This dissertation presents new fuzzy logic techniques for designing control systems for a wide class of complex systems. The methods are developed in detail for a crane system which contains one rigid-body and one oscillation mode. The crane problem is to transfer the rigid body a given distance such that the pendulation of the oscillation mode is regulated at the final time using a single control input. The investigations include in-depth studies of the time-optimal crane control problem as an integral part of the work. The main contributions of this study are: (1) Development of rule-based systems (both fuzzy and crisp) for the design of optimal controllers. This development involves control variable parametrization, rule derivation with parameter perturbation methods, and the design of rule based controllers, which can be combined with model-based feedback control methods. (2) A thorough investigation and analysis of the solutions for time-optimal control problems of oscillation mode systems, with particular emphasis on the use of phase-plane interpretation. (3) Development of fuzzy logic control system methodology using expert rules obtained through energy reducing considerations. In addition, dual mode control is a "spin-off" design method which, although no longer time optimal, can be viewed as a near-optimal control method which may be easier to implement. In both types of design optimization of the fuzzy logic controller can be used to improve performance. / Ph. D.

Approved for public release; distribution in unlimited. / Spray cooling is a promising means of dissipating large steady state heat fluxes in high density power and electronic systems, such as thermophotovoltaic systems. The present study reports on the effectiveness of spray cooling in removing heat fluxes as high as 220 W/cm2. An experiment was designed to determine how the parameters of spray volumetric flow rate and droplet size influence the heat removal capacity of such a system. A series of commercially available nozzles were used to generate full cone water spray patterns encompassing a range of volumetric flow rates (3.79 to 42.32 L/h) and droplet Sauter mean diameters (17.4 to 35.5 micrometers). The non-flooded regime of spray cooling was studied, in which liquid spreading on the heater surface following droplet impact is the key phenomenon that determines the heat transfer rate. The experimental data established a direct proportionality of the heat flux with spray flow rate, and an inverse dependence on the droplet diameter. A correlation of the data was developed to predict heat flux as a function of the studied parameters over the range of values tested in this. / Lieutenant, United States Navy

Time-optimal solutions provide us with the fastest means to regulate a system in presence of input constraints. This advantage of time-optimal control solutions is offset by the fact that their real-time implementation involves computationally intensive iterative techniques. Moreover, time-optimal controls depend on the initial state and have to be recalculated for even the slightest perturbation. Clearly time-optimal controls are not good candidates for online regulation. Consequently, the search for alternatives to time-optimal solutions is a very active area of research. The work described here is inspired by the simplicity of optimal-aim concept. The "optimal-aim strategies" provide online regulation in presence of bounded inputs with minimal computational effort. These are based purely on state-space geometry of the plant and are inherently adaptive in nature. Optimal-aim techniques involve aiming of trajectory derivative (or the state velocity vector) so as to approach the equilibrium state in the best possible manner. This thesis documents the efforts to develop an online regulation algorithm for systems with input constraints. Through a number of hypotheses focussed on trying to reproduce the exact time-optimal solution, the diffculty associated with this task is demonstrated. A modification of optimal-aim concept is employed to develop a novel regulation algorithm. In this algorithm, aim directions are chosen in a special manner to generate the time-optimal control approximately. The control scheme thus developed is shown to be globally stabilizing for systems having eigenvalues in the CLHP (closed left half-plane). It is expected that this method or its modifications can be extended to higher dimensional systems as a part of future research. An alternative control algorithm involving a simple state-space aiming concept is also developed and discussed.

Time-optimal solutions provide us with the fastest means to regulate a system in presence of input constraints. This advantage of time-optimal control solutions is offset by the fact that their real-time implementation involves computationally intensive iterative techniques. Moreover, time-optimal controls depend on the initial state and have to be recalculated for even the slightest perturbation. Clearly time-optimal controls are not good candidates for online regulation. Consequently, the search for alternatives to time-optimal solutions is a very active area of research. The work described here is inspired by the simplicity of optimal-aim concept. The "optimal-aim strategies" provide online regulation in presence of bounded inputs with minimal computational effort. These are based purely on state-space geometry of the plant and are inherently adaptive in nature. Optimal-aim techniques involve aiming of trajectory derivative (or the state velocity vector) so as to approach the equilibrium state in the best possible manner. This thesis documents the efforts to develop an online regulation algorithm for systems with input constraints. Through a number of hypotheses focussed on trying to reproduce the exact time-optimal solution, the diffculty associated with this task is demonstrated. A modification of optimal-aim concept is employed to develop a novel regulation algorithm. In this algorithm, aim directions are chosen in a special manner to generate the time-optimal control approximately. The control scheme thus developed is shown to be globally stabilizing for systems having eigenvalues in the CLHP (closed left half-plane). It is expected that this method or its modifications can be extended to higher dimensional systems as a part of future research. An alternative control algorithm involving a simple state-space aiming concept is also developed and discussed.

In this thesis we develop methods that facilitate an aerial rendezvous between two air vehicles. The objective of this research is to produce a method that can be used to insert a miniature air vehicle behind a rendezvous vehicle and then track that vehicle to enable a visual rendezvous. For this research we assume the rendezvous vehicle is following a relatively stable and roughly elliptical orbit. Path planners and controllers have been developed that can be used to effectively intercept the rendezvous vehicle by inserting the MAV onto the orbit of interest. A method for planning and following time-optimal Dubins airplane interception paths between a miniature air vehicle and the rendezvous vehicle is presented. We demonstrate how a vector field path following a scheme can be used for navigation along these time-optimal Dubins airplane paths. A post-orbit insertion tracking method is also presented which can be used to track the target vehicle on an arbitrarily oriented elliptical orbit while maintaining a specified following distance. We also present controllers that can be used for disturbance rejection during the orbit-insertion and interception operations. All of these methods were implemented in simulation and with hardware. Results from these implementations are presented and analyzed.

Aerobiological sampling using unmanned aerial vehicles (UAVs) is an exciting research field blending various scientific and engineering disciplines. The biological data collected using UAVs helps to better understand the atmospheric transport of microorganisms. Autopilot-equipped UAVs can accurately sample along pre-defined flight plans and precisely regulated altitudes. They can provide even greater utility when they are networked together in coordinated sampling missions: such measurements can yield further information about the aerial transport process. In this work flight vehicle path planning, control and coordination strategies are considered for unmanned autonomous aerial vehicles. A time-optimal path planning algorithm, that is simple enough to be solved in real time, is derived based on geometric concepts. The method yields closed-form solution for an important subset of candidate extremal paths; the rest of the paths are found using a simple numerical root-finding algorithm. A multi-UAV coordination framework is applied to a specific control-volume sampling problem that supports aerobiological data-collection efforts conducted in the lower atmosphere. The work is part of a larger effort that focuses on the validation of atmospheric dispersion models developed to predict the spread of plant diseases in the lower atmosphere. The developed concepts and methods are demonstrated by field experiments focusing on the spread of the plant pathogen <i>Phytophthora infestans</i>. / Ph. D.

Various unmanned missions deploy vehicles such as missiles, torpedoes, ground robots, and unmanned aerial vehicles. Guidance strategies for these vehicles aim to intercept a target point and satisfy additional objectives such as specifications on impact angle and interception time. Certain impact angles are crucial for a greater warhead effectiveness, and minimizing the interception time is important for vehicles with limited endurance time and for reducing the probability of detection. This thesis considers the time-optimal impact angle constrained guidance problem for interception of moving targets. In the first part of the thesis, a Dubins paths–based guidance methodology for minimum-time lateral interception of a moving and non-maneuvering target is designed. The existence and the time-optimality of the paths are established for impact angle constrained interception of moving targets. The capture regions are analyzed and a classification of the initial geometries is developed for deducing the time-optimal path type. The corresponding guidance command for optimal interception can be generated from the information of initial engagement geometry and target’s speed. In the next part of the thesis, the concept of equivalent virtual target is introduced to address the problem of impact along a general direction. An algorithm is developed to obtain the optimal interception point for generalized interception scenarios. A proof of convergence is presented for the proposed algorithm. Achieving different impact angles, the interceptor often takes sharp turns. Following such curved trajectories, the interceptor may fail to keep the target inside the seeker field-of-view. In the next part of the thesis, the field-of-view characteristics of the proposed optimal guidance strategies are analyzed. Closed-form expressions are derived for the interceptor’s look-angle to the target. Satisfying field-of-view condition at endpoints of the path segments that constitute the optimal path is proven to guarantee target motion inside the field-of-view throughout the engagement. The stationary target case is also analyzed as a specific scenario. The last part of the thesis presents a method to extend the proposed guidance strategies to maneuvering target scenarios.

