Adequate control of the position of the plasma column within the STOR-M tokamak is a chief requirement in order for experimental quality discharges to be obtained. Optimal control over tokamak discharge parameters, including the plasma position, is very difficult to achieve. This is due in large part to the difficulty in modelling the tokamak discharge parameters, as they are highly nonlinear and time varying in nature. The difficulty of modelling the tokamak discharge parameters suggests that a control system, such as a fuzzy logic based controller, which does not require a system model may be well suited to the control of fusion plasma. In order to improve the quality of control over the plasma position within the STOR-M tokamak, the existing analog PID controller was modified. These modifications facilitate the application of a digital controller by a personal computer via the Advantech PCL-711B data acquisition card. The performance of the modified plasma position controller and an Arbitrary Signal Generator developed by the author was evaluated. This modified plasma position controller was applied successfully to the STOR-M tokamak during both normal mode and A.C. mode operation. In both cases, the modified controller provided adequate control over the position of the plasma column within the discharge chamber. Furthermore, the modified controller was more convenient to optimize than the original, existing analog PID controller. By taking advantage of the modifications that were made to the plasma position controller, a fuzzy logic controller was developed by the author. The fuzzy logic based plasma position controller was also successfully applied to the STOR-M tokamak during both normal mode and A.C. operation. The fuzzy controller was demonstrated to reliably provide a higher degree of control over the position of the plasma column within the STOR-M tokamak than the modified PID controller.

Industrial applications increasingly require actuators that offer a combination of high force output, large stroke and high accuracy. The ElectroHydraulic Actuator (EHA) was designed by Drs. Habibi and Goldenberg originally as a high-performance actuator for use in robotics. However, it was determined that the EHA had the potential to achieve high positional accuracy. Little research has been performed in the area of high-accuracy hydraulic positioning systems. Therefore, the objective of this study to achieve nano-scale positional accuracy with the EHA while maintaining large stroke and high force output. It was planned to achieve this objective through modification of the prototype EHA and the use of fuzzy control. During this research project, both hardware and control system modifications to the EHA were performed. A high-precision optical encoder position sensor with a 50 nm resolution was mounted on the inertial load to directly measure the position of the load. A number of device drivers were written to interface the MATLAB real-time control environment with the optical encoder and servo motor amplifier. A Sugeno-inference fuzzy controller was designed and implemented in MATLAB. For comparison purposes, a switched-gain controller and a proportional controller were also implemented in the control environment. The performance of the fuzzy controller was compared to the switched-gain controller and the proportional controller in a number of tests. First, the regulatory and tracking performance of the EHA with an inertial load of 20 kg was examined. It was determined in the regulatory tests that the positional accuracy of the EHA with the fuzzy controller was excellent, achieving a steady state error of 50 ± 25 nm or less for step inputs in the range 5 cm to 200 nm. The positional accuracy during the tracking tests was found to be reduced compared to the regulatory tests since the actuator did not have sufficient time to settle to final accuracy due to the timevarying input signals. In all cases, it was found that the positional accuracy of the EHA with the fuzzy controller was significantly greater than with the switched-gain and proportional controllers for both regulatory and tracking signals. Testing with the inertial load eliminated or changed was not performed because the position sensor was mounted to the load, making it unfeasible to alter the load during the time frame of this study. The regulatory and tracking performance of the EHA with an inertial load of 20 kg plus external resistive loads of 90 to 280 N were investigated. It was found that the positional accuracy of the EHA decreased with the application of an external load to 3.10 ± 0.835 µm for a 1 cm step input (90 N load) and 8.45 ± 0.400 µm for a 3 cm step input (280 N load). Again, the positional accuracy of the EHA decreased during the tracking tests relative to the regulatory tests, for the reason stated above. This implies that the positional accuracy of the EHA with a resistive load is in the microscale, rather than the nano-scale as was put forth as the objective of this study. Nevertheless, the positional accuracy of the EHA with the fuzzy controller was found to be significantly greater than with the switched-gain and proportional controllers. It is postulated that the increase in positional error observed during the external load tests was due to an increase in cross-port leakage, relative to the inertial load tests, caused by the pressure differential induced across the actuator by the external load. Methods of reducing the increase in positional error caused by external loads on the EHA remains an area for future study.

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This thesis presents a visual servo control scheme for a ball-and-plate system with a maze. The maze built on the plate forms obstacles for the ball and increases variety and complexity of its environment. The ball-and-plate system is a two degrees-of-freedom robotic wrist with an acrylic plate attached as the end effector. By using image processing techniques, the ball¡¦s position is acquired from the visual feedback, which was implemented with a webcam and a personal computer. A fuzzy controller, which provides dexterity of the robotic wrist, is designed to decide the slope angles of the plate to guide the ball to a designated target spot. Using the method of distance transform, the path planning based on the current position of the ball is conducted to find the shortest path toward the target spot. Besides, a relaxed path, appears to be more suitable for actual applications, is provided by the obstacle¡¦s expansion approach. Experimental results show that the presented control framework successfully leads the ball to pass through the maze and arrive at target spot. The visual servo control scheme works effectively in both stabilization and tracking control. Based on this preliminary achievement, further improvement and deeper exploration on related research topics can be carried on in the future.

