Nowadays, high portion of tactical missiles use gimbaled seeker. For accurate target tracking, the platform where the gimbal is mounted must be stabilized with respect to the motion of the missile body. Line of sight stabilization is critical for fast and precise tracking and alignment. Although, conventional PID framework solves many stabilization problems, it is reported that many PID feedback loops are poorly tuned. In this thesis, recently introduced robot control method, proxy based sliding mode control, is adopted for the line of sight (LOS) stabilization. Before selecting the proposed method, adaptive neural network sliding mode control and fuzzy control are also implemented for comparative purposes. Experimental and simulation results show a satisfactory response of the proxy based sliding mode controller.

This thesis focuses on the design of an electrical drive system for the purpose of high precision motion control. A modern electrical drive is usually equipped with a current regulated voltage source along with powerful motion controller system utilizing one or more micro-controllers and/or digital signal processors (DSPs). That is, the motor drive control is mostly performed by a dedicated digital-motion controller system. Such a motor drive mostly interfaces with its host processor via various serial communication protocols such as Profibus, CAN+, RS-485 etc. for the purpose of receiving commands and sending out important status/control signals. Considering that the motor drives lie at the heart of every (multi-axis) motion control system, the aim of this thesis is to explore the design and implementation of a conventional DC motor drive system suitable for most industrial applications that require precision and accuracy. To achieve this goal, various underlying control concepts and important implementation details are rigorously investigated in this study. A low power DC motor drive system with a power module, a current regulator and a motion controller is built and tested. Several design revisions on these subsystems are made so as to improve the overall performance of the drive system itself. Consequently, important &ldquo / know-how&rdquo / required for building high performance (and high power) DC motor drives is gained in this research.

Smart structures become highly popular with the developing technology. The aim of this study is to develop a basic model, which can be also used in the design of more complex systems by performing simultaneous optimization of a structure and associated controller with respect to some design parameters and feedback gains. In this thesis work, two smart structures are used as case studies and their results are compared with the available results in the literature. The first case study is simple twobar truss problem controlled by either one or two actuators. This problem is solved both numerically and analytically. The latter is a twenty-element parabolic truss, which is controlled by four actuators. This problem is solved numerically only. In the optimization process, the design parameters are taken as the cross sectional areas of bar elements, positions and/or number of actuators, and the elements of closed loop gain matrix. In the second case study, in addition to these parameters, shape design parameters are also optimized. A coordinate transformation is applied in both cases from the displacement space to the modal space. The modal model reduction method is used in the design of second problem. The optimization goal in both cases studies is to minimize the system energy while satisfying some frequency and mass constraints. In the second case study, in addition to the original objective function, system controllability and stability robustness are also maximized. In the solution of design problem, two optimization algorithms are used one embedded within the other. In the outer loop, a hide and seek simulated annealing algorithm optimizes structural design parameters, and positions and/or number of actuators. In order to generate a candidate design family for this level, optimal closed loop gain matrices are calculated by using MATLAB&reg / .

New control methods are developed for the unconstrained motion and constrained force and motion control of flexible robots. The dynamic equations of the flexible robots are partitioned as pseudostatic equilibrium equations and deviations from them. The pseudostatic equilibrium considered here is defined as a hypothetical state where the tip point variables have their desired values while the modal variables are instantaneously constant. Then, the control torques for the pseudostatic equilibrium and for the stabilization of the deviation equations are formed in terms of tip point coordinates, modal variables and contact force components. The performances of the proposed methods are illustrated on a planar two-link robot and on a spatial three-link robot. Unmodeled dynamics and measurement noises are also taken into consideration. Performance of the proposed motion control method is compared with the computed torque method.

Orientador: Gilmar Barreto / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-09T16:50:00Z (GMT). No. of bitstreams: 1 Giesbrecht_Mateus_M.pdf: 3904732 bytes, checksum: 55e43903b08b7c8d770f9120fb071c40 (MD5) Previous issue date: 2007 / Resumo: A motivação para este estudo é criar um modelo computacional capaz de prever se o regime de trabalho a que um motor monofásico de indução é submetido implica ou não em um aquecimento que comprometa os materiais isolantes do mesmo. A solução apresentada busca encontrar uma equação a diferenças em que a saída do sistema (temperatura do motor no instante k+1) é calculada como uma combinação linear das entradas (temperatura do motor, valor RMS da corrente e temperatura ambiente no instante k). Para conhecer os coeficientes desta combinação linear, foram realizados alguns ensaios e, a partir de seus resultados, foi aplicado o método dos mínimos quadrados para a obtenção do modelo computacional que representa o sistema. Os resultados computacionais obtidos com o modelo proposto refletem com exatidão o comportamento do sistema real. O modelo desenvolvido também é útil para outras aplicações em que se utilize um motor de indução monofásico em regime intermitente periódico com partida / Abstract: This study motivation was finding a computer-based model that was able to foresee if the duty cycle applied in a single-phase induction motor implies or not in an overheating that can compromise the motor insulation. The solution presented here is based on finding a difference equation in which the system output (motor temperature at time k+1) is calculated as a linear combination of the input (motor temperature, RMS current and ambient temperature at time k). The Mean Square Method was applied to find the coefficients of this linear combination, resulting in the final computational model that represents the system. The computational results found with the proposed model reflect exactly the real system behaviour. This model is also useful to other applications in which a single-phase induction motor during intermittent periodic duty with starting is used. / Mestrado / Automação / Mestre em Engenharia Elétrica

Inertial Measurement Unit (IMU) and Global Positioning System (GPS) receivers are sensors that are widely used for land vehicle navigation. GPS receivers provide position and/or velocity data to any user on the Earth&rsquo / s surface independent of his position. Yet, there are some conditions that the receiver encounters difficulties, such as weather conditions and some blockage problems due to buildings, trees etc. Due to these difficulties, GPS receivers&rsquo / errors increase. On the other hand, IMU works with respect to Newton&rsquo / s laws. Thus, in stark contrast with other navigation sensors (i.e. radar, ultrasonic sensors etc.), it is not corrupted by external signals. Owing to this feature, IMU is used in almost all navigation applications. However, it has some disadvantages such as possible alignment errors, computational errors and instrumentation errors (e.g., bias, scale factor, random noise, nonlinearity etc.). Therefore, a fusion or integration of GPS and IMU provides a more accurate navigation data compared to only GPS or only IMU navigation data. v In this thesis, loosely coupled GPS/IMU integration systems are implemented using feed forward and feedback configurations. The mechanization equations, which convert the IMU navigation data (i.e. acceleration and angular velocity components) with respect to an inertial reference frame to position, velocity and orientation data with respect to any desired frame, are derived for the geographical frame. In other words, the mechanization equations convert the IMU data to the Inertial Navigation System (INS) data. Concerning this conversion, error model of INS is developed using the perturbation of the mechanization equations and adding the IMU&rsquo / s sensor&rsquo / s error model to the perturbed mechanization equation. Based on this error model, a Kalman filter is constructed. Finally, current navigation data is calculated using IMU data with the help of the mechanization equations. GPS receiver supplies external measurement data to Kalman filter. Kalman filter estimates the error of INS using the error mathematical model and current navigation data is updated using Kalman filter error estimates. Within the scope of this study, some real experimental tests are carried out using the software developed as a part of this study. The test results verify that feedback GPS/INS integration is more accurate and reliable than feed forward GPS/INS. In addition, some tests are carried out to observe the results when the GPS receiver&rsquo / s data lost. In these tests also, the feedback GPS/INS integration is observed to have better performance than the feed forward GPS/INS integration.

In this study, a parametric model for a main battle tank electric gun turret drive system stabilization controller has been developed. Main scope was the study of the muzzle deviation due to barrel flexibility. Traverse and elevation dynamics has been modeled to include the drive-line and barrel flexibilities. Order of the models has been kept large enough to cover the frequencies dominant in the interest scope but at the same time low enough to create a parametric model which can be used in real-time fire control computers. Therefore a 5-dof elevation and a 7-dof traverse models have been implemented. These models have been used to design a classical feedback and feedforward controllers which performed good enough to meet 0.5mrad stabilization accuracies. After satisfactory results have been obtained from the stabilization controller, a special coincidence algorithm has been implemented by time-series analysis of the disturbance signal which is constantly being measured by the feedforward gyro. Necessity of predicting the future muzzle angular orientation due to the latency in fire is discussed and by using autoregressive modeling of the disturbance signal, future values of the disturbance signal has been entered into the observer model. The prediction horizon has been set to the time delay value between the trigger is pulled by the gunner and the ammunition exit from the muzzle. By checking the future coincidence within a very narrow windowing (0.05mrad) a 100% first round hit probability in theory has been achieved. This is assured since the coincidence inhibited the fire signals which were to miss the aiming point with a large error.

This doctoral study aims to develop a methodology for use in determining aerodynamic models and parameters from actual flight test data for different types of autonomous flight vehicles. The stepwise regression method and equation error method are utilized for the aerodynamic model identification and parameter estimation. A closed loop aerodynamic parameter estimation approach is also applied in this study which can be used to fine tune the model parameters. Genetic algorithm is used as the optimization kernel for this purpose. In the optimization scheme, an input error cost function is used together with a final position penalty as opposed to widely utilized output error cost function. Available methods in the literature are developed for and mostly applied to the aerodynamic system identification problem of piloted aircraft / a very limited number of studies on autonomous vehicles are available in the open literature. This doctoral study shows the applicability of the existing methods to aerodynamic model identification and parameter estimation problem of autonomous vehicles. Also practical considerations for the application of model structure determination methods to autonomous vehicles are not well defined in the literature and this study serves as a guide to these considerations.