DC Motor Speed Research Articles

Design of active disturbance rejection controller for the system with unknown model using Laguerre functions

This paper concentrates on the design problem of linear active disturbance rejection control (LADRC) for uncertain systems, whose order and parameters are unknown. In general, LADRC has diversified structural forms due to different order and parameters selection. To clarify the prerequisites for constructing the LADRC strategy, a Laguerre-based LADRC (LLADRC) method is proposed, which provides controller design guidance for systems with unknown models by capturing the impulse response. Then, intensive attention is focused on establishing internal stability conditions of the feedback system and parameter tuning rules of the prescribed controller. To gain a better understanding, the internal correlation between LLADRC and standard LADRC of the same order is analyzed. It is shown that observer and controller gains of the standard LADRC can be tuned via a workable LLADRC to achieve better control performance. Finally, a numerical example and an application design of DC motor speed control are studied, both of which demonstrate the feasibility and validity of the proposed method.

Design of Solar Electric Bicycle Based on Pulse Width Modulation on Throttle as DC Motor Speed Regulator

Electric bicycles are designed to use renewable energy to support the government's efforts to reduce carbon emission consumption. Problems in every region or city regarding fueled vehicles certainly increase air pollution. Generally, electric bicycles are designed to be a solution and are used in daily life to carry out daily activities by requiring a bicycle gas throttle control that can assist the driver or person in controlling the speed of the electric bicycle. In this study, designing a solar electric bicycle as environmentally friendly energy based on PWM signals to determine the duty cycle value or duty cycle with an optimized PWM value can affect the speed system (km / h) in Revolutions Per Minute (RPM) to determine the performance of the DC motor. The electric bicycle uses 30Wp solar power, two 12V 7.5 Ah batteries assembled in series, and a 24V 250W DC brushless motor. Based on the design results with a total weight of 37kg electric bicycle plus the weight of 55kg, 65kg, 75kg, and 85kg driver variations, the total controller power value is 163.44 watts. The results of duty cycle testing (duty cycle) were 25%, 50%, 75%, and 98%, with 249.9 as the maximum value of PWM and 9.8 Vout generated against the maximum speed of the electric bicycle of 2648 RPM or the equivalent of an electric bicycle speed of 18-28 km/hour. In this case, the electric bicycle is in a condition suitable for use to carry out daily activities by utilizing clean, cheap and appropriate energy

Efficient DC motor speed control using a novel multi-stage FOPD(1 + PI) controller optimized by the Pelican optimization algorithm.

This paper introduces a novel multi-stage FOPD(1 + PI) controller for DC motor speed control, optimized using the Pelican Optimization Algorithm (POA). Traditional PID controllers often fall short in handling the complex dynamics of DC motors, leading to suboptimal performance. Our proposed controller integrates fractional-order proportional-derivative (FOPD) and proportional-integral (PI) control actions, optimized via POA to achieve superior control performance. The effectiveness of the proposed controller is validated through rigorous simulations and experimental evaluations. Comparative analysis is conducted against conventional PID and fractional-order PID (FOPID) controllers, fine-tuned using metaheuristic algorithms such as atom search optimization (ASO), stochastic fractal search (SFS), grey wolf optimization (GWO), and sine-cosine algorithm (SCA). Quantitative results demonstrate that the FOPD(1 + PI) controller optimized by POA significantly enhances the dynamic response and stability of the DC motor. Key performance metrics show a reduction in rise time by 28%, settling time by 35%, and overshoot by 22%, while the steady-state error is minimized to 0.3%. The comparative analysis highlights the superior performance, faster response time, high accuracy, and robustness of the proposed controller in various operating conditions, consistently outperforming the PID and FOPID controllers optimized by other metaheuristic algorithms. In conclusion, the POA-optimized multi-stage FOPD(1 + PI) controller presents a significant advancement in DC motor speed control, offering a robust and efficient solution with substantial improvements in performance metrics. This innovative approach has the potential to enhance the efficiency and reliability of DC motor applications in industrial and automotive sectors.

Comparison Between Conventional PID Controller and Neural Network PID Controller Based on DC Motor Speed Control

DC motor is a multivariable, strong coupling and nonlinear controlled system, and is difficult to setting up the accurate mathematical model. So, it cannot achieve good control effect using traditional PID control method. To tackle this problem ANN based PID controller is proposed in this paper. The objective here is to compare the response of DC motor controlled by two different PID controllers.

Experimental implementation of Speed Stabilizer Based Field Oriented Control of Brushless DC Motor for Scooter Applications

An electric scooter, as one type of Lightweight vehicles technology, is a motorized vehicle designed for short-distance travel and recreational purposes. It is powered by an electric motor and typically has a rechargeable battery that provides sufficient power to operate the vehicle. Electric scooters are similar to traditional scooters but are much quieter, eco-friendly, and more energy-efficient. They are commonly used as an alternative mode of transportation for commuting, sightseeing, and recreational activities. This work presents an experimental implementation of speed stabilizer of electric scooter. In fact, a constant speed function might be required in a specific case in the operation of the scooter. A Field Oriented Control (FOC) method was chosen to control the speed of 3-phase Brushless DC motor of the scooter using a PIC16F873A Microcontroller through a Driver circuit. The control algorithm is designed to produce pulse width modulation (PWM) signal with the PID controller of the pulse bandwidth equipped with this Microcontroller and compared to the return pulse of the speed sensor in order to create and apply a closed back-feed system for good stability performance of scooter speed at different load values. The results obtained from this work show that the possibility of obtaining a wide range of control of the speed of the scooter at different loads with high reliability.

Analysis of the PID Controller Parameters for A Surface Mobility Platform Mobile Robot

Surface mobility control is a fundamental challenge in robotics, and its applications range from autonomous vehicles to industrial automation. The main aim of the paper is to analyze the PID controller parameters for the speed control of a surface mobility platform mobile robot. MATLAB simulation toolbox and mathematical model of the DC motor are used to find the optimal PID controller parameters to complete the DC motor speed control system. For the SMP motion control system, the mobile robot kinematic model is supported as a differential drive system. In this paper, the PID controller parameters for the DC motor control system are analyzed with simulation results using various KP, KI, KD gains. The experimental results of the SMP mobile robot with optimal PID controller parameters are analyzed by driving on the rough, slope and even terrains. According to simulation results and experimental tests, the proposed system effectively controls the speed of the SMP mobile robot, demonstrating satisfactory performance in settling time, rise time, and system overshoot. Among PI and PID controllers, the designed PID controller can quickly control to reach the desired DC motor speed. Using the optimal PID coefficient parameters, all motors reached their desired speed in 0.12 seconds during simulations. In the experimental tests on various terrain (even, slope and rough), all motors achieved their desired speed simultaneously within 25 seconds.Keywords: Differential drive, PID controller, motion trajectory, real-time speed control. skid steering, SMP mobile robot, surface mobility control

DC motor speed control using various Technology Controllers. Review

DC motor speed control using various Technology Controllers. Review

A comparative study between PI, PD and PID controllers to control motor speed

DC Motors are widely used in industries for various purposes. Many situations demand changes in the speed of the DC Motor, and this makes necessity to develop a method to effectively control the speed of DC motor. There are conventional and digital controller types, Proportional Integral (PI), Proportional Derivative (PD), and Proportional Integral Derivative (PID) used to control speed of the DC motor. In this project PI, PD and PID is modeling and simulated in MATLAB SIMULINK to control speed of the DC Motor. Aforementioned Controllers analyzed and evaluated on four terms overshoot, rise time, steady state error and settling time, the purpose of the evaluation to find the best performance to control the speed of DC motor. As a result of this, PID is the best controller due to it is improved performance when compared with others controllers.

DC motor speed control using boost converter DC-DC chopper type based on the PID controller

Abstract The boost converter with PID-based control is designed to be able to control the speed of the DC motor. In particular, the boost converter based on the PID able to produce output from the control process that is more intelligent, efficient and effective in maintaining the stability of the DC motor rotation. From the results, It can shows the difference and effect of output when using only boost converter and when implemented with PID control. The motor control is carried out with different torque conditions. The expected result is controlling the motor speed by the boost converter based on the PID and its performance at the time of starting as well as to changes in the reference speed of rotation and load according to the set point. From the experiment, it was found that the boost converter can increase the voltage according to changes in load torque and PID control can eliminate overshoot on the system and can reach the reference speed quickly, it only takes 1 second. Based on the data analysis that has been conducted, it can be concluded that the boost converter with PID controller functions quite well to regulate the DC motor speed to remain at the reference speed.

Performance evaluation of BLDC motor drive mounted in aerial vehicle (drone) using adaptive neuro-fuzzy

The development of autonomous drones equipped with cameras and various sensors has paved the way for their application in agriculture and perimeter security. These aerial drones require specific power, acceleration, high torque, and efficiency to meet the demands of agricultural tasks, utilizing built-in brushless DC (BLDC) motors. However, a common challenge drone’s face is maintaining the desired speed for extended periods. Enhancing the performance of BLDC motors through advanced controllers is crucial to address this issue. This research paper proposes optimizing the size and speed of brushless DC motors for aerial vehicles using an adaptive fuzzy inference system and supervised learning techniques. When these drones carry loads, the BLDC motors must dynamically adjust the drone's speed. During this phase, the motors must control their speed and torque using artificial intelligence controllers like adaptive neuro-fuzzy inference systems (ANFIS) to enhance the drone's functionality, resilience, and safety. This research has conducted analyses focused on improving the performance of BLDC motors explicitly personalized for unmanned aerial vehicle (UAVs). The proposed method will be implemented using MATLAB/Simulink, expecting to significantly enhance the BLDC motor's performance compared to conventional controllers. Comparative analyses will be conducted between traditional and ANFIS controllers to validate the effectiveness of the proposed approach.

Investigating PID Controller Effectiveness: An Extensive Analysis and Wide-ranging Uses

This study offers an in-depth investigation of the performance of proportional-integral-derivative (PID) controllers, providing an extensive evaluation and analyzing a wide range of applications. PID controllers, essential feedback mechanisms in various domains, are recognized as foundational instruments in control systems. This study evaluates PID controllers in in scenarios such as DC motor speed regulation, power system stability, Automatic Voltage Regulator (AVR) performance optimization, time delay processes, load frequency management, DC drive control, systematic process stability, and their developments in industrial control. The purpose of the study is to highlight the adaptability and effectiveness of PID controllers in contemporary control systems, including how artificial intelligence (AI) can be integrated into PID controller tuning.

Control system of the electric drive of a robot with a dc motor

Problem. Robotics and flexible production systems are the most important technical basis for the intensification of production. The use of robotic systems is expanding every year. This paper considers a two-circuit servo control system using the example of a DC motor current and speed control system and examines the functional diagram of the third circuit, a digital angle control system. Using the Matlab + SIMULINK software package, the servo drive and the digital system for controlling the angular position of the robot manipulator were modelled. Goal. As a result of the analysis, the purpose of the study was highlighted: the development of a digital system for adjusting the angular position of the manipulator, improve the quality of its positioning. Tasks: to study work management systems; to study the drives of robots; to get a mathematical model of an electric motor; to develop a machine diagram of a digital electric drive; to synthesize a three-loop robot positioning control system. Methodology. The research problems should be solved by methods of analysis and synthesis of automatic control systems. Results. In the work, a three-circuit control system of the electric drive of a robot with a direct current motor was developed. Thus, as a result of modeling the operation of a digital electric drive with three control circuits for current, speed and positioning, an aperiodic transient process was provided with quality indicators. Originality. Thus, the results of simulation of the two-loop servo control system showed that the dynamic characteristics of the electric motor in terms of current and speed of rotation, which meet the requirements of the task, are provided by the PI controller in the current control circuit and the PID controller in the speed control circuit. Thus, as a result of modeling the operation of a digital electric drive with three control circuits for current, speed and positioning, an aperiodic transient process was provided with quality indicators. Practical value. The following results were obtained during the research: the best control law for the current circuit is the proportional-integral (PI) law; the best control law for the speed contour is the proportional-integral-differential (PID) law; the best control law for a digital positioning control loop is the proportional (P) law.

Analysis and Performance Validation of CRONE Controllers for Speed Control of a DC Motor

In recent decades controllers play a major role for an efficient control and reliable operation of an industrial process. Hence in this paper, a special kind of Commande Robuste d’Ordre Non Entier (CRONE) controller is designed for controlling the speed of DC Motor (DCM). The proper design procedure of two generations CRONE control strategies named as First-Generation CRONE (FGC) and Second-Generation CRONE (SGC) controllers are implemented through the transfer function of armature-controlled DCM. Simulations are performed on MATLAB software in order to investigate the servo responses of two designed CRONE controllers, besides the results are presented in terms of settling time(ts), rise time(tr), Integral Square Error (ISE) and Integral Absolute Error (IAE). In addition, the relay PI controller is designed and the simulation results are presented for comparison purpose. It is evident from the comparing results that the SGC controller is superior for effective process control.

A Comparative Study of DC Motor Speed Control Techniques Using Fuzzy, SMC and PID

A Comparative Study of DC Motor Speed Control Techniques Using Fuzzy, SMC and PID

IOT Based DC Motor Speed and Direction Control

This paper introduces an innovative Internet of Things (IoT) based system designed to control the speed and direction of a DC motor using the Blynk mobile application. The system integrates an OLED display (SSD1306), an ESP8266 microcontroller, a 300 RPM DC motor, and an L293D motor driver. With this system, users can remotely manage the speed and direction of the DC motor through the Blynk app, accessible on smartphones or tablets. Real-time feedback on the motor's speed and direction is provided via the OLED display, enhancing user interaction and experience. The ESP8266 microcontroller acts as the core control unit, interfacing with the Blynk app via Wi-Fi to receive user commands and adjust the motor's operation accordingly. The bidirectional control feature of the L293D motor driver enables precise manipulation of the motor's speed and direction. By leveraging IoT technology and the Blynk app, users gain the flexibility to control the motor from any location with internet connectivity, offering convenience and accessibility. Additionally, the OLED display enhances the user interface, enabling intuitive monitoring and adjustment of motor parameters. In conclusion, this system offers a versatile and user-friendly solution for remotely managing DC motor speed and direction, with potential applications spanning across home automation, robotics, and industrial control systems.

