transported via AUV to their destination then morph into their final form upon arrival. They are a lightweight, compact solution. The wrapped package includes the deployable structure, underwater pump, and other necessary instruments, and the entire package is able to meet the payload capability requirements. Upon inflation, these structures can morph into final shapes that are a hundred times larger than their original volume, which extends the detection range and also provides long-term observation capabilities. This dissertation reviews underwater platforms, underwater acoustics, imaging sensors, and inflatable structure applications then proposes potential applications for the inflatable structures. Based on the proposed applications, a conceptual design of an underwater tubular structure is developed and initial prototypes are built for the study of the mechanics of inflatable tubes. Numerical approaches for the inflation process and bending loading are developed to predict the inflatable tubular behavior during the structure’s morphing process and under different loading conditions. The material properties are defined based on tensile tests. The numerical results are compared with and verified by experimental data. The methods used in this research provide a solution for underwater inflatable structure design and analysis. Several ocean morphing structures are proposed based on the inflatable tube analysis. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection