The traveling wave ultrasonic motor is considered for use in haptic devices where a certain input-output relation is desired between the applied force and the resulting motion. Historically, DC motors have been the standard choice for this purpose. Owing to its unique characteristics, the ultrasonic motors have been considered an attractive alternative. However, there are some limitations when using the ultrasonic motor for force-feedback applications. In particular, direct torque control is difficult, and the motor can only supply torque in the direction of motion. To accommodate these limitations we developed an indirect control approach. The experimental results demonstrate that the model reference control method was able to approximate a second order spring-damper system.

Métodos de controle por modelo de referência, usualmente encontrados na literatura de controle baseado em dados, têm como principal característica a especificação do desempenho desejado em malha fechada através de um modelo de referência. Estes métodos são, no entanto, comumente desenvolvidos para tratar o problema de seguimento de referência, em detrimento do comportamento relativo à perturbação de carga. Nesse sentido, recentemente foi desenvolvido o método de controle baseado em dados Virtual Disturbance Feedback Tuning – VDFT, que pode ser interpretado como um método de controle por modelo de referência para perturbação, em que o controlador é sintonizado para alcançar em malha fechada o comportamento regulatório especificado. A escolha no entanto do modelo de referência para perturbação mostra-se desafiadora, especialmente considerando o cenário em que pouca ou nenhuma informação sobre o modelo paramétrico do sistema está disponível. Dessa forma, este trabalho tem como objetivo estudar o impacto da escolha deste modelo sobre a sintonia do controlador utilizando o método VDFT e propor uma abordagem sistemática para lidar com essa variável de projeto. A solução aqui concebida é a de flexibilizar o modelo de referência para perturbação e identificar parte do seu numerador juntamente aos parâmetros do controlador que, associada a um conjunto de diretivas de projeto, permitem aproximar o comportamento em malha fechada do inicialmente especificado. Esse resultado viabiliza a utilização do método VDFT com critério flexível no contexto de uma estrutura hierárquica de controle, em que uma malha externa de controle preditivo é associada à malha de controle por VDFT, evitando a etapa de identificação de um modelo para o processo. Por fim, a formulação do método VDFT, assim como sua adaptação flexível, é estendida a fim de levar em conta processos multivariáveis. Experimentos e resultados em simulação ilustram as contribuições deste trabalho. / Model reference control methods, usually found within data-based control literature, have as main feature the specification of the desired closed-loop performance through a reference model. These methods are however commonly developed to address the set point tracking problem, to the disadvantage of load disturbance rejection. In this sense, the data-based control method Virtual Disturbance Feedback Tuning – VDFT was recently developed, which could be interpreted as a model reference control method for disturbance, in which the controller is tuned in order to reach in closed-loop the specified regulatory behavior. Nonetheless, the choice of the disturbance reference model is challenging, especially considering the scenario where little or no information on the process’ parametric model is available. This work aims therefore to study the impact of the disturbance reference model choice on the controller tuning using the VDFT method and to propose a systematic approach to deal with this design variable. The solution here conceived is to loosen the disturbance reference model and identify part of its numerator along with the controller parameters, which, associated with a set of design directions, allow the closed-loop behavior to be drawn closer to the one initially specified. This result enables the use of the VDFT method with flexible criterion in the context of a hierarchical control structure, in which an external predictive control loop is associated to the VDFT control loop, avoiding thus the identification of a process model. Finally, VDFT method’s formulation, as well as its flexible adaptation, is extended in order to take into account multivariable processes. Experiments and simulation results illustrate the contributions of this work.

A presente tese tem por propósito contribuir para uma política de planejamento no campo da educação a distância (EAD). Para isto concebe uma proposta multi-modelo de referência lastreada na definição de estratégias em espectro de alta complexidade, que considera uma seqüência de procedimentos sistematizados nas seguintes fases: (i) Determinação das necessidades de informação, em duas etapas: (a) identificação dos fatores críticos de sucesso (FCS) e (b) identificação das áreas de informação; (ii) Determinação das competências, em três etapas: (a) determinação dos conhecimentos, (b) determinação das habilidades, e (c) determinação das atitudes; (iii) Determinação dos graus de avaliação de competências; (iv) Determinação das estratégias em redes de conhecimentos. Evidencia-se a aplicação a um estudo de caso nas concessões rodoviárias no Brasil, na perspectiva das parcerias público-privadas (PPPs). A consecução da pesquisa foi por meio da intervenção de especialistas e um grupo pequeno de estudantes de um programa de EAD (MBA) aplicado às PPPs. A coleta de dados foi por meio de um formulário semi-estruturado, do tipo escalar, em uma matriz de julgamento, com a intervenção de especialistas. Vários instrumentos de apoio foram utilizados na elaboração da modelagem, com vistas a reduzir a subjetividade dos resultados alcançados: escalagem psicométrica - Lei dos Julgamentos Categóricos de Thurstone (LJC), Multicriteriais-Compromise Programinng, Electre III, e Promethee II; Análise Multivariada; Krigagem, Redes Neurais Artificiais (RNA); Redes Neurofuzzy. Os resultados produzidos mostraram-se satisfatórios, validando o procedimento proposto para EAD. Procedimento este, fundamental na definição de programas destinados para planejar a capacitação de recursos humanos a distância, bem como para a constituição de outros elementos do capital intelectual em políticas de EAD. / This thesis intends to contribute to the planning guidelines in the field of distance education (DE). Thus, it develops a multi-model reference proposal supported by the definition of a highly complex spectrum of strategies that considers a sequence of systematic procedures in the following phases: (i) Determining the information needs in two stages: (a) identification of the critical success factors (CSF), and (b) identification of the information areas; (ii) Determination of competences in three stages, determining: (a) knowledge, (b) skills, and (c) attitudes; (iii) Determination of the degree of competence evaluation; and (iv) Determination of strategies in knowledge networks. There is the application to a case study of the road concessions in Brazil, within the perspective of public-private partnerships (PPPs). The research was achieved through the intervention of specialists and a small group of students from a DE program (MBA) applied to the PPPs. The data collection was conducted by means of a semi-structured form, the scalar type in a trial matrix, to which experts ascribed their assessments. Several support instruments were used in the modeling elaboration in order to reduce subjectivity in the results: psychometric scales - Thurstones Law of Comparative Judgment (LCJ), Multi-criteria Compromise Programming, Electre III, and Promethee II; Multivariate Analysis; Krigage, Artificial Neural Networking (ANN); Neuro-fuzzy networks. The results produced are satisfactory, validating the proposed procedure for DE. This is an essential procedure for the definition of programs designed to plan the training of human resources at a distance, as well as to establish other elements of intellectual capital for DE guidelines.

A crescente complexidade do controle dos processos industriais vem exigindo sistemas de controle cada vez mais precisos, confiáveis e versáteis. No sentido de atender a estas exigências, algoritmos diversos de controle e estimação, tais como: técnicas de controle adaptativas, preditivas, estimação paramétrica, filtros de Kalman, observação de estados, etc. têm sido desenvolvidas, simuladas e implementadas com relativa facilidade nos modernos sistemas digitais. Este trabalho propõe uma estratégia de controle em redes Fieldbus usando controle adaptativo por modelo de referência através de variáveis de estado, para resolver sistemas complexos. O algoritmo de controle proposto é composto por um observador de estados trabalhando em conjunto com um esquema de controle adaptativo por modelo de referência. As malhas de controle no Fieldbus consistem em um conjunto de blocos funcionais padrões existentes, conectados aos novos blocos funcionais propostos e desenvolvidos de acordo com as especificações da norma Fieldbus Foundation. Este algoritmo de controle realiza os cálculos de maneira distribuída entre os dispositivos da rede Fieldbus, implicando em várias vantagens, tais como: a) perda do supervisório não implica na perda do algoritmo de controle, b) menor tráfego de dados na rede, c) algoritmo de controle que não depende do tempo de processamento do computador. Os resultados dos testes obtidos são apresentados e demonstraram um alto grau de precisão, destacando-se a estabilidade e aplicabilidade do algoritmo proposto. / The rising complexity of the industrial control processes has been claiming more and more accurate, reliable and versatile control systems. Attempting to satisfy this demand, several control and estimation systems algorithms, such as adaptive and predictive techniques, parametric estimation, Kalman filtering, state observation, have been designed, simulated and implemented with relative easiness in the modern digital systems. This work proposes a new control strategy in Fieldbus networks, using adaptive control techniques through state variables, to solve complex systems. The proposed control algorithm is based on an states observer concurrently working with a reference model adaptive control scheme. The modified Fieldbus network consists of a set of standard function blocks, connected to the proposed new function blocks. These new function blocks comply with the specifications of the Fieldbus Foundation norm. This control algorithm accomplishes its calculation in a distributed way among the fieldbus devices. This operating feature results in some advantages, such as: any failure in the supervisory system does not imply in the loss of the control algorithm, b) a lower data transmission in the network, c) control algorithm that does not depend on the processing time of the computer. The obtained results corroborate with the expected advantages of the proposed algorithm, in terms of high degree of accuracy, stability and applicability.

The application of Model Reference Adaptive Control (MRAC) for train dynamic braking is investigated in order to control dynamic braking forces while remaining within the allowable adhesion and coupler forces.  This control method can accurately determine the train braking distance.  One of the critical factors in Positive Train Control (PTC) is accurately estimating train braking distance under different operating conditions.  Accurate estimation of the braking distance will allow trains to be spaced closer together, with reasonable confidence that they will stop without causing a collision.  This study develops a dynamic model of a train consist based on a multibody formulation of railcars, trucks (bogies), and suspensions.   The study includes the derivation of the mathematical model and the results of a numerical study in Matlab.  A three-railcar model is used for performing a parametric study to evaluate how various elements will affect the train stopping distance from an initial speed.  Parameters that can be varied in the model include initial train speed, railcar weight, wheel-rail interface condition, and dynamic braking force.  Other parameters included in the model are aerodynamic drag forces and air brake forces. An MRAC system is developed to control the amount of current through traction motors under various wheel/rail adhesion conditions while braking.  Minimizing the braking distance of a train requires the dynamic braking forces to be maximized within the available wheel/rail adhesion.  Excessively large dynamic braking can cause wheel lockup that can damage the wheels and rail.  Excessive braking forces can also cause large buff loads at the couplers.  For DC traction motors, an MRAC system is used to control the current supplied to the traction motors.  This motor current is directly proportional to the dynamic braking force.  In addition, the MRAC system is also used to control the train speed by controlling the synchronous speed of the AC traction motors.  The goal of both control systems for DC and AC traction motors is to apply maximum available dynamic braking while avoiding wheel lockup and high coupler forces.  The results of the study indicate that the MRAC system significantly improves braking distance while maintaining better wheel/rail adhesion and coupler dynamics during braking.  Furthermore, according to this study, the braking distance can be accurately estimated when MRAC is used.  The robustness of the MRAC system with respect to different parameters is investigated, and the results show an acceptable robust response behavior. / Ph. D.

High blood pressure, also called hypertension is one of the most common worldwide diseases afflicting humans and is a major risk factor for stroke, myocardial infarction, vascular disease, and chronic kidney disease. If blood pressure is controlled and oscillations in the hemodynamic variables are reduced, patients experience fewer complications after surgery. In clinical practice, this is usually achieved using manual drug delivery. Given that different patients have different sensitivity and reaction time to drugs, determining manually the right drug infusion rates may be difficult. This is a problem where automatic drug delivery can provide a solution, especially if it is designed to adapt to variations in the patient’s conditions. This research work presents an investigation into the development of abnormal blood pressure (hypertension) controllers for postoperative patients. Control of the drugs infusion rates is used to simultaneously regulate the hemodynamic variables such as the Mean Arterial Pressure (MAP) and the Cardiac Output (CO) at the desired level. The implementation of optimal control system is very essential to improve the quality of patient care and also to reduce the workload of healthcare staff and costs. Many researchers have conducted studies earlier on modelling and/or control of abnormal blood pressure for postoperative patients. However, there are still many concerns about smooth transition of blood pressure without any side effect. The blood pressure is classified in two categories: high blood pressure (Hypertension) and low blood pressure (Hypotension). The hypertension often occurred after cardiac surgery, and the hypotension occurred during cardiac surgery. To achieve the optimal control solution for these abnormal blood pressures, many methods are proposed, one of the common methods is infusing the drug related to blood pressure to maintain it at the desired level. There are several kinds of vasodilating drugs such as Sodium Nitroprusside (SNP), Dopamine (DPM), Nitro-glycerine (NTG), and so on, which can be used to treat postoperative patients, also used for hypertensive emergencies to keep the blood pressure at safety level. A comparative performance of two types of algorithms has been presented in chapter four. These include the Internal Model Control (IMC), and Proportional-Integral-Derivative (PID) controller. The resulting controllers are implemented, tested and verified for three sensitivity patient response. SNP is used for all three patients’ situation in order to reduce the pressure smoothly and maintain it at the desire level. A Genetic Algorithms (GAs) optimization technique has been implemented to optimise the controllers’ parameters. A set of experiments are presented to demonstrate the merits and capabilities of the control algorithms. The simulation results in chapter four have demonstrated that the performance criteria are satisfied with the IMC, and PID controllers. On the other hand, the settling time for the PID control of all three patients’ response is shorter than the settling time with IMC controller. Using multiple interacting drugs to control both the MAP and CO of patients with different sensitivity to drugs is a challenging task. A Multivariable Model Reference Adaptive Control (MMRAC) algorithm is developed using a two-input, two-output patient model. Because of the difference in patient’s sensitivity to the drug, and in order to cover the wide ranges of patients, Model Reference Adaptive Control (MRAC) has been implemented to obtain the optimal infusion rates of DPM and SNP. This is developed in chapters five and six. Computer simulations were carried out to investigate the performance of this controller. The results show that the proposed adaptive scheme is robust with respect to disturbances and variations in model parameters, the simulation results have demonstrated that this algorithm cannot cover the wide range of patient’s sensitivity to drugs, due to that shortcoming, a PID controller using a Neural Network that tunes the controller parameters was designed and implemented. The parameters of the PID controller were optimised offline using Matlab genetic algorithm. The proposed Neuro-PID controller has been tested and validated to demonstrate its merits and capabilities compared to the existing approaches to cover wide range of patients.

