DC Motor Position Research Articles

Dynamic data model and robust controller with high‐frequency component reduction for unknown time‐varying discrete‐time systems

AbstractThis article presents an adaptive controller tailored for discrete‐time systems, emphasizing robustness and addressing time‐varying constraints. An equivalent model is constructed solely from input‐output data collected from an unknown plant. Performance optimization involves determining an appropriate learning rate guided by theoretical analysis. A control law is derived from the equivalent model and a proposed auxiliary controller, with parameter settings guided by theoretical analysis to achieve robust convergence in closed‐loop performance. Comprehensive experimental and comparative assessments confirm the superior performance of both the equivalent model and the proposed controller, especially in brushless DC motor position control. Moreover, compared to similar schemes, the proposed controller generates fewer high‐frequency control effort components. The investigation validates the approach's robustness in real‐world conditions, including uncertainties, disturbances, and common time‐varying constraints in practical plant scenarios.

Comparative Analysis of Optimal Control Strategies: LQR, PID, and Sliding Mode Control for DC Motor Position Performance

This study applies these control methods to the DC motor system to examine the robustness and performance of four optimal control methods. Optimal controllers aim to control the system to minimize a selected performance index. These control methods offer advantages such as improving energy efficiency, reducing costs, and enhancing system security. The Linear Quadratic Regulator (LQR) based controller is the primary optimal control method. Two well-known traditional control techniques include the Proportional-Integral-Derivative (PID) and Integral Sliding Mode Controller (ISMC). However, they do not usually contain optimal properties. In this study, the optimal control algorithms, defined by obtaining controller parameters through the Riccati equation, are applied to achieve accurate position-tracking control in a DC motor system using Matlab/Simulink. The integral term-based algorithms seem to be robust and eliminate steady-state errors. The optimal PID controller could not provide the minimum performance index, unlike the other controllers in the study. LQR and optimal ISMC algorithms could allow the performance index to be a minimum. An illustrative comparison of the performances of all optimal control algorithms has been presented through graphical representation, along with corresponding interpretations.

IOT-ENABLED SMART LIGHTING SYSTEM WITH INTEGRATED PULLEY MECHANISM FOR HOME AUTOMATION

Lighting systems play a fundamental role in our daily life operations. However, the typical light bulb has a finite lifespan and is often installed in hard-to-reach locations, posing a challenge when it needs replacement. To address this issue, we've developed an IoT bulb holder equipped with a pulley mechanism designed to lower itself to a user-accessible height. This innovative system also features built-in light control functionality. Our solution integrates a microcontroller with a Wi-Fi module, a mechanical motor for the pulley mechanism, and an Android app. The Android app serves as the central control hub for the system. The microcontroller manages the DC motor's position and light control, responding to instructions from the app. Light control is achieved through a relay circuit, while the pulley mechanism is operated using a DC motor with a worm gearbox. The worm gearbox was chosen for its self-locking capabilities, eliminating the need for continuous power to maintain the light bulb at the desired height. 3D modeling software was utilized to create the casing and gearing components. Tests with two different microcontrollers: NodeMCU ESP8266 and ESP32 have been conducted. A comparative analysis revealed that the ESP32 is the superior choice for IoT projects due to its enhanced Wi-Fi efficiency and connectivity capabilities.

DC motor position control with Raspberry Pi on Simulink wireless external mode

In recent years, the use of Raspberry Pi as a microcontroller in real-time applications has becomewidespread. In this study, Raspberry Pi is used for DC motor position control system. In addition, wirelesscommunication is provided between the external control panel prepared in the Matlab/Simulink programand the Raspberry Pi. Thanks to this control panel, the system can be turned on and off, the controller gainscan be changed, and the position information of the motor can be displayed on the scope in real-time.

Model Reference Adaptive PID Controller Design and Analysis of the Impact of Controller Parameters on System Behavior: DC Motor Position Control

Oransal-integral-türev (PID) kontrol yöntemi, basit mimarisi, kolay tasarım ve otomatik kazanç ayarlama gibi çekici özellikleri nedeniyle endüstride yaygın olarak uygulanmaktadır. Bununla birlikte, PID denetleyicisiyle başarılı bir endüstriyel uygulama yapabilmek için genellikle denetleyicinin önceden manuel olarak yeniden ayarlanması gerekmektedir. Bu sorunu çözmek için çalışma kapsamında, düşük maliyetli STM32F4 uygulama geliştirme kiti ve Waijung blok seti kullanılarak uyarlamalı kontrol yöntemlerinden biri olan Model Referans Uyarlamalı PID Denetleyici (MRUPIDD) tasarımı gerçekleştirilmiştir. Uyarlanabilir PID denetleyicisi, sistem parametreleri zamanla değişse bile istenen kontrol performansını sağlamak için parametre ayarlama mekanizmasına sahiptir. Parametre ayarlama mekanizması ve denetleyici tasarımı için Massachusetts Teknoloji Enstitüsü (Massachusetts Institute of Technology-MIT) kuralı kullanılmıştır. Çalışma kapsamında tasarlanan denetleyicinin DC motor üzerinde konum kontrol uygulaması gerçekleştirilmiş ve PID denetleyicisi ile karşılaştırılarak hata maliyetleri hesaplanmıştır. Uyarlama kazanç parametrelerinin sistem davranışına etkisinin incelenmesi için ise farklı gama kazanç değerleri sisteme uygulanmış ve kararlılığı bozan durumlar incelenmiştir.

