Inertial sensors in the stabilization system of the balancing vehicle

The article presents the possibilities of using popular MEMS inertial sensors in the object tilt angle estimation system and in the system for stabilizing the vertical position of the balancing robot. Two research models were built to conduct the experiment. The models use microcontroller development board of the STM32F3 series with the Cortex-M4 core, equipped with a three-axis accelerometer, magnetometer and gyroscope. To determine the accuracy of the angle estimation, comparative tests with a pulse encoder were performed

Proteus II: design and evaluation of an integrated power-efficient underwater sensor node

We describe the design and evaluation of an integrated low-cost underwater sensor node designed for reconfigurability, allowing continuous operation on a relatively small rechargeable battery for one month. The node uses a host CPU for the network protocols and processing sensor data and a separate CPU performs signal processing for the ultrasonic acoustic software-defined Modulator/Demodulator (MODEM). A Frequency Shift Keying- (FSK-) based modulation scheme with configurable symbol rates, Hamming error correction, and Time-of-Arrival (ToA) estimation for underwater positioning is implemented. The onboard sensors, an accelerometer and a temperature sensor, can be used to measure basic environmental parameters; additional internal and external sensors are supported through industry-standard interfaces (I2C, SPI, and RS232) and an Analog to Digital Converter (ADC) for analog peripherals. A 433 MHz radio can be used when the node is deployed at the surface. Tests were performed to validate the low-power operation. Moreover the acoustic communication range and performance and ToA capabilities were evaluated. Results show that the node achieves the one-month lifetime, is able to perform communication in highly reflective environments, and performs ToA estimation with an accuracy of about 1-2 meters

Optimized Biosignals Processing Algorithms for New Designs of Human Machine Interfaces on Parallel Ultra-Low Power Architectures

The aim of this dissertation is to explore Human Machine Interfaces (HMIs) in a variety of biomedical scenarios. The research addresses typical challenges in wearable and implantable devices for diagnostic, monitoring, and prosthetic purposes, suggesting a methodology for tailoring such applications to cutting edge embedded architectures. The main challenge is the enhancement of high-level applications, also introducing Machine Learning (ML) algorithms, using parallel programming and specialized hardware to improve the performance. The majority of these algorithms are computationally intensive, posing significant challenges for the deployment on embedded devices, which have several limitations in term of memory size, maximum operative frequency, and battery duration. The proposed solutions take advantage of a Parallel Ultra-Low Power (PULP) architecture, enhancing the elaboration on specific target architectures, heavily optimizing the execution, exploiting software and hardware resources. The thesis starts by describing a methodology that can be considered a guideline to efficiently implement algorithms on embedded architectures. This is followed by several case studies in the biomedical field, starting with the analysis of a Hand Gesture Recognition, based on the Hyperdimensional Computing algorithm, which allows performing a fast on-chip re-training, and a comparison with the state-of-the-art Support Vector Machine (SVM); then a Brain Machine Interface (BCI) to detect the respond of the brain to a visual stimulus follows in the manuscript. Furthermore, a seizure detection application is also presented, exploring different solutions for the dimensionality reduction of the input signals. The last part is dedicated to an exploration of typical modules for the development of optimized ECG-based applications

Infrared video tracking of UAVs: Guided landing in the absence of GPS signals

Master's Project (M.S.) University of Alaska Fairbanks, 2019Unmanned Aerial Vehicles (UAVs) use Global Positioning System (GPS) signals to determine their position for automated flight. The GPS signals require an unobstructed view of the sky in order to obtain position information. When inside without a clear view of the sky, such as in a building or mine, other methods are necessary to obtain the relative position of the UAV. For obstacle avoidance a LIDAR/SONAR system is sufficient to ensure automated flight, but for precision landing the LIDAR/SONAR system is insufficient for effectively identifying the location of the landing platform and providing flight control inputs to guide the UAV to the landing platform. This project was developed in order to solve this problem by creating a guidance system utilizing an infrared (IR) camera to track an IR LED and blue LEDs mounted on the UAV from a RaspberryPI 3 Model B+. The RaspberryPI, using OpenCV libraries, can effectively track the position of the LED lights mounted on the UAV, determine rotational and lateral corrections based on this tracking, and, using Dronekit-Python libraries, command the UAV to position itself and land on the platform of the Husky UGV (Unmanned Ground Vehicle)