The wind turbine generation system (WTGS) exhibits a nonlinear characteristic and its maximum power point varies with changing atmospheric conditions. In order to operate the WTGS at maximum power output under various wind speeds and to avoid using speed encoder in practical applications, it is necessary to improve the controller system to operate the maximum power points in the WTGS. There are three factors to influence wind generator, the wind speed, power coefficient and the radius of blade. The power coefficient depends on the blade pitch angle and tip speed ratio (TSR). The objective of the dissertation is to develop an intelligent controlled wind energy conversion system (WECS) using AC/DC and DC/AC power converters for grid-connected power application. To achieve a fast and stable response for the real power control, an intelligent controller was proposed, which consists of a fuzzy neural network (FNN), a recurrent fuzzy neural network (RFNN), a wilcoxcon radial basis function network (WRBFN) and a improved Elman neural network (IENN) for MPPT. Furthermore, the parameter of the developed FNN, RFNN, WRBFN and IENN are trained on-line using back-propagation learning algorithm. However, the learning rates in the FNN, RFNN, WRBFN, and IENN are usually selected by trial and error method, which is time-consuming. Therefore, modified particle swarm optimization (MPSO) method is adopted to adjust the learning rates to improve the learning capability of the developed RFNN, WRBFN and IENN. Moreover, presents the estimation of the rotor speed is based on the sliding mode and model reference adaptive system (MRAS) speed observer theory. Furthermore, a sensorless vector-control strategy for an induction generator (IG) operating in a grid-connected variable speed wind energy conversion system can be achieved. On the other hand, a WRBFN based with hill-climb searching (HCS) maximum-power-point-tracking (MPPT) strategy is proposed for permanent magnet synchronous generator (PMSG) with a variable speed wind turbine. Finally, many simulation results are provided to show the effectiveness of the proposed intelligent control wind generation systems.

