Mechatronics education systems through sensing and control design

Summary form only given, as follows. The presentation will go over motor drive fundamentals including dc motor control and ac induction motor control. In general, the motor drive includes two control loops: (1) speed and (2) current. The speed loop normally deals with field and torque commands, and the current loop is to control the instantaneous armature current. Such a general motor drive control concept is applicable to both dc and ac motors. With understanding of dc motor speed control, the rationale for the need of ac motor vector control will be derived. Different vector control methods will be explained using the decoupled equivalent circuits. In terms of current control, both dc and ac motors need the so-called pulse-width-modulated (PWM) converters or inverters to regulate the current. Different PWM techniques will be explained in this presentation. Finally the PWM inverter related motor drive issues will be addressed.

Los controladores de carga son implementados en varios sistemas electrónicos con el objetivo de proteger y controlar la carga y descarga de una batería; en el caso de los controladores utilizados en sistemas fotovoltaicos autónomos se implementan dos tipos de tecnologías, Pulse Width Modulation (PWM) y Maximum Power Point Tracking (MPPT). En este artículo se compararon dos controladores de carga con diseños originales en sistemas fotovoltaicos con las mismas especificaciones técnicas para determinar el comportamiento de cada uno bajo condiciones ambientales similares. La implementación de ambos controladores de carga se basó en software y hardware con diseños originales, utilizando tecnología PWM y MPPT. Ambos sistemas están compuestos por el controlador de carga, un panel solar de 30 W y una batería de 12 V a 18 Ah; se realizaron las pruebas experimentales de ambos controladores midiendo voltaje y corriente en el panel y en la batería en procesos de carga y descarga, observando que el controlador MPPT tiene una eficiencia promedio mayor que el controlador PWM debido a que el tipo de tecnología implementada influye directamente en la eficiencia, incluso ante valores menos favorables de radiación solar y temperatura ambiente. El controlador PWM es una opción de eficiencia aceptable y además de bajo costo respecto al controlador MPPT. En la implementación de ambos controladores se calcularon tiempos de autonomía similares.

In this paper, a pulse width modulation (PWM) control approach to speed trackong control is developed for the three-phase induction motor in electric vehicles.The PWM technique is amployed to design controllers.By incorporating the three-phase bridge recifier into the motor based on the PWM technique ,the PWM control approach is developed.The proposed control method is able to overcome the disadvatage of the motor in the traditional design procedure.In addition,it is proved that the tracking error converges to a small neighborhood of the all origin and all the closed-loop signals are bounded.The results of the MATLAB simulation illustrate the effectiveness of the proposed approach.

This paper describes the design of low-cost DC motor controller for use by robot hobbyists. The motor controller created by this project has a profound impact on the robot hobbyist arena by creating a product that performs far beyond its expectations This is due to the fact that this motor controller will drive two independent DC motors with the same functionality found in a high-end single motor controller, and cost only $30 to build. Testing has shown that the hardware platform designed and created by this project is capable of performing all the functionality of a high-end motor controller while controlling two DC motors. The software is user-friendlier than any other motor controller currently available.

The article considers the problem of the DC motors control that are often used in many electric drive systems. Due to the progress of industrial electronics and technology it has become possible to develop more efficient motor control circuits. The conventional speed control methods commit power losses in the system, which can be minimized by using the power electronics strategy. There is considered the thyristor control of DC motors of the ship electric drive. The DC motor control systems are described and simulation models in the MATLAB Simulink program are presented. The thyristor methods for controlling a DC motor speed are listed: single-phase semi-controlled converter (for motors with power up to 15 kW); single-phase drive with a controlled converter (available to operate in two quadrants); three-phase semi-controlled converter; three-phase controlled converter; single-phase reverse converter realized by connecting two single-phase converters (ensuring multi-mode operation); three-phase reverse converter realized as a single-phase converter. The mechanical characteristic of a DC motor was illustrated when the voltage supplied to the armature winding changed. It has been stated that control of the armature voltage is more favorable for speeds below the rated speed; flow control is preferable for speeds above the nominal speed. It has been inferred that speed control by means of power electronics devices provides large energy savings, in contrast to the traditional speed control methods, since the traditional methods experience significant energy losses.