Comparison Performances between MABSA-PI Controller and MABSA-PD Controller for DC Motor Position System

The goal of this project is to create two different types of controllers for regulating DC motor position systems which are the MABSA-PI controller and the MABSA-PD controller. The MATLAB controllers are developed using the Simulink toolbox, while the transfer function of a DC motor is obtained from its circuit. Modified adaptive bats sonar algorithm (MABSA) will be implemented in the PI controller and PD controller as the main algorithm. MABSA is one of the swarm intelligences and is usually for an optimization problem. Next, the tuning method for the PI controller and PD controller will be the trial-and-error method. The combination graph of each controller will be shown in Simulink scope as the project is tested for various positions. The controller's ability to regulate the position of a DC motor was studied. The comparision among the system's transient response parameters, including percentage overshoot, rising time (Tr), and settling time (Ts), would be discused. Various toolbox functions available in Simulink software can be employed to repossess these parameter outcomes.

LQR+I and Fuzzy Logic Controller Design for DC Motor Position Control

Sabit mıknatıslı Doğru Akım (DA) motorları kontrol eğitimi uygulamalarında sıklıkla tercih edilmektedir. Kapalı çevrim DA motor kontrol uygulamaları için farklı birçok metot geliştirilmiştir. Geliştirilen metotların en önemli hedefi kontrolcü performansında yüksek başarım elde edebilmektir. Bu çalışmada, bir DA motorun açısal konum kontrolü, integratör ilave edilmiş doğrusal karesel regülatör (LQR+I) ve bulanık mantık kontrol (FLC) yöntemleri kullanılarak tasarlanmış ve öncelikle simülasyon ortamında daha sonra gerçek zamanda başarılı bir şekilde test edilmiştir. Model tabanlı LQR ve model tabanlı olmayan FLC kontrol yöntemleri deneysel bir sistem üzerinde uygulanmış ve elde edilen sonuçlar karşılaştırılmıştır. Kontrol algoritması hızlı kontrol prototipleme tekniği ile Waijung kütüphanesi kullanılarak hazırlanmış ve STM32F4 Discovery kiti aracılığıyla sistemde testler gerçekleştirilmiştir. Kontrolcü performanslarının daha net ortaya çıkması için gerçek zamanlı farklı referans sinyalleri sisteme uygulanmış, bu sinyaller sonucunda ise her iki kontrolcü de başarılı sonuçlar elde etmiştir.

Comparison of cascade P-PI controller tuning methods for PMDC motor based on intelligence techniques

In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.

Modeling and Controlling the Actuator Joint Angle Position on the Robot Arm Base Using Discrete PID Algorithm

DC motor is a motor that is easy to apply. Its application in robotic DC motor control often occurs errors due to the existing load, so that the DC motor becomes inaccurate. The control used is PID (proportional integral differential). This PID control system works by processing calculations based on the control variables Kp, Ki, and Kd to achieve the conditions according to the expected setpoint. To make a DC motor position control device can be controlled with a PID controller. In practice, the variable to be controlled in this research is position control in the form of degrees. With the Arduino Mega controller, the motor driver as a DC motor rotation controller, the DC motor is given feedback in the form of an encoder sensor, the software used is the Arduino IDE. The results showed that PID control can correct errors and transient responses with a time constant value of 1.50 seconds, a rise time of 1.60 seconds, a settling time of 2.30 seconds and a delay time of 1.20 seconds and a peak time of 1.6 seconds and an error value of 0.33% through tuning parameter Kp = 16 Ki = 0.001 Kd = 16.

Low speed sensorless control method of brushless DC motor based on pulse high frequency voltage injection

A low speed sensorless position control method for brushless DC motor based on pulse pulse high frequency voltage injection is proposed according to the characteristic that the brushless DC motor (BLDCM) which is produced at present makes the counter electromotive force waveform show sinusoidal waveform in view of the problem that it is difficult to accurately obtain the rotor position and speed of the brushless DC motor at zero and low speed. Its principle is to inject high frequency sinusoidal voltage signal on the estimated direct axis of the synchronous rotating coordinate system so that the motor can generate saturated salient effect, obtain the estimation error containing the rotor position information, and by detecting the output current of PI regulator of quadrature axis current loop, and then estimate the initial position of the rotor and judges the magnetic pole, realize the determination of the actual rotor position, finally, realize the non-position static low speed control of BLDCM by adding current and speed rings. According to the simulation test, it shows that this method can detect the position and speed of the motor rotor well at both zero speed and low speed.

축소 차수 모델 기반 제어기와 결합한 PI 관측기 기반 제어 시스템의 안정성 해석

System model order reduction is a popular technique employed by control systems engineers due to its ability to reduce model complexity. However, control systems designed based on reduced-order model may cause closed-loop system instability when applied to the full-order model. In addition, conventional control system improvement methods such as increasing the controller gains or using robust control techniques in particular disturbance observers can further deteriorate system performance. In order to shade light on this phenomena, this paper presents an analytical study of the effects of high observer gain on the stability of observer compensated control systems whereby both the controller and the observer are designed using the reduced-order system model. The analysis is performed by carrying out stability analysis of the closed-loop system through root locus method and Routh-Hurwitz stability criterion. The paper also presents a comparative analysis between placing all the closed-loop poles of the controller at a single location or multiple locations using LQR technique for the aforementioned class of controller. The results obtained from the analysis have been validated through a DC motor position control system application.

Phase Lead-Lag Controller Design for Real-Time DC Motor Position Control with Root Locus and Bode Diagram

Bu çalışmada, gerçek zamanlı DC motor konum kontrolü için klasik kontrol yöntemlerinden olan faz ilerlemeli ve faz ilerlemeli – gerilemeli denetleyici tasarımı kök yer eğrisi ve Bode diyagramı yöntemleri ile gerçekleştirilmiştir. Model tabanlı bir denetleyici tasarlanacağı için matematiksel model, kara kutu sistem tanımlama yöntemiyle deneysel verilerden hesaplanarak elde edilmiştir. STM