Application of the Nucleo STM32 module in teaching microprocessor techniques in automatic control

Abstract

The paper presents the possibilities of using the Nucleo STM32F746 module as part of the microprocessor systems course during didactic classes in the field of automation and robotics. The components of the laboratory set and the STM32CubeIDE integrated development environment were discussed. The possibility of using the sets to illustrate the tasks like automatic determination of characteristics, FIR and IIR signal filtration and the implementation of the automatic control system has been shown.

Full text

PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 98 NR 10/202222 245
Tomasz MARCINIAK, Kacper PODBUCKI, Jakub SUDER
Poznan University of Technology, Institute of Automatic Control and Robotics, Division of Signal Processing and Electronic Systems
ORCID: 1. 0000-0001-6035-7325; 2. 0000-0001-8673-4037, 3. 0000-0002-3156-0639
doi:10.15199/48.2022.10.55
Application of the Nucleo STM32 module
in teaching microprocessor techniques in automatic control
Abstract. The paper presents the possibilities of using the Nucleo STM32F746 module as part of the microprocessor systems course during didactic
classes in the field of automation and robotics. The components of the laboratory set and the STM32CubeIDE integrated development environment
were discussed. The possibility of using the sets to illustrate the tasks like automatic determination of characteristics, FIR and IIR signal filtration and
the implementation of the automatic control system has been shown.
Streszczenie. W artykule przestawiono możliwości użycia modułu Nucleo STM32F746 w ramach przedmiotu systemy mikroprocesorowe podczas
zajęć dydaktycznych dla kierunku automatyka i robotyka. Omówiono elementy składowe zestawu laboratoryjnego oraz zintegrowane środowisko
programistyczne STM32CubeIDE. Pokazano możliwości wykorzystania zestawów do ilustracji zagadnień automatycznego wyznaczania
charakterystyk, filtracji sygnałów FIR i IIR oraz realizacji układu regulacji automatycznej. (Zastosowanie modułu Nucleo STM32 w nauczaniu
technik mikroprocesorowych w automatyce)
Keywords: STM32, Nucleo, microcontroller, automatic control system.
Słowa kluczowe: STM32, Nucleo, mikrokontroler, układ regulacji automatycznej.
Introduction
Manufacturers of microcontrollers offer relatively
inexpensive experimental modules that facilitate
familiarization with the functionality of a given
microcontroller and its programming techniques. Currently,
one of the popular solutions are the modules of the Arduino
family, in which the Arduino UNO with the ATmega328P
microcontroller is the most popular [1]. This solution allows
to quickly make a prototype of a simple control system, or
even a simple digital signal processing (DSP) system [2],
but the full use of the microcontroller is quite limited due to
the concept of the so-called Arduino bootloader and
because of the relatively simple IDE programming
environment without the possibility of debugging.
Due to the above limitations, a better solution are
experimental modules prepared by the company ST, which
has developed a number of modules called Discovery and
Nucleo for its microcontrollers. Discovery modules, apart
from the microcontroller, contain additional electronic
components [3]. An exemplary module is shown in Fig. 1.
Fig.1. Discovery STM32F429 and Nucleo STM32F746
Nucleo modules, designed in 32, 64 and 144 formats
(which is related to the number of I / O pins) typically do not
have any additional electronic components apart from the
microcontroller itself, and therefore their price is lower. A
characteristic feature of Nucleo is the ST-LINK / V2-1
programmer / debugger, which can be detached (broken
off) from the base board. These modules have connectors
with derived signals, including connectors of the Arduino
UNO standard. For Nucleo modules, PCB covers (so-called
shields) can be prepared, which may contain additional I / O
elements [4].
Techniques of using and programming STM32
microcontrollers are well presented in numerous tutorials
prepared by the ST company and manuals, including Polish
ones [5, 6, 7, 8].
Elements of the laboratory kit
For didactic activities, the Nucleo STM32F746 [9]
(Fig. 1) module can be used. The microcontroller is based
on the ARM® 32-bit Cortex®-M7 CPU core with a floating
point unit (FPU), has 1MB Flash memory and 320kB SRAM
memory and is equipped with a number of serial interfaces
(including I2C, UART, SPI), and, what is important from the
point of view of learning about DSP issues, both 12-bit
analog-to-digital converters (ADCs) and 12-bit digital-to-
analog converters (DACs).
Programming the Nucleo module can be performed
using the free STM32CubeIDE environment (Fig. 2), which,
using the STM32CubeMX graphic interface, supports the
configuration of the pins, individual devices of the
microcontroller and clocks (Fig. 3), enabling generation of
the initialization code.
Fig.2. STM32CubeIDE environment

