In this paper, a radial position control approach of a bearingless induction motor is proposed. The rotor is supported by magnetic forces, which is complex to model. Generally, simplifications are adopted to determine a linearized model that hinders classical controllers' performance. On the other hand, fuzzy controllers have non-linear characteristics and do not require precise mathematical models. Instead, it uses the experience and knowledge of human operators to build a knowledge base to be used on the control. The prototype under study is a three-phase induction motor without a rated power of 1 HP, 4-pole, 220/380V and rated current 3/1.75A. It operates on a vertical axis, so there is no need to compensate for the rotor weight. The paper proposes the implementation of a Mamdani Fuzzy PD controller in order to control the rotor radial position of a three-phase induction motor by means of a Texas Instruments TMS320F28335 Digital Signal Processor (DSP). We present experimental results that validate the good performance of the fuzzy controller.

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The electromagnetic frequency regulator (EFR) device has proven to be an attractive solution for driving grid-connected electrical generators in distributed generation (DG) systems based on renewable energy sources (RES). However, the dynamic characteristic of the EFR has not yet been discussed for cases where its parameters vary from the nominal values. To evaluate this issue, this paper proposes a method for transient and steady-state performance analysis applied to the EFR device considering parametric variations. To perform this analysis, a dynamic model of the EFR device is derived, and its dynamic characteristics are discussed. Based on this model, the system’s controller gains are designed by using the root-locus method (RLM) to obtain the desired dynamic performance. Then, a sensitivity analysis of the closed-loop poles under the effect of parameters variation is performed. In addition, the paper also presents an analysis of the EFR-based system operating with the designed controllers. The proposed theoretical analysis is assessed using simulation and experimental results. The simulation program was developed using a Matlab/Simulink platform, while the experimental results were obtained through a laboratory setup emulating the EFR-based system.

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