Eddy dynamometer is widely used in drive motor and ICE's character testing, in which it can't be loaded large torque under lower speed, and can't drag testing motor, and its dynamic response is weak .Also it changes mechanical energy to heat energy, which wastes energy resource. In this paper, a new kind of electric dynamometer based on separate-excited DC generator is introduced to overcome these shortcomings, which realizes large load torque under lower speed, and can measure motor's characters in four quadrants, and has quick dynamic response ability. The electric dynamometer can work in steady speed mode, steady torque mode and steady power mode. It can not only measure motor steady character, but also dynamic character. In this paper, the whole system hardware framework and software will be introduced. DC motor's control method is introduced in detail. At last, experiment results will be shown on.

Development and performance assessment of a DC electric variable-rate controller for use on grain drills

A generalized DC model for constant frequency control of Class-D converters is presented. Based on the Class-D converter with a variable capacitance switch (VCS), a generalized DC model including some losses is found from its steady-state operation waveforms by Fourier analysis. The duty ratio of the power switches is retained as an explicit parameter in the model, which makes the model also useful for pulse width modulation (PWM) control. It is found that VCS control allows a much wider range of output voltage variation than PWM control. Moreover, by small-signal perturbation of the DC model, the AC models for low frequency control- and line-to-output responses can also be obtained. An experimental Class-D converter with a VCS operating at 350 kHz is implemented to verify the derived equations.

Solar energy a sustainable energy system can have several applications, one of them can be focused on photovoltaic solar cookers. The objective of the research was to determine the solar irradiation and implement a pulse width modulation (PWM) control system for a photovoltaic solar cooker in the Peruvian highlands. First, the solar irradiation of the Peruvian highlands was determined on sunny and rainy days, to implement a photovoltaic solar cooker controlled by a programmable logic controller (PLC), with PWM programming instruction. The results of solar irradiation on sunny days are uniform with a maximum value of 1075 W/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and on rainy days it is very irregular with drops of up to 100 W/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , the photovoltaic solar cooker through PWM control is 23% more efficient that a conventional electric kitchen, however, supplying only photovoltaic solar energy, saves 100% of the electric energy, being a sustainable system.

The DC motors an outstanding portion of apparatus in automotive and automation industrial applications requiring variable speed and load characteristics due to its ease of controllability. Creating an interface control system for multi DC motor drive operations with centralized speed control, from small-scale models to large industrial applications much demand. By using Lab VIEW (laboratory virtual instrument engineering workbench) as the motor controller, can control a DC motor for multiple purposes using single software environment. The aim of this paper is to propose the centralized speed control of DC motor using Lab VIEW. Here, the Lab VIEW is used for simulating the motor, whereas the input armature voltage of the DC motor is controlled using a virtual Knob in Lab VIEW software. The hardware part of the system (DC motor) and the software (in personal computer) are interfaced using a data acquisition card (DAQ) -Model PCI- 6024E. The voltage and Speed response is obtained using LABVIEW software. Using this software, group of motors’ speed can be controlled from different location using remote telemetry. The propose work also focuses on controlling the speed of the individual DC motor using PWM scheme (Duty cycle based Square wave generation) and DAQ. Help of the DAQ along with Lab VIEW front panel window, the DC motor speed and directions can be change easily in remote way. In order to test the proposed system the laboratory model for an 80W DC motor group (multi drive) is developed for different angular displacements and directions of the motor. The simulation model and experimental results conforms the advantages and robustness of the proposed centralized speed control.