246 PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 98 NR 10/2022
Fig.3. Graphical configuration of clocks in the STM32CubeMX
environment
In addition to the Nucleo module, during the laboratory
classes, additional modules and electronic components are
necessary, for example: the BH1750 light intensity sensor,
the BMP280 pressure and temperature sensor, the LM358
and LM386 operational amplifiers, 16 × 2 LCD displays with
an I2C converter, as well as auxiliary elements such as a
breadboard, rotary encoder, potentiometers, LED etc.
The first few laboratory classes are devoted to the basic
issues of programming techniques in the STM32CubeIDE
environment, data acquisition, control (e.g. PWM
generation) as well as archiving and visualization of
measurements.
An interesting possibility of the STM32CubeIDE
environment is the ability to analyze energy consumption
using the Power Consumption Calculator (Fig. 4), which
allows to accurately assess the energy demand of individual
microcontroller devices and shows which of them can be
turned off for savings.
Fig.4. An example of analysis using the Power Consumption
Calculator
The ability to use the laboratory set and the environment is
important in the following classes related to the
implementation of measurement and control systems,
digital signal processing algorithms and the preparation of
the didactic automatic control system. Examples of
laboratory exercises of such systems are presented in the
following chapters.
Determination of the photoresistor characteristics
The BH1750 light intensity sensor enables
measurements in the range of 1 - 65535 lx, and gives the
possibility of a determination of photoresistor sensitivity
characteristic. The block diagram of the measurement
system is shown in Fig. 5. The reference measurement,
carried out by the BH1750, is sent to the microcontroller via
the I2C interface. The tested photoresistor, in a divider
circuit with a resistor, e.g. 10 kΩ, is connected to the ADC
and should be placed close to the BH1750 module (Fig. 6).
The lighting intensity is changed by means of a white LED
controlled by a PWM signal. The measurement result, ADC
in relation to the lux value, can be observed using Serial
Wire Viewer in the STM32CubeIDE environment or sent via
UART to other visualization programs.
Fig.5. Block diagram of a system for determining the characteristics
of a photoresistor
Fig.6. BH1750 module and photoresistor illuminated with white LED
Implementation of digital filtration
Another issue discussed in the class is the presentation
of digital signal processing [10, 11]. As mentioned earlier,
the STM32F746 microcontroller has analog-to-digital and
digital-to-analog converters, which allows to easily build a
DSP system, the general concept of which is shown in
Fig. 7.
Fig.7. General concept of a digital signal processing system using
the Nucleo STM32F746
For the generation of analog test signals, a PC sound
card and software for generating sinusoidal signals (for
example https://www.szynalski.com/tone-generator/) can be
used. The voltage range from the sound card (± 1V) should
be adapted to the ADC input voltage range of the analog-to-
digital converter (voltage 0-3.3V). The LM358 op-amp can
be applied for this purpose. Figure 8 shows the schematic
and simulation of the input amplifier operation in the LT
Spice environment.
Nucleo
STM32
I2C
ADC Photoresistor
BH1750
LED
PWM
± 1
V
Nucleo
STM32
ADC1
(
PA 3
)
DAC1
(PA_4) RC filter
LM358
0-3.3 V
Waveform
generator
Oscilloscope

PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 98 NR 10/2022 247
Fig.8. An example of an input amplifier simulation made with the
use of LT Spice software
FIR or IIR digital filtration is programmed using the
STM32F746 microcontroller. An important element is the
correct setting of the ADC and DAC, including the correct
sampling rate.
The output signal from the DAC has the character of a
step function and a reconstructive filter is needed [12].
Observation of the analog signal can be done with an
oscilloscope, and if it is not available, an alternative is
computer sound card with oscilloscope visualization
software. Such solution has limitations related to the
frequency band (typically range up to 20 kHz), but it is
sufficient for teaching. An example of such software is
shown in Fig. 9, and its additional advantage is the FFT
analysis function.
During the course, students implement and analyze the
operation of the following filters:
 an averaging filter,
 a band-pass filter,
 IIR filters designed using impulse invariant or
bilinear transforms.
Fig.9. Oscilloscope using a PC sound card
(https://www.zeitnitz.eu/Scope_en)
The averaging filter (e.g. of length N = 5) is relatively
simple to implement and allows to get acquainted with the
signal attenuation process. Fig. 10 shows the frequency
response of the filter, which can be plotted with the freqz
command in Matlab or Octave-Online. A practical
assessment of the filter's operation can be made using a
generator and an oscilloscope. The input signal is reset for
two zeros, for example for 1600 Hz and 3200 Hz, assuming
a sampling rate of 8000 samples / second. Additionally, the
student can observe the phenomenon of aliasing.
In the next step, the student becomes familiar with the
design of FIR filters with given characteristics. The filter
coefficients can be determined by software, for example the
FDA Tool from the Matlab package [13]. On the Internet it is
also possible to find pages that allow automatic
determination of filter coefficients, an example is shown in
Fig. 11.
Fig.10. The frequency response of a filter of length N = 5 obtained
with the freqz command
Fig. 11. An example of designing a FIR filter on the page http://t-
filter.engineerjs.com/
The implementation of IIR filters consists in transforming the
transmittance of the analog filter to the form of the
transmittance of the digital filter, and then writing the
difference equation and its software. The impulse invariant
or bilinear transform are used to convert the analog
transmittance. Due to the nature of these transformations,
the obtained digital transmittances are different and the
frequency characteristics are also different [10].
Automatic control system
An interesting exercise, combining elements of the control
theory and the practical use of a microprocessor system, is
the construction and programming of a demonstration PID
temperature control system. The block diagram is shown in
Fig. 12.
Fig.12. Block diagram of the temperature control system
The student's task is to prepare a hardware and software
project that stabilizes the temperature with a specific
deviation (e.g. at the level of 5% or less of the control range
value). In addition, it is required to set a reference value by
means of serial communication or a rotary encoder as well
as the ability to observe the current value measured with
the STM Studio or Telemetry Viewer software and LED or
LCD display. An example of a controller circuit is shown in
Fig. 13. For temperature measurement, the DS18B20 or
Nucleo
STM32
I2C
PWM
Rotary encoder
BMP280 Resistor
TIM
I2C LCD 16x2
Transistor Power
supply
5 V / 0.2 A

