Orientador: Celso Pascoli Bottura / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e Computação / Made available in DSpace on 2018-08-31T09:18:30Z (GMT). No. of bitstreams: 1 Serra_GinalberLuizdeOliveira_D.pdf: 2165582 bytes, checksum: a1dad46bc4d817f8d4e6457f60ae9599 (MD5) Previous issue date: 2005 / Resumo: Esta tese apresenta propostas de metodologias para identificação e controle inteligentes. Uma metodologia para identificação de sistemas dinâmicos não-lineares no tempo discreto, baseada tio método de variável instrumental e no modelo nebuloso Takagi-Sugeno, é apresentada. Nesta metodologia, a qual é uma extensão do método de variável instrumental tradicional, as variáveis instrumentais escolhidas, estatisticamente independentes do ruído, são mapeadas em conjuntos nebulosos, particionando o espaço de entrada em sub-regiões, para estimação não-polarizada dos parâmetros do conseqüente dos modelos nebulosos TS em ambiente ruidoso. Um esquema de controle adaptativo gain scheduling baseado em redes neurais, sistemas nebulosos e algoritmos genéticos para sistemas dinâmicos não-lineares no tempo discreto também é apresentado. 0 controlador nebuloso é desenvolvido e projetado com o usa de um algoritmo genético para satisfazer, simultaneamente, múltiplos objetivos. Com o esquema de aprendizagem supervisionada, os parâmetros do controlador nebuloso são usados para projetar um gain scheduler neural para ajuste on-line do controlador nebuloso em alguns pontos de operação do sistema dinâmico / Abstract: This thesis presents proposals of methodologies for intelligent identification and control. A methodology tor nonlinear dynamic discrete time systems identification, based on the instrumental variable method and Takagi-Sugeno fuzzy model, is presented. In this methodology, which is an extension of the standard instrumental variable method, the chosen instrumental variables, estatistically independent of the noise, are mapped into fuzzy sets, partitioning the input space in subregions, for unbiased estimation of Takagi-Sugeno fuzzy model consequent parameters in a noisy environment. A gain scheduling adaptive control design based on neural network, fuzzy systems and genetic algorithms for nonlinear dynamic discrete time systems is also presented. The fuzzy controller is developed and designed by a genetic algorithm to satisfy, simultaneously, multiple objectives. "With the supervised learning scheme, the fuzzy controller parameters are used to design the gain neural scheduler to tune on-line the fuzzy controller in some operation points of the dynamic system / Doutorado / Automação / Doutor em Engenharia Elétrica

Indiana University-Purdue University Indianapolis (IUPUI) / Multiresolution image fusion is an emerging area of research for use in military and commercial applications. While many methods for image fusion have been developed, improvements can still be made. In many cases, image fusion methods are tailored to specific applications and are limited as a result. In order to make improvements to general image fusion, novel methods have been developed based on the wavelet transform and empirical variance. One particular novelty is the use of directional filtering in conjunction with wavelet transforms. Instead of treating the vertical, horizontal, and diagonal sub-bands of a wavelet transform the same, each sub-band is handled independently by applying custom filter windows. Results of the new methods exhibit better performance across a wide range of images highlighting different situations.

In this thesis, a particular class of agent is singled out for examination. In order to provide a guiding metaphor, we speak of control room agents. Our focus is on rational decision- making by such agents, where the circumstances obtaining are such that rationality is bounded. Control room agents, whether human or non-human, need to reason and act in a changing environment with only limited information available to them. Determining the current state of the environment is a central concern for control room agents if they are to reason and act sensibly. A control room agent cannot plan its actions without having an internal representation (epistemic state) of its environment, and cannot make rational decisions unless this representation, to some level of accuracy, reflects the state of its environment. The focus of this thesis is on three aspects regarding the epistemic functioning of a control room agent: 1. How should the epistemic state of a control room agent be represented in order to facilitate logical analysis? 2. How should a control room agent change its epistemic state upon receiving new information? 3. How should a control room agent combine available information from different sources? In describing the class of control room agents as first-order intentional systems hav- ing both informational and motivational attitudes, an agent-oriented view is adopted. The central construct used in the information-theoretic approach, which is qualitative in nature, is the concept of a templated ordering. Representing the epistemic state of a control room agent by a (special form of) tem- plated ordering signals a departure from the many approaches in which only the beliefs of an agent are represented. Templated orderings allow for the representation of both knowledge and belief. A control room agent changes its epistemic state according to a proposed epistemic change algorithm, which allows the agent to select between two well-established forms of belief change operations, namely, belief revision and belief update. The combination of (possibly conflicting) information from different sources has re- ceived a lot of attention in recent years. Using templated orderings for the semantic representation of information, a new family of purely qualitative merging operations is developed. / School of Computing / Ph. D. (Computer Science)

Carefree handling refers to the ability of a pilot to operate an aircraft without the need to continuously monitor aircraft operating limits. At the heart of all carefree handling or maneuvering systems, also referred to as envelope protection systems, are algorithms and methods for predicting future limit violations. Recently, envelope protection methods that have gained more acceptance, translate limit proximity information to its equivalent in the control channel. Envelope protection algorithms either use very small prediction horizon or are static methods with no capability to adapt to changes in system configurations. Adaptive approaches maximizing prediction horizon such as dynamic trim, are only applicable to steady-state-response critical limit parameters. In this thesis, a new adaptive envelope protection method is developed that is applicable to steady-state and transient response critical limit parameters. The approach is based upon devising the most aggressive optimal control profile to the limit boundary and using it to compute control limits. Pilot-in-the-loop evaluations of the proposed approach are conducted at the Georgia Tech Carefree Maneuver lab for transient longitudinal hub moment limit protection. Carefree maneuvering is the dual of carefree handling in the realm of autonomous Uninhabited Aerial Vehicles (UAVs). Designing a flight control system to fully and effectively utilize the operational flight envelope is very difficult. With the increasing role and demands for extreme maneuverability there is a need for developing envelope protection methods for autonomous UAVs. In this thesis, a full-authority automatic envelope protection method is proposed for limit protection in UAVs. The approach uses adaptive estimate of limit parameter dynamics and finite-time horizon predictions to detect impending limit boundary violations. Limit violations are prevented by treating the limit boundary as an obstacle and by correcting nominal control/command inputs to track a limit parameter safe-response profile near the limit boundary. The method is evaluated using software-in-the-loop and flight evaluations on the Georgia Tech unmanned rotorcraft platform- GTMax. The thesis also develops and evaluates an extension for calculating control margins based on restricting limit parameter response aggressiveness near the limit boundary.

In this thesis, a particular class of agent is singled out for examination. In order to provide a guiding metaphor, we speak of control room agents. Our focus is on rational decision- making by such agents, where the circumstances obtaining are such that rationality is bounded. Control room agents, whether human or non-human, need to reason and act in a changing environment with only limited information available to them. Determining the current state of the environment is a central concern for control room agents if they are to reason and act sensibly. A control room agent cannot plan its actions without having an internal representation (epistemic state) of its environment, and cannot make rational decisions unless this representation, to some level of accuracy, reflects the state of its environment. The focus of this thesis is on three aspects regarding the epistemic functioning of a control room agent: 1. How should the epistemic state of a control room agent be represented in order to facilitate logical analysis? 2. How should a control room agent change its epistemic state upon receiving new information? 3. How should a control room agent combine available information from different sources? In describing the class of control room agents as first-order intentional systems hav- ing both informational and motivational attitudes, an agent-oriented view is adopted. The central construct used in the information-theoretic approach, which is qualitative in nature, is the concept of a templated ordering. Representing the epistemic state of a control room agent by a (special form of) tem- plated ordering signals a departure from the many approaches in which only the beliefs of an agent are represented. Templated orderings allow for the representation of both knowledge and belief. A control room agent changes its epistemic state according to a proposed epistemic change algorithm, which allows the agent to select between two well-established forms of belief change operations, namely, belief revision and belief update. The combination of (possibly conflicting) information from different sources has re- ceived a lot of attention in recent years. Using templated orderings for the semantic representation of information, a new family of purely qualitative merging operations is developed. / School of Computing / Ph. D. (Computer Science)

The field buses, and particularly the ‘PROFIBUS’, are currently widely used in automation systems, with the intention to automate industrial applications. It is of the utmost importance that one should understand how these systems operate, because failure to understand may result in improper applications, which can ultimately lead to intense network problems and, consequently, lead to potential catastrophic failures in industrial equipment, as well as compromising the health and safety of the people. This research was the performance evaluation of SAMANCOR PROFIBUS network that controls the chrome manufacturing plant. The problem with the network was that it was failing intermittently. These network failures resulted in loss of production, loss of throughput, compromised quality, downtime due to reworks, high costs in energy used to rework, and equipment damage or failure. One of the OBJECTIVES of the research was to carry out a performance evaluation of the PROFIBUS network in terms of the possible electromagnetic interference (EMI) within the plant’s PLC network. This topic emanated from the network service providers that kept insisting that the network was unstable, due to possible electromagnetic interference caused by possible high voltage cables running next to the plant network cables. This assumption was without fact, and hence the research was conducted. The QUANTITATIVE research method was used to conduct the research, where simulation of the plant network, using external parameters, were used to carry out the research. Furthermore, experiments were conducted and the physical measurements were performed on the network, where parameters derived from these measurements were used to compare the two networks. In essence, the network was tested under known configurations. The manner in which the network was simulated was that of stepping up the electrical current from the external device, and recording the response of the network. A stand-alone network rig was built and used to carry out the tests, and the results were compared with those obtained from the plant network. / Electrical and Mining Engineering / M. Tech. (Electrical Engineering)

This work presents an intelligent control of position and velocity to a climber robot developed to perform inspections of pressure vessels. The climber robot has steerable and magnetic wheels, which makes it similar to an omnidirectional robot due to its high maneuverability. The intelligent velocity control proposed uses the switching Fuzzy controllers according to the movement to be performed, which allow the use of all the robot's movement potential respecting the constraints imposed by the dynamic model and magnetic adhesion. Also, a position controller was developed in cascade with the speed controller to verify the navigation capability of the robot in a 2D environment. Simulated and experimental tests are applied for validation of control techniques implemented and they're presented at the end of this work. / Este trabalho apresenta um controle inteligente de posição e velocidade para um robô escalador desenvolvido para realizar inspeções em vasos de pressões. O robô escalador possui rodas direcionáveis e magnéticas, o que o torna similar a um robô omnidirecional em virtude da sua alta manobrabilidade. O controle inteligente de velocidade proposto utiliza o chaveamento de controladores Fuzzy de acordo com o movimento a ser realizado, que permitem a utilização de todo o potencial de movimentação do robô respeitando as restrições impostas pelo modelo dinâmico e pela adesão magnética. Também foi projetado um controlador de posição em cascata com o de velocidade para a verificação da capacidade de navegação do robô em um ambiente 2D. Testes simulados e experimentais são aplicados para a validação das técnicas de controle implementadas e são apresentados ao final do trabalho.

Indiana University-Purdue University Indianapolis (IUPUI) / This thesis proposes an automated grid-based alignment system utilizing lasers and an array of light-detecting photodiodes. The intent is to create an inexpensive and scalable alignment system for pick-and-place robotic systems. The system utilizes the transformation matrix, geometry, and trigonometry to determine the movements to align the robot with a grid-based array of photodiodes. The alignment system consists of a sending unit utilizing lasers, a receiving module consisting of photodiodes, a data acquisition unit, a computer-based control system, and the robot being aligned. The control system computes the robot movements needed to position the lasers based on the laser positions detected by the photodiodes. A transformation matrix converts movements from the coordinate system of the grid formed by the photodiodes to the coordinate system of the robot. The photodiode grid can detect a single laser spot and move it to any part of the grid, or it can detect up to four laser spots and use their relative positions to determine rotational misalignment of the robot. Testing the alignment consists of detecting the position of a single laser at individual points in a distinct pattern on the grid array of photodiodes, and running the entire alignment process multiple times starting with different misalignment cases. The first test provides a measure of the position detection accuracy of the system, while the second test demonstrates the alignment accuracy and repeatability of the system. The system detects the position of a single laser or multiple lasers by using a method similar to a center-of-gravity calculation. The intensity of each photodiode is multiplied by the X-position of that photodiode. The summed result from each photodiode intensity and position product is divided by the summed value of all of the photodiode intensities to get the X-position of the laser. The same thing is done with the Y-values to get the Y-position of the laser. Results show that with this method the system can read a single laser position value with a resolution of 0.1mm, and with a maximum X-error of 2.9mm and Y-error of 2.0mm. It takes approximately 1.5 seconds to process the reading. The alignment procedure calculates the initial misalignment between the robot and the grid of photodiodes by moving the robot to two distinct points along the robot’s X-axis so that only one laser is over the grid. Using these two detected points, a movement trajectory is generated to move that laser to the X = 0, Y = 0 position on the grid. In the process, this moves the other three lasers over the grid, allowing the system to detect the positions of four lasers and uses the positions to determine the rotational and translational offset needed to align the lasers to the grid of photodiodes. This step is run in a feedback loop to update the adjustment until it is within a permissible error value. The desired result for the complete alignment is a robot manipulator positioning within ±0.5mm along the X and Y-axes. The system shows a maximum error of 0.2mm in the X-direction and 0.5mm in the Y-direction with a run-time of approximately 4 to 5 minutes per alignment. If the permissible error value of the final alignment is tripled the alignment time goes down to 1 to 1.5 minutes and the maximum error goes up to 1.4mm in both the X and Y-directions. The run time of the alignment decreases because the system runs fewer alignment iterations.

Indiana University-Purdue University Indianapolis (IUPUI) / There is a strong urge for advanced diagnosis method, especially in high power battery packs and high energy density cell design applications, such as electric vehicle (EV) and hybrid electric vehicle segment, due to safety concerns. Accurate and robust diagnosis methods are required in order to optimize battery charge utilization and improve EV range. Battery faults cause significant model parameter variation affecting battery internal states and output. This work is focused on developing diagnosis method to reliably detect various faults inside lithium-ion cell using electrochemical model based observer and fuzzy logic algorithm, which is implementable in real-time. The internal states and outputs from battery plant model were compared against those from the electrochemical model based observer to generate the residuals. These residuals and states were further used in a fuzzy logic based residual evaluation algorithm in order to detect the battery faults. Simulation results show that the proposed methodology is able to detect various fault types including overcharge, over-discharge and aged battery quickly and reliably, thus providing an effective and accurate way of diagnosing li-ion battery faults.