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.

The following topics are dealt with: fuzzy set theory; learning (artificial intelligence); fuzzy logic; fuzzy control; pattern clustering; pattern classification; fuzzy reasoning; fuzzy systems; decision making; control system synthesis.

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.

This paper presents the implementation of a fuzzy control strategy for speed regulation of an electromagnetic frequency regulator (EFR) prototype, aiming to eliminate the dependence on knowledge of physical parameters in the most diverse operating conditions. Speed multiplication is one of the most important steps in wind power generation. Gearboxes are generally used for this purpose. However, they have a reduced lifespan and a high failure rate, and are still noise sources. The search for new ways to match the speed (and torque) between the turbine and the generator is an important research area to increase the energy, financial, and environmental efficiency of wind systems. The EFR device is an example of an alternative technology that this team of researchers has proposed. It considers the main advantages of an induction machine with the rotor in a squirrel cage positively. In the first studies, the EFR control strategy consisted of the conventional PID controllers, which have several limitations that are widely discussed in the literature. This strategy also limits the EFR’s performance, considering its entire operating range. The simulation program was developed using the Matlab/Simulink platform, while the experimental results were obtained in the laboratory emulating the EFR-based system. The EFR prototype has 2 poles, a nominal power of 2.2 kW, and a nominal frequency of 60 Hz. Experimental results were presented to validate the efficiency of the proposed control strategy.

The insertion of photovoltaic (PV) systems on the small-scale low voltage (LV) networks can result in operational instability conditions due to the PV undispatched behavior and current harmonic injection. This paper presents a study of the impact evaluation of PV systems with different penetration levels and operational scenarios in a LV network. The conducted studies evaluate the effects verified at the point of common coupling (PCC) when PV system injects power with different penetration levels. For evaluating these effects, the internal impedance of the PCC is estimated based on a injection signal scheme. The network impacts evaluation uses standards for small-scale grid-connected PV systems in which reactive power compensation is rarely implemented. Experimental results demonstrate the impact of PV by analysing the variables: voltage fluctuation, harmonic distortion, and unbalanced level. Based on this, it is possible to evaluate the impact of the PV on the LV networks, which provides a strategic information for determining the proper penetration level for insertion small-scale PVs LV microgrids.

The growing demand for clean energy sources has driven the insertion of photovoltaics (PV) in low-voltage networks. However, the non-dispatchable nature of these units can produce instability issues like voltage fluctuations or frequency deviation. It can be worse if these units are connected to a weak network. One way to overcome this problem is to impose suitable impedance values on PV inverter. However, it is hard to shape the PV output impedance by simply adjusting its control loop gains. For that reason, this paper proposes a method for shaping the PV output impedance by using a virtual impedance scheme, which can be designed independently of the PV control system. With the proposed method, the stability margin of grid-connected system can be increased by imposing desirable PV output impedance. Experimental results validate the proposed impedance shaping strategy.