[pt] Um controlador Heurístico Adaptativo baseia-se num conjunto de regras lingüísticas para conduzir um processo com modelo impreciso ou complexo ao estado desejado. O comportamento do processo deve respeitar os requisitos de performance predefinidos. Para satisfazer estes objetivos, a estrutura interna do controle sofre mudanças para adequá- la as condições vigentes no processo. Os métodos de adaptação abordados consideram a modificação de uma estrutura matricial interpretada como as correções incrementais, compatíveis com os ajustes a serem efetuados sobre o processo, ou como regras, constituídas por variáveis nebulosas, que requerem manipulações adicionais para produzir a saída do controlador. Em qualquer dos casos, a adaptação é realizada a partir de uma Tabela de Índices de Performance. Para facilitar a sua obtenção é implementado um procedimento, que fornece a representação matricial das regras lingüísticas, concatenadas na forma de um Algoritmo Lingüístico de Controle. O comportamento dinâmico do Sistema, composto pelos Controladores Heurísticos e por processos com modelos distintos, é considerado para Tabelas de índices de Performance com várias dimensões. As regras lingüísticas, correlacionadas com estas tabelas, foram elaboradas com diversas classes de atributos. As simulações realizadas concentram-se sobre os parâmetros dos controladores, que influenciam significativa- Os estudos abordam também o comportamento da estrutura interna destes controladores e o seu desempenho em termos da velocidade de atuação sobre o processo. / [en] A heuristic Controller uses a set of linguistic rules, which are derived from expertise or human operators´ skills, in order to achieve control of processes that have inaccurate or complex models. An adaptative Heuristic Controller adjusts the set of rules in an automatic and continuous way, aiming to achieve prescribed objectives indicated by a performance measure. The adaptative procedures modify a matrix, the elements of which are either incremental corrections or numeric rules associated with fuzzy variables. In both cases a Performance Index Table and a learning method are employed to correct that matrix. The Performance Table is a matrix calculated from a set of linguistic rules. The controllers are implemented with different Performance Tables, considering various sets of linguistic values and quantization levels. The dynamic behaviour of overdamped and underdamped processes is investigated. The performance of simulated systems is analyzed with respect to relevant parameters that affect their behaviour.

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This thesis presents collision avoidance integrated with lane keeping and adaptive cruise control for a car. Collision avoidance is the ability to avoid obstacles that are in the vehicle's path, without causing damage to the obstacle or car. There are three types of collision avoidance controllers, passive, active, and semi-active. This thesis is designed using active collision avoidance controllers. There are two controllers developed for collision avoidance in this paper. They are an optimal controller and a fuzzy controller. The optimal vehicle trajectory, which maximizes the distance to an obstacle and changes lanes, is derived. The optimal collision avoidance controller is a closed loop controller; with the decisions based on the current state. The fuzzy controller makes decisions based on the system rules. A simulation environment was created to compare these two controllers as viable solutions for collision avoidance. The environment uses MATLAB/Simulink for simulation of the vehicle as well as the optimal and fuzzy controllers. The simulation incorporates system blocks of the kinematics of a car, navigation, states, control law, and velocity controller. Once the controllers are fully developed and tested in the simulation environment, they are implemented and tested on the platform vehicle. This verifies the real world performance of the controllers. The platform vehicle is a modified radio controlled car. This car is completely autonomous. The car has onboard sensors that allow it to follow a white piece of tape as well as detect obstacles. / Master of Science

To reinforce its Inez network, which was operated close to its stability limits, American Electric Power (AEP) undertook two major developments, one being the installation of a Static Var Compensator (SVC) in November, 1980 and the other one being the installation of the world's first Unified Power Flow Controller (UPFC) in 1998. The controllers in the system include the Automatic Voltage Regulators (AVRs) of the generators, the controllers of the SVC, and UPFC. To coordinate the control actions of these controllers and prevent voltage instability resulting from their fighting against each other, a two level hierarchical control scheme using fuzzy logic has been developed and its performance was assessed via simulations. The second level of the hierarchy determines the set points of the local controllers of the AVRs, SVC, and UPFC and defines the switching sequences of the capacitor banks, the goal being to maximize the reactive reserve margins of the Inez subsystem. Numerous simulations were carried out on this system to determine the actions of the fuzzy controller required to prevent the occurrence of voltage collapse under double contingency. Simulations have revealed the occurrence of nonlinear interactions between the machines resulting in stable limit cycles, nonlinear oscillations undergoing period doubling leading to chaos and possible voltage collapse. The proposed fuzzy scheme provides a fast, simple and effective way to stretch the stability limit of the system for double contingency conditions, up to 175 MW in some cases. This is a significant increase in the system capacity. / Master of Science