248 PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 98 NR 10/2022
BMP280 sensors can be applied, which are characterized
by a relatively high measurement accuracy.
Fig.13. An example of a temperature controller system
Initial analysis of the system operation and
parameterization can be performed using the Matlab
environment based on the tutorial [14]. The Curve Fitting
Tool (Fig. 14) is helpful to determine the parameters of the
object from the step response, and the selection of the
controller settings is conveniently performed with the PID
Tuner tool (Fig. 15).
Fig.14. Determination of transmittance parameters using the Curve
Fitting Tool
Fig.15. Selection of controller settings by means of PID Tuner
As mentioned before, the stabilized temperature
measurement result can be observed using Serial Wire
Viewer in the STM32CubeIDE environment or sent via
UART to other visualization programs.
Conclusions
The STM32CubeIDE development environment facilitates
the preparation of a project for Nucleo and Discovery
prototype modules, and also allows to observe the real-time
operation of the designed systems and combine theory with
practice. The cost of the devices allows the student to use
the proposed solutions also outside laboratory classes at
home during a distance learning.
The presented, selected information on the
implementation of laboratory classes shows that at a
relatively low cost, it is possible to organize an introductory
course on signal control processing. The environment
should be supplemented with additional programs (both
paid and free alternative) enabling quick prototyping and
preparation of automatic control parameters.
This research was funded partly by the 2022 subvention
and partly with the SMART4ALL EU Horizon 2020 project,
Grant Agreement No 872614.
Authors: Tomasz Marciniak PhD, E-mail:
tomasz.marciniak@put.poznan.pl, Kacper Podbucki MSc, , E-mail:
kacper.podbucki@put.poznan.pl, Jakub Suder MSc, E-mail:
jakub.suder@put.poznan.pl, Poznan University of Technology,
Institute of Automatic Control and Robotics, Division of Signal
Processing and Electronic Systems, ul. Jana Pawła II 24, 60-965
Poznań, Poland.
REFERENCES
[1] Arduino Home, https://www.arduino.cc/ , access: 30.03.2022
[2] Marciniak T., Dąbrowski A., "Nauczanie zagadnień cyfrowego
przetwarzania sygnałów z zastosowaniem modułów z
mikrokontrolerem", Przegląd Elektrotechniczny, 94 (2018), nr 9,
125-127
[3] STM32 Discovery Kits, https://www.st.com/en/evaluation-
tools/stm32-discovery-kits.html#products, access: 30.03.2022
[4] Marciniak T., Dąbrowski A., Puchalski R., Dratwiak D.,
Marciniak W., Zastosowanie mikrokontrolera STM32F410 do
prezentacji zagadnień cyfrowego przetwarzania sygnałów,
Przegląd Elektrotechniczny, 95 (2019), nr 10, 118-120
[5] Szumski M., Mikrokontrolery STM32 w systemach sterowania i
regulacji, BTC, (2018)
[6] Galewski M., STM32. Aplikacje i ćwiczenia w języku C z
biblioteką HAL, BTC (2019)
[7] Kurczyk A., Mikrokontrolery STM32 dla początkujących, BTC
(2019)
[8] Paprocki K., Mikrokontrolery STM32 w praktyce, BTC (2009)
[9] STM32 Nucleo-144 development board with STM32F746ZG
MCU, supports Arduino, ST Zio and morpho connectivity,
https://www.st.com/en/evaluation-tools/nucleo-f746zg.html ,
access: 30.03.2022.
[10] Ünsalan C., Yücel M. E., Gürhan H. D., Digital Signal
Processing using Arm Cortex-M based Microcontrollers Theory
and Practice, Arm Education Media (2018)
[11] Marciniak T., Podbucki K., Suder J., Dąbrowski A., Analysis of
Digital Filtering with the Use of STM32 Family Microcontrollers.
In: Bartoszewicz A., Kabziński J., Kacprzyk J. (eds) Advanced,
Contemporary Control. Advances in Intelligent Systems and
Computing, Springer, Cham., (2020), vol 1196, 287-295
[12] Marciniak T, Cetnarowicz D., Pawłowski P., Dąbrowski A.,
Projektowanie filtrów analogowych do modułów cyfrowego
przetwarzania sygnałów, Przegląd Elektrotechniczny,95 (2019),
nr 10, 125-129
[13] Matlab, https://www.mathworks.com/products/matlab.html,
access: 30.03.2022
[14] Burn K, Cox C. A, hands-on approach to teaching system
identification using first-order plus dead time modelling of step
response data. The International Journal of Electrical
Engineering & Education, (2020);57(1), 24-40