NRF52-piirisarjaan perustuva elektroninen ohjausjärjestelmän kehitysalusta

Aim of the thesis was to develop and build an embedded hardware device that utilizes a SoC from the Nordic Semiconductor nRF52-series. The purpose was to create a modular platform that would be capable of controlling later developed control system applications. The selected example application was a heating control system for a small scale wood chip burning water boiler. The nRF52-series devices are SoC’s with integrated 2.4 GHz radio modules, which are intended for implementing low bandwidth wireless networks such as BLE or ANT+. The devices have a ARM Cortex-M4 processors integrated to a set of peripheral devices. The processors are capable of running both application code and wireless networks stacks in the same device, which makes them fully integrated wireless SoC solutions. In the platform the radio is planned to be used for extending the user interface as well as connecting additional devices such as sensors. However, the content of the thesis is solely focused on developing and implementing hardware part of the design. The hardware developed in the thesis is a modular three board design. Consisting of one main board with the SoC and two auxiliary boards with connection interfaces to the application. The boards are supplied from mains network and can control three mains powered devices with duplicated switches for safety. When mains network is not available, the device operates from a integrated li-ion battery which keeps non-mains related features working from several hours to multiple days. Other main features include a BLE radio, USB serial interface, battery charger and a configurable interface for thermocouples and resistive temperature sensors. Additionally the device has a user interface consisting of a LED-array, two digit 7-segment display, buzzer, buttons and a motorized potentiometer. Design decisions, implementation and some operational theory are covered in the theoretical part of the thesis. In the practical part of the thesis, all features of the three boards were designed as well as a schematic and layout of the boards were drawn. Component sourcing, board assembly and reflow soldering were also done within the thesis. All boards were designed to fit in a off-the-self enclosure with custom designed and manufactured front panel serving as the user interface. The work done during the thesis covers a full electronic hardware device development process and resulted in an actual devices that can be used to control applications such as the boiler heating system

Embedded Controller Design for Mechatronics System

Many mechatronic systems have challenging control difficulties due to the high nonlinear structures and time‐varying dynamic behaviors. In addition to these, there are external disturbances, which cannot be predicted and change according to uncontrolled working environments. Conventional controllers are insufficient to solve the aforementioned problems and to compensate the environmental disturbances. Therefore, adaptive controllers have been proposed as a solution to these inefficiencies of conventional controllers. Adaptive control is applied for solving the control problem of the mechatronic sun tracker that ensures the movement of the mechanism to harvest maximum energy coming from solar to the PV module surface during the sunshine duration. For this type of control problems, conventional controllers are very limited and they have a lot of deficiencies. The adaptive mechanism governed by an adaptation law is the heart of any adaptive controller. We establish the adaptation law for the plant control system using Lyapunov stability theory. This adaptation law is precise for a generic second‐order system; hence, it is obviously applicable for adaptive control of other second‐order systems in different realms, such as industrial production system, military, and robotics

Microcontroller based control system with flexible configuration

The paper is aimed at description of the developed microcontroller based control system with flexible configuration allowing very simple implementation in many control tasks. It consist of the central module equipped with 32bit microcontroller MK60DN512 by NXP Semiconductor and input/ output modules for interfacing central module to the controlled process. Central module consists of two boards connected together – mainboard and microcontroller daughter board. Daughter board provides all the necessary microcontroller’s signals on the two 2-row 40pin headers and complete Ethernet communication interface. Mainboard provides to the daughter board 5V stabilized power supply and all necessary peripherals – SDHC card slot, RS232 and RS485 communication interfaces. RS232 is used for communication with smart sensors for instance; RS485 is especially used for high speed interconnection with up to 15 expansion peripheral modules. Control system is programmable in C language using any compatible IDE – NXP Kinetis Design Studio, for example. For this purpose support program libraries including necessary routines for control and monitoring tasks were created. © 2018, Danube Adria Association for Automation and Manufacturing, DAAAM. All rights reserved

Computationally Efficient Self-Tuning Controller for DC-DC Switch Mode Power Converters Based on Partial Update Kalman Filter

In this paper, a partial update Kalman Filter (PUKF) is presented for the real-time parameter estimation of a DC-DC switch-mode power converter (SMPC). The proposed estimation algorithm is based on a novel combination between the classical Kalman filter and an M-Max partial adaptive filtering technique. The proposed PUKF offers a significant reduction in computational effort compared to the conventional implementation of the Kalman Filter (KF), with 50% less arithmetic operations. Furthermore, the PUKF retains comparable overall performance to the classical KF. To demonstrate an efficient and cost effective explicit self-tuning controller, the proposed estimation algorithm (PUKF) is embedded with a Bányász/Keviczky PID controller to generate a new computationally light self-tuning controller. Experimental and simulation results clearly show the superior dynamic performance of the explicit self-tuning control system compared to a conventional pole placement design based on a pre-calculated average model