1. This research aims to study the edge computing devices with a faster processing and signal connecting function based on development of the physical layer and magnetic sensing devices. It is important matter for smart robot in multi-axis motor control. Based on the variable robot properties, it includes humanoid robots, wheeled machines, and fixed robots, respectively, are contented. This research is constructed as follows: to establishing an edge computing device system, the image vision system with neural-network learning theory to control robot arm path, multiple magnetic sensors in physical layer to analyze the signals of the motor, voltage, current, temperature, etc., are transmitted signal to the edge computing device and IoTs computing server system.2. IntroductionThe Industry 4.0 concept represents the trend of data exchange and automation in the manufacturing industry. It is defined by cloud computing, cyber-physical systems and the IoTs. In Industry 4.0, computers and automation technologies are integrated with robots and their components [1,2]. These robots and other components are remotely connected to a computer system, and the computer system is equipped with algorithms that can control and learning robots with minimal human intervention. For the motor device, the robot composes the control of the DC motor and relate to the accessories vital role. However, there are many factors that can misguide the controller's work, to make an unable to accurately control and/or have the desired dynamic behavior. For example, the resistance (Ohmic) of the coil winding of the motor is changed due to the temperature is different. If the vibration level is high and the wear of the rotor ball bearing becomes larger, the friction coefficient will also be affected. Therefore, the cloud computing environment of industrial factories, a continuous processing is required to re-evaluate the precise values of motor parameters and update the corresponding controller settings. In addition, it should be noted that the torque and speed sensors of the motor must have the correct selection to assist for achieving the correctness of the program.3. Theory and methods: multi-axis motor sensing and visual images of robotic armsCollaborative robots focus on intelligent motor control. Based on this construction, multiple sensor component signals are added. The physical information such as voltage, current, vibration, electric heating, magnetic flux sensing, and motor position is diagnosed through integrated control. This study, the artificial intelligent motor with the sensing signals, is used to control motor speed, positioning, constant horsepower, constant torque, force feedback, vibration resistance, overheating, overload, and instantaneous short circuit, as shown in Figure 1. The electromagnetic control of this paper is as follows:A. Single robotic arm function automation: Directly control the robot motor, at the same time, it has higher precision and speed to perform specific tasks repeatedly, but most of them cannot clearly actuate without an electromagnetic sensor.B. Part of the arm automation: It assists decision-making through environmental sensing input signals. In this study, robots use vision and sensors to determine the decision-making process, which is not easy to deal with accidental arm interference.C. Conditional autonomous robot: Control the arm according to the environmental monitoring behavior, but the external server can operate in real time.D. Highly autonomous robot: an environment that needs to be defined in an area or any situation without human operation.4. Experimental results and discussionBased on the motor control of intelligent robots, this research proposes a better and faster algorithm structure, which is a neural network-like combined with particle swarm method, which is used to calculate the convergence result of a lower loss function, which can accurately control the motor parameters and combine the IoTs, as shown in Figure 2. First, the robotic arm establishes multi-input sensing values, using the above algorithm to evaluate the robotic arm motor parameters, the prevention of interference from peripheral physical sensing, and the signal processing of external visual images. The issues raised based on past research experience include:(1) Establish edge and fog calculations to control the voltage and current of the motor, (2) establish neural network algorithm to calculate motor parameter, (3) construct the image vision system, (4) establish a smart robot platform, including wheel-shaped and human-shaped robots as experiments, which uses the above-mentioned deep learning theory to construct the test of the robot's motor motion and signal transmission response, (5) to use the multiple sensors, motor electromagnetic signals, piezoelectric sensors, and load signals, as the force feedback of the robot to calculate and judge. Finally, (6) to integrate the edge computing of the sensing layer, the fog computing of the signal processing layer, and faster computing layer through the IoTs cloud server. The IoTs chip is to use the dual-core Linkit-7697 (Taiwan’s MediaTek Inc). The chip can perform as a cloud computing and remote device, which indeed meet the requires of providing multi-sensing force feedback for cooperative robot handling objects. **

