Juvenal Rodriguez-Resendiz

Adjustable Speed Drive Project for Teaching a Servo Systems Course Laboratory

This paper describes an adjustable speed drive for a three-phase motor, which has been implemented as a design for a servo system laboratory course in an engineering curriculum. The platform is controlled and analyzed in a LabVIEW environment and run on a PC. Theory is introduced in order to show the sensorless algorithms. These are computed by means of speed feedback from speed and flux estimators, which provide tracking of these variables in spite of the presence of an uncertain load torque and changes in the time constant. The novel electronic architecture permits students to use low-cost hardware. The project was divided into several subsystems in order to give students the opportunity to construct a tuning procedure for torque and speed control loops.

A New Adaptive Self-Tuning Fourier Coefficients Algorithm for Periodic Torque Ripple Minimization in Permanent Magnet Synchronous Motors (PMSM)

Torque ripple occurs in Permanent Magnet Synchronous Motors (PMSMs) due to the non-sinusoidal flux density distribution around the air-gap and variable magnetic reluctance of the air-gap due to the stator slots distribution. These torque ripples change periodically with rotor position and are apparent as speed variations, which degrade the PMSM drive performance, particularly at low speeds, because of low inertial filtering. In this paper, a new self-tuning algorithm is developed for determining the Fourier Series Controller coefficients with the aim of reducing the torque ripple in a PMSM, thus allowing for a smoother operation. This algorithm adjusts the controller parameters based on the components harmonic distortion in time domain of the compensation signal. Experimental evaluation is performed on a DSP-controlled PMSM evaluation platform. Test results obtained validate the effectiveness of the proposed self-tuning algorithm, with the Fourier series expansion scheme, in reducing the torque ripple.

A review of parameter estimators and controllers for induction motors based on artificial neural networks

Induction motors (IMs) are the most used electromechanic machines in industrial applications. Their control has become the subject of many studies since the 70s, and there have been several approaches to achieve high-performance adjustable speed drivers (ASDs). The review presented in this article can support the state of some related researches, since it deals with current state-of-the-art of Artificial Neural Networks (ANNs) oriented to experiments that perform motion control with induction motors. It summarizes many previous works focused on IM and can help the reader to have a starting point to begin their own research on choosing a correct type of Neural Network (NN). The paper provides a list of ANNs used to improve the ASD-control, extending the IM-driver life and achieving proper motor operation, their size and performance. A good match between IM parameter values and the data that the controller needs for the induction machine is imperative. Artificial Intelligence (AI) is a helpful tool to achieve this. The summary will also present an overview of different ANN-based drive approaches.

Dual-Phase Lock-In Amplifier Based on FPGA for Low-Frequencies Experiments

Photothermal techniques allow the detection of characteristics of material without invading it. Researchers have developed hardware for some specific Phase and Amplitude detection (Lock-In Function) applications, eliminating space and unnecessary electronic functions, among others. This work shows the development of a Digital Lock-In Amplifier based on a Field Programmable Gate Array (FPGA) for low-frequency applications. This system allows selecting and generating the appropriated frequency depending on the kind of experiment or material studied. The results show good frequency stability in the order of 1.0 × 10−9 Hz, which is considered good linearity and repeatability response for the most common Laboratory Amplitude and Phase Shift detection devices, with a low error and standard deviation.

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

Application of morphological connected openings and levelings on magnetic resonance images of the brain

In this article, several advanced connected transformations from mathematical morphology for computational neuroanatomy applications are developed. In particular, brain is separated from the skull in MRI T1 using morphological connected openings. The use of connected transformations allow the preservation of regions, without introduce new information. As a result, the segmented brains preserve by complete information of the original images being more reliable for the specialist who deals with information such as white and gray matter.

Indirect Field Oriented Control of an Induction Motor Sensing DC-link Current

This paper describes an analysis method for achieving control torque and speed with vector control for induction motors. An indirect field-oriented output feedback motor controller is presented; it is suitable for low-cost applications. A current model control is used to sense back electromotive force (back-EMF) by means of an analog to digital converter (ADC); its simulation and filtering are discussed. A Current model is the core of this work, but other system modules are analyzed such the proportional-integrative (PI) controller, the space vector with pulse width modulation (SVPWM), and others. Their implementations on a digital signal processor (DSP) along with the electrical power stage are shown. The cascaded structure of the controller allows performing a constructive tuning procedure for position and speed control loop.

Design and Construction of a Didactic 3-DOF Parallel Links Robot Station with a 1-DOF Gripper

The main objective of the construction of a robot station presented in this article is to allow the students to design andproduce a feasible-to-build mechatronic device using robust, low-cost components. It is a tool for students to gainexperience integrating different mechatronic fields of knowledge, as well as practicing the procedures needed tosuccessfully accomplish their own design. The project starts by describing the target requirements to be achieved bythe prototype robot, these requirements will serve as the guideline for the design and further manufacture and testingof the system. The sub-assemblies of the mechanism are analyzed, main technical areas and their processes arediscussed individually emphasizing the methods and materials used, then results are presented along with somepractical recommendations to extend the scope of the project and improve the performance of the prototype robot. Ithas been especially important to maintain the didactical approach and design the platform with affordable componentsthat can be easily obtained; this is also true for the tools and software used. The article is also intended to introducethe student to industrial design methodology, allowing for different manufacturing processes and robot architectures tobe incorporated for the specific scope of the project and the available tools and facilities.

An Approach to Motion Control Applications Based on Advanced Programmable Devices

In this article a methodology for constructing a simple servo loop for motion control applications which is suitable for educational applications is presented. The entire hardware implementation is demonstrated, focusing on a microcontroller-based (μC) servo amplifier and a field programmable gate array-digital signal processor (FPGA-DSP) motion controller. A novel hybrid architecture-based digital stage is featured providing a low-cost servo drive and a high performance controller, which can be used as a basis for an industrial application. Communication between the computer and the controller is exploited in this project in order to perform a simultaneous adaptive servo tuning. The USB protocol has been put into operation in the user front-end because a high speed sampling frequency is required for the PC to acquire position feedback signals. A software interface is developed using educational software, enabling features not only limited to a motion profile but also the supervisory control and data acquisition (SCADA) topology of the system. A classical proportional-integral-derivative controller (PID) is programmed on a DSP in order to ensure a proper tracking of the reference at both low and high speeds in a d.c. motor. Furthermore, certain blocks are embedded on an FPGA. As a result, three of the most important technologies in signal processing are featured, permitting engineering students to understand several concepts covered in theoretical courses.

A project-oriented approach for power electronics and motor drive courses

Power electronics and motor drives are major topics covered in undergraduate electrical engineering courses. Nevertheless, current teaching methods are usually based on intensive mathematical analysis, which can be difficult for students to understand but mainly to apply. This article provides ideas and practical experiences of a project-oriented approach implemented in power electronics and motor drives courses at the Automation and Control Department of the Universidad Autónoma de Querétaro, Querétaro, México. By using a microcontroller-based motor drive and a more practical approach in class, it is possible to introduce students to these courses in a more attractive and efficient way. The results presented prove that this methodology improves student competency, increases motivation and promotes teamwork in such technical courses.