Thales E. P. Almeida

Anti-windup method for fuzzy PD+I, PI and PID controllers applied in brushless DC motor speed control

This paper proposes a new anti-windup method for integrative portion of many controllers: PI, PID and fuzzy PD+I. The proposed method does not require any coefficient for the anti-windup method, as other known anti-windup methods does. All the deduction and development of the proposed anti-windup method for PI, PID and fuzzy PD+I are presented here, resulting in two general and simple anti-windup equivalent methods. Following, the application of the proposed anti-windup method in a brushless DC motor speed control, employing a fuzzy PD+I controller, is shown and compared to a traditional anti-windup method, which achieves better results than that traditional method.

Improved Sensorless Vector Control of Induction motor Using Sliding Mode Observer

This work deals with a sensorless speed control for three-phase induction motor in order to improve its operation at low speed. Initially, a direct field oriented control employing space vector pulse with modulation based on sliding mode observer (SMO) is studied and evaluated due to its high accuracy in estimating the flux at low speed. The proposed current model based on SMO provides good speed estimation under low speed and parameter or load changes. Simulations and experimental tests with diferent operational conditions at low speed are carried out in order to test the sensorless control. The results show a good perfomance and agreed with the results shown in recent papers.

Integral sliding mode controller with anti-windup method analysis in the vector control of induction motor

This work presents an integral sliding mode controller, applied to the three-phase induction motor IM using indirect field oriented control technique. Besides seeking high dynamic performance using the slinding mode controller, it is discussed the necessity of a parametric action control (known as equivalent control) to turn the system stable. To do so, it is used an integral sliding mode controller with anti-windup method. The motor performance is verified by means of numeric simulations and experimental tests with load disturbances.

Improved finite control-set model-based direct power control of BLDC motor with reduced torque ripple

Brushless DC (BLDC) motor is used in a wide range of applications due to its high efficiency and high power density. However, as its main drawback, it develops significant torque ripple during phase commutation in conventional 120° conducting mode operation. To reduce torque undulations, this paper presents a simple approach for BLDC motor drive by applying a model-based predictive direct power control (MPDPC) with duty cycle concept. As a result of controlling active and reactive power exchanged between stator and rotor, low torque ripple can be achieved. Compared to priors works, this paper introduces the duty cycle concept with lower complexity and number of calculations to improve the conventional MPDPC steady-state performance. The effectiveness of proposed approach is demonstrated by simulation results.

Investigation of Reluctance Torque in a BLDC Motor using Frozen Permeability Method and Equivalent Air-gap Analysis

This work investigates the reluctance torque in a surface mounted Brushless DC motor (BLDC) regarding the saturation effects due to the increase of electric load. At first, the reluctance torque is evaluated considering the line inductance waveforms for three different electromagnetic load conditions. Based on these results, which show an impressive change on the behavior of reluctance torque due to electromagnetic saturation, a further investigation is carried out in order to clarify the role played by each tooth in the reluctance torque, and of course, in the line inductance waveforms. These investigations are carried out with the aid of Frozen Permeability Method and the Equivalent Air-gap Analysis.

Pseudo sliding mode control with integrative action applied to brushless DC motor speed control

Although sliding mode control has many drawbacks when applied to electrical drives due to real limitations of switches, as limited frequency of operation, turn on and turn off delays, some of its theory can be succesfully used in order to project a high performance controller, robust and with a reduced design effort. This paper shows the use of sigmoidal function, hyperbolic tangent, instead of the signal function. So, it actually consists not in a pure but in a pseudo (or quasi) sliding mode, combined to an integrative controller action and with an anti-windup effect, so the result is a high performance controller, robust to machine parameters and disturbances, and light in its design. Results shows its high performance and robustness. The chosen sliding surface has integrative control action combined to an anti-windup feature, which zeroes the steady state error and minimizes the output system overshoot.

Low cost heading sensing system for an autonomous aquatic surface vehicle

This work describes the development of a heading reference system composed of low cost inertial sensors with MicroElectroMechanical Systems (MEMS) technology, which present high noise levels. Thus, filtering and sensors measurements fusion is done in order to achieve a reliable estimation, trough an extended Kalman filter. The system is used for navigation and control of an autonomous aquatic surface vehicle. In this work, the principles of inertial navigation, orientation representation as well as the coordinate frames involved are investigated, presenting the quaternion method, and the update procedure according to the heading changes. The developed system was tested in the lab and on a trimaran shaped vessel navigating on a dam.

Fault identification in doubly fed induction generator using FFT and neural networks

This paper presents a fault identification system for doubly fed induction generator (DFIG). It considers cases of single phase short-circuits and load switching. The system uses the fast fourier transform (FFT) to preprocessor data, which consist by the stator line currents. The principal component analysis (PCA) is employed to reduce the dimensionality of the output data of FFT and the fault identification is made by means of artificial neural network (ANN). Also, a post-processing (PP) is employed in order to increase the network reliability, which reduces the error of ANN. The system is simulated in the MATLAB simulation software using a database with different voltage, speed and load. The results show that the system with PCA, FFT and ANN has a good performance and accuracy with the PP to fault identification in the DFIG.