This research proposes a training set of digital image processing using LabVIEW for object inspection topic. The collection consists of a conveyor set, digital camera, a robot arm, a training book, and 12 VDO clips. The conveyor base and frame are elaborately created by a 3D printer with PLA plastic. The conveyor which rotates circularly is driven by a dc motor. It is graphically controlled by LabVIEW, which interfaces with a microcontroller board and dc motor. A robot arm operates as a rejecting arm, pushing an unwanted object away from the conveyor. The inspection process employs a real-time USB camera and infrared light sensors incorporating a digital image processing algorithm. Additionally, the training book comprises of 12 chapters which match with 12 VDO clips combined as a learning set. A batch of VDO clips is published online through the YouTube channel. Content examples are color detection, object shape classification, motor control, reject arm control, and water level inspection. Details of each chapter are apparatus preparation, the graphically programming process, and GUI design. The 12 VDO clips are also added to the training package for self-study. A compact size and easiness to replicate and carry of conveyor set are the advantages of the training set. The training package was evaluated by 6 expert lecturers from the department of Teacher Training in Electrical Engineering, KMUTNB, with an average value of 4.30 from 5. The training set also is assessed by 26 students from the senior class. Finally, the evaluated results show that the training set can improve student's enthusiasm, and easy understanding and serve as encouragement.

High-resolution 3D printing, particularly electrohydrodynamic (EHD) printing, represents a transformative approach for advanced manufacturing applications, including wearable electronics, bioelectronics, and soft robotics. Despite its potential, EHD printing faces challenges such as complex waveform control, limited material compatibility, satellite droplet formation, and continuous charge accumulation. To address these issues, the use of pulse-width modulation (PWM) control is proposed to enhance EHD printing performance. The influence of duty cycles and pulse subdivisions on EHD printing was systematically investigated through experiments and simulations, analyzing their effects on jetting dynamics, droplet formation, charge accumulation, and line quality. The results demonstrate that PWM modulation significantly improves jetting stability, reduces droplet diameter by up to 25%, minimizes satellite droplet formation, and effectively mitigates charge accumulation. Furthermore, PWM control was shown to facilitate the production of high-quality patterns. Notably, the proposed PWM approach is compatible with existing waveform control setups, offering enhanced precision and stability without requiring substantial modifications. These findings underscore the potential of PWM-controlled EHD printing for achieving high-resolution, versatile manufacturing in electronics and functional device production.

Metallic joints are created in multivariable gas metal arc welding process by maintaining a balance between the quantum of heat generated and the feeding rate of electrode metal to the weld gap. The wire feeding control is often independently handled. The wire feeder unit should be simple, low cost, and capable of producing accurate speed. Arc welding controllers are often kept in clumsy conditions and the wire feeder unit is located close to the welder, could be much away from the controller. To reduce interconnections, separate sensing element for speed feedback should be avoided. Due to their negligible electrical and mechanical time constant, the pancake-type permanent magnet dc motor is suitable for wire feeding, where sensing of back electromotive force (EMF) for feedback is easy. When high frequency pulsewidth modulation (PWM) controller is used, the sensing of back EMF gets complicated. This paper explores the constraints on the choice of PWM frequency along with its maximum pulsewidth for different types of dc motors. It further elaborates comparatively on the choice of suitable control function for generating accurate speed control of wire feeding using back EMF as feedback. Finally, this paper also details the experimental results using the proposed control function.

This paper investigates a nonlinear speed control scheme for a brushless DC motor (BLDC) drive. In order to achieve high performance speed tracking, an adaptive backstepping controller is designed to obtain the reference voltage for the pulse width modulation (PWM) control which does not require the traditional PI controller. To regulate the dynamics of the drive system, the proposed controller is designed to track a desired linear reference model. With the proposed control scheme, The system possesses the advantages of good speed tracking performance and robustness to the parametric uncertainties and disturbance. The effectiveness of the proposed control scheme is verified by the simulation results.