iv ABSTRACT ADAPTIVE CONTROL OF GUIDED MISSILES Tiryaki Kutluay, Kadriye Ph.D., Department of Aerospace Engineering Supervisor: Asst. Prof. Dr. Ilkay Yavrucuk February 2011, 147 Pages This thesis presents applications and an analysis of various adaptive control augmentation schemes to various baseline flight control systems of an air to ground guided missile. The missile model used in this research has aerodynamic control surfaces on its tail section. The missile is desired to make skid to turn maneuvers by following acceleration commands in the pitch and yaw axis, and by keeping zero roll attitude. First, a linear quadratic regulator baseline autopilot is designed for the control of the missile acceleration in pitch axis at a single point in the flight envelope. This baseline autopilot is then augmented with a Direct Model Reference Adaptive Control (DMRAC) scheme using Neural Networks for parameter estimation, and an L1 Adaptive Control scheme. Using the linearized longitudinal model of the missile at the design point, simulations are performed to analyze and demonstrate the performance of the two adaptive augmentation schemes. By injecting uncertainties to the plant model, the effects of adaptive augmentations on the linear baseline autopilot are examined. v Secondly, a high fidelity simulation software of the missile is used in order to analyze the performance of the adaptive augmentations in 6 DoF nonlinear flight simulations. For the control of the missile in three axis, baseline autopilots are designed using dynamic inversion at a single point in the flight envelope. A linearizing transformation is employed during the inversion process. These coarsely designed baseline autopilots are augmented with L1 adaptive control elements. The performance of the adaptive control augmentation system is tested in the presence of perturbations in the aerodynamic model and increase in input gain, and the simulation results are presented.

No description available.

High blood pressure, also called hypertension is one of the most common worldwide diseases afflicting humans and is a major risk factor for stroke, myocardial infarction, vascular disease, and chronic kidney disease. If blood pressure is controlled and oscillations in the hemodynamic variables are reduced, patients experience fewer complications after surgery. In clinical practice, this is usually achieved using manual drug delivery. Given that different patients have different sensitivity and reaction time to drugs, determining manually the right drug infusion rates may be difficult. This is a problem where automatic drug delivery can provide a solution, especially if it is designed to adapt to variations in the patient’s conditions. This research work presents an investigation into the development of abnormal blood pressure (hypertension) controllers for postoperative patients. Control of the drugs infusion rates is used to simultaneously regulate the hemodynamic variables such as the Mean Arterial Pressure (MAP) and the Cardiac Output (CO) at the desired level. The implementation of optimal control system is very essential to improve the quality of patient care and also to reduce the workload of healthcare staff and costs. Many researchers have conducted studies earlier on modelling and/or control of abnormal blood pressure for postoperative patients. However, there are still many concerns about smooth transition of blood pressure without any side effect. The blood pressure is classified in two categories: high blood pressure (Hypertension) and low blood pressure (Hypotension). The hypertension often occurred after cardiac surgery, and the hypotension occurred during cardiac surgery. To achieve the optimal control solution for these abnormal blood pressures, many methods are proposed, one of the common methods is infusing the drug related to blood pressure to maintain it at the desired level. There are several kinds of vasodilating drugs such as Sodium Nitroprusside (SNP), Dopamine (DPM), Nitro-glycerine (NTG), and so on, which can be used to treat postoperative patients, also used for hypertensive emergencies to keep the blood pressure at safety level. A comparative performance of two types of algorithms has been presented in chapter four. These include the Internal Model Control (IMC), and Proportional-Integral-Derivative (PID) controller. The resulting controllers are implemented, tested and verified for three sensitivity patient response. SNP is used for all three patients’ situation in order to reduce the pressure smoothly and maintain it at the desire level. A Genetic Algorithms (GAs) optimization technique has been implemented to optimise the controllers’ parameters. A set of experiments are presented to demonstrate the merits and capabilities of the control algorithms. The simulation results in chapter four have demonstrated that the performance criteria are satisfied with the IMC, and PID controllers. On the other hand, the settling time for the PID control of all three patients’ response is shorter than the settling time with IMC controller. Using multiple interacting drugs to control both the MAP and CO of patients with different sensitivity to drugs is a challenging task. A Multivariable Model Reference Adaptive Control (MMRAC) algorithm is developed using a two-input, two-output patient model. Because of the difference in patient’s sensitivity to the drug, and in order to cover the wide ranges of patients, Model Reference Adaptive Control (MRAC) has been implemented to obtain the optimal infusion rates of DPM and SNP. This is developed in chapters five and six. Computer simulations were carried out to investigate the performance of this controller. The results show that the proposed adaptive scheme is robust with respect to disturbances and variations in model parameters, the simulation results have demonstrated that this algorithm cannot cover the wide range of patient’s sensitivity to drugs, due to that shortcoming, a PID controller using a Neural Network that tunes the controller parameters was designed and implemented. The parameters of the PID controller were optimised offline using Matlab genetic algorithm. The proposed Neuro-PID controller has been tested and validated to demonstrate its merits and capabilities compared to the existing approaches to cover wide range of patients. / Libyan Ministry of Higher Education scholarship