Analysis of DC motor for process control application using neural network predictive controller

A DC motor is a critical actuator in process control systems. This study investigates the effectiveness of a deep learning (DL) based Neural Network Predictive Controller (NNPC) for precise DC motor speed control. The NNPC anticipates the motor’s future behaviour based on its current state and control inputs. The controller then optimally generates inputs to minimise tracking errors and enhance system performance. The NNPC demonstrated a remarkable reduction in Mean Squared Error (MSE), achieving a training MSE of 2.75 × 10−14 and the best validation MSE of 9.2023 × 10−14. These quantitative outcomes affirm the reliability and robustness of the proposed NNPC for speed control in DC motor systems across diverse applications.

Design and Implementation of Buck Boost Converter for fuzzy Logic Controller Based DC Motor Speed Control

Design and Implementation of Buck Boost Converter for fuzzy Logic Controller Based DC Motor Speed Control

Development of DC Motor Speed Control Using PID Based on Arduino and Matlab For Laboratory Trainer

DC motors are widely used as propulsions, including in electric bicycles. The problem faced by students in the DC motor control laboratory working using software simulation is that they do not have practical learning experience using digital instruments. This article aims to develop a DC motor speed control that can be used to learn practical Proportional Integral Derivative (PID) control in the laboratory. The DC motor speed control was developed using a combination of Arduino UNO microcontroller and Matlab software. The PID method was used because it is still broadly studied and applied in industries. The test results showed that the developed trainer can work well with PID variable values that can be entered via the keypad, and DC motor transient responses can be displayed in Matlab. From the experimental results, it was found that the optimal PID variable values were Kp=0.04, Ki=0.05, and Kd=0.004, where the controller produced a low overshoot value, i.e., 0.73% of its set point and a settling time of 10.66 seconds. The test results of using the developed trainer in the Fundamental of Control Engineering laboratory work showed that the developed trainer gave students practical learning experience in designing PID control for DC motor speed by using digital equipment, i.e., microcontroller and actual DC motor as well as analyzing its corresponding transient response in Matlab software environment

Model-based adaptive security control strategy against false data injection attacks in cyber–physical systems

This paper addresses the problem of adaptive security control for cyber–physical systems (CPSs) under external nonlinear disturbances and false data injection (FDI) attacks on actuators. To address FDI attacks, a full-order disturbance estimator is proposed for eliminating disturbances in the forward channel. Furthermore, an attack model based on the system state vector is developed to estimate the attack vector by considering potential attacks that can induce state errors between the reference model and the actual system. Subsequently, a novel model-based adaptive security control (MASC) strategy is devised using attack compensation and state feedback. The key advantage of our proposed strategy lies in its ability to effectively mitigate the adverse effects of attacks while accounting for nonlinear disturbances. Finally, experimental validation conducted on a brushless DC motor speed control system demonstrates the capability of achieving high output tracking accuracy.

SSA-based Fractional Order PI-PD Cascade Controller Design for DC Motor Speed Control

Bu çalışmada doğru akım (DA) motoru hız kontrolünü sağlamak için eklemeli ve kesir dereceli (FOPI-FOPD) denetleyici tasarımı önerilmiştir. Önerilen denetleyici parametreleri son yıllarda geliştirilen Serçe Arama Algoritması (SAA) ile optimize edilmiştir. Denetleyici parametrelerinin aranması için çeşitli amaç fonksiyonları kullanılmıştır. Bu amaç fonksiyonları zamanla çarpılan mutlak hatanın integrali (ITAE), mutlak hatanın integrali (IAE), zamanla çarpılan hatanın karesinin integrali (ITSE), hatanın karesinin integrali (ISE) ve Zwe-Lee Gaing (ZLG) fonksiyonudur. Zaman bölgesinde aşma (M_p), oturma süresi (t_s) ve yükselme süresi (t_r) bakımından kullanılan amaç fonksiyonlarından elde edilen sonuçlar karşılaştırılmıştır. Ayrıca elde edilen sonuçlar frekans bölgesinde kazanç marjı, faz marjı ve bant genişliği açısından incelenmiştir. Zaman ve frekans bölgesinde farklı amaç fonksiyonlarından elde edilen en iyi sonuç literatürdeki çalışmalarla karşılaştırılmıştır. Ayrıca önerilen denetleyicide elde edilen en iyi sonuç için gürbüzlük, bozucu yük ve referans hız değişimi analizleri incelenmiştir.