الفهرس 
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Abstract
This thesis studies linear induction motor design equations and the equivalent circuit model. Also the block diagram of the LIM is presented describing the component and the main relations. The simulation of the LIM based on Simulink Mathlab ® software program is given as relations between the variables and the motor parameters. The control techniques will be presented for the induction motor. Two prototypes of linear induction motors are presented. The thesis presents a new two degree of linear motion in X- Y plane and therefore a multi-axis motion. The complete implementation of the field oriented control of induction motor using digital signal processor DSP is presented. Finally, a temperature estimation algorithm based on the field oriented control of induction motor is simulated and implemented using the DSP.The main focus of the study is the implementation of techniques regarding flux estimation and rotor speed estimation by the use of sensorless closed-loop observers. Within this framework, the information about the mathematical representation of the induction motor, pulse width modulation technique and flux oriented vector control techniques together with speed adaptive flux estimation -a kind of sensorless closed loop estimation technique- and Kalman filters is given. With the comparison of sensorless closed-loop speed estimation techniques, it has been attempted to identify their superiority and inferiority to each other by the use of simulation models and real-time experiments. In the experiments, the performance of the techniques developed and used in the thesis has been examined under extensively changing speed and load conditions. The real-time experiments have been carried out by the use of TI TMS320F28 I 2 digital signal processor, control card and the motor drive card Furthermore, Mathlab ”Embedded Target for the TI C2000 DSP” and ”Code Composer Studio” software tools have been used. The simulations and experiments conducted in the study have illustrated that it is possible to increase the performance at low speeds at the expense of increased computational burden on the processor.