ARM-based Microcontrollers Research Articles

Stable Rules Definition for Fuzzy TS Speed Controller Implemented for BLDC Motor

This paper deals with the application of a fuzzy-logic-based controller for a drive with a BLDC motor. Two main aspects of the work are presented in this paper. The first of them is focused on the design process of the fuzzy model. For this purpose, the rules of the applied fuzzy system are defined according to the Lyapunov function. The gain coefficients of the controller are optimized using the Chameleon Swarm Algorithm. Various issues and aspects were analyzed in the simulation tests (robustness against parameter changes, the influence of the controller parameters on the precision of control, stages of optimization, etc.). The presented work confirms the assumptions regarding precision and stable operation (also in the presence of changes in the object parameters—the mechanical time constants of the engine) in connection with the applied fuzzy speed controller. Moreover, the second part of the manuscript presents the low-cost power electronic device developed for laboratory tests. It uses STM32 ARM-based microcontrollers (state variable measurement, control algorithm calculation, control signal generation) and a Raspberry Pi 4B microcomputer (control application—reference value and parameter definition). The experiment performed for the control structure—an electric drive with a BLDC motor—verified the theoretical considerations.

Comparison of processing speed between Arduino Due and Teensy 3.6 boards in a system identification application

The system identification technique is a powerful real-time signal processing tool when dealing with the characterization of dynamic systems. This approach uses adaptive filtering techniques and the least mean square (LMS) algorithm to estimate the impulse response of a system in a finite impulse response (FIR) filter format. The main purpose of this paper is to compare the results and processing speed of two ARM-based microcontrollers as well as to give a theoretical background and an implementation procedure of the technique. ARM (Advanced RISC Machine) is an architecture of 32-bit processors usually applied in embedded systems due to its processing power, relatively low consumption, cost and small size. The impulse responses obtained by the method for several passive electronic filters were transformed to the frequency domain and compared with simulations of the circuits' frequency responses. This practice was repeated for both boards and for different parameters of the algorithm. The results have shown that the Arduino Due was unable to deal with higher sampling frequencies due to its processor limitations. On the other hand, the Teensy 3.6, a more powerful controller, yields great results even for higher frequencies.

Design and Construction of A Laser-Based Respiratory Gating System For Implementation of Deep Inspiration Breathe Hold Technique in Radiotherapy Clinics.

Background:Deep inspiration breath-hold (DIBH) is known as a radiotherapy method for the treatment of patients with left-sided breast cancer. In this method, patient is under exposure only while he/she is at the end of a deep inspiration cycle and holds his/her breath. In this situation, the volume of the lung tissue is enhanced and the heart tissue is pushed away from the treating breast. Therefore, heart dose of these patients, using DIBH, experiences a considerable decline compared to free breathing treatment. There are a few commercialized systems for implementation of DIBH in invasive or noninvasive manners.Methods:We present a novel constructed noninvasive DIBH device relied on a manufacturing near-field laser distance meter. This in-house constructed system is composed of a CD22-100AM122 laser sensor combined with a data acquisition system for monitoring the breathing curve. Qt Creator (a cross-platform JavaScript, QML, and C++-integrated development environment that is part of the SDK for development of the Qt Graphical User Interface application framework) and Keil MDK-ARM (a programming software where users can write in C and C++ and assemble for ARM-based microcontrollers) are used for composing computer and microcontroller programs, respectively.Results:This system could be mounted in treatment or computed tomography (CT) room at suitable cost; it is also easy to use and needs a little training for personnel and patients. The system can assess the location of chest wall or abdomen in real time with high precision and frequency. The performance of CD22-100AM122 demonstrates promise for respiratory monitoring for its fast sampling rate as well as high precision. It can also deliver reasonable spatial and temporal accuracy. The patient observes his/her breathing waveform through a 7” 1024 × 600 liquid crystal display and gets some instructions during treatment and CT sessions by an exploited algorithm called “interaction scenario” in this study. The system is also noninvasive and well sustainable for patients.Conclusions:The constructed system has true real-time operation and is rapid enough for delivering clear contiguous monitoring. In addition, in this system, we have provided an interaction scenario option between patient and CT or Linac operator. In addition, the constructed system has the capability of sending triggers for turning on and off CT or Linac facilities. In this concern, the system has the superiority of combining a plenty of characteristics.

In situ image processing capabilities of ARM-based micro-controllers

Dealing with visual data is the key for environmental monitoring tasks in Wireless Multimedia Sensor Networks (WMSNs). Tasks such as object detection, recognition, and/or tracking do require extracting and using the right information from the inherently large amount of visual data. The widely accepted solution of legacy WSNs, transmitting the acquired data to a central base station for further processing, would render a WMSN totally useless because of the unacceptable use of bandwidth and energy. Therefore, we consider the in situ processing as a viable solution for WMSNs. However, processing power and memory capacity restrictions of existing multimedia sensor nodes along with their power consumption are the limiting factors for wide-spread use of in situ processing. Nevertheless, recent technological improvements and introduction of the new ARM cores encourage us to evaluate the image processing capabilities of ARM7/ARM9/ARM11 based micro-controllers for in situ processing in WMSNs. In this work, we first discussed the architectural design differences among the various ARM cores. Then we classified image processing algorithms into three categories. Then, we evaluated the performance of each microcontroller by running a set of basic image processing algorithms necessary for object detection, recognition, and/or tracking. The test results show that ARM11 runs up to 6---30 times faster than ARM9 and ARM7, respectively. Besides, ARM11 consumes up to 5---7 times less energy than ARM9 and ARM7 for the same type of operations.