In this paper we examine the stabilization of LTI discrete-time systems with control input constraints in the form of saturation nonlinearities. This kind of constraint is usually introduced to simulate the effect of actuator limitations. Since global controllability can not be assumed in the presence of constrained control, the controllable regions and their characterizations are analyzed first. We present an efficient algorithm for finding controllable regions in terms of their boundary hyperplanes (inequality constraints). A previously open question about the exact number of irredundant boundary hyperplanes is also resolved here. The main result of this research is a time-optimal nonlinear controller which stabilizes the system on its controllable region. We give analgorithm for on-line computation of control which is also implementable for high-order systems. Simulation results show superior response even in the presence of disturbances.

In this paper we examine the stabilization of LTI discrete-time systems with control input constraints in the form of saturation nonlinearities. This kind of constraint is usually introduced to simulate the effect of actuator limitations. Since global controllability can not be assumed in the presence of constrained control, the controllable regions and their characterizations are analyzed first. We present an efficient algorithm for finding controllable regions in terms of their boundary hyperplanes (inequality constraints). A previously open question about the exact number of irredundant boundary hyperplanes is also resolved here. The main result of this research is a time-optimal nonlinear controller which stabilizes the system on its controllable region. We give analgorithm for on-line computation of control which is also implementable for high-order systems. Simulation results show superior response even in the presence of disturbances.

La thèse traite de la planification des mouvements optimaux dans les systèmes robotiques redondants pour l'automatisation des processus d’enroulement filamentaire. L'objectif principal est d'améliorer la productivité des cellules de travail en développant une nouvelle méthodologie d'optimisation des mouvements coordonnés du robot manipulateur, du positionneur de pièce et de l'unité d'extension de l'espace de travail. Contrairement aux travaux précédents, la méthodologie proposée offre une grande efficacité de calcul et tient compte à la fois des contraintes technologiques et des contraintes du système robotique, qui décrivent les capacités des actionneurs et s'expriment par les vitesses et accélérations maximales admissibles dans les articulations actionnées. La technique développée est basée sur la conversion du problème continu original en un problème combinatoire, où toutes les configurations possibles des composants mécaniques sont représentées sous la forme d'un graphe multicouche dirigé et le mouvement temporel optimal est généré en utilisant le principe de programmation dynamique. Ce mouvement optimal correspond au plus court chemin sur le graphique satisfaisant les contraintes de lissage. Les avantages de la méthodologie développée sont confirmés par une application industrielle d’enroulement filamentaire pour la fabrication de pièces thermoplastiques au CETIM. / The thesis deals with the optimal motion planning in redundant robotic systems for automation of the composite lay-up processes. The primary goalis to improve the lay-up workcell productivity by developing a novel methodology of optimizing coordinated motions of the robotic manipulator,workpiece positioner and workspace extension unit,which ensure the shortest processing time and smooth movements of all mechanical components. In contrast to the previous works, the proposed methodology provides high computational efficiencyand also takes into account both the technological constraints and the robotic system constraints, which describe capacities of the actuators and are expressed by the maximum allowable velocities and accelerations in the actuated joints. The developed technique is based on conversion of the original continuous problem into a combinatorial one, where all possible configurations of the mechanical components are represented as a directed multi layergraph and the desired time-optimal motion is generated using dynamic programming principle for searching the shortest path on the graph satisfying the smoothness constraints. It is also proposed an enhancement of this technique by dividing the optimization procedure in two stages combining global and local searches. At the first stage, the developed algorithm is applied in the global search space generated with large discretization step. Then,the same technique is applied in the local search space, which is created with smaller step in the neighborhood of the obtained trajectory. The advantages of the developed methodology are confirmed by industrial implementation on the factory floor that deals with manufacturing of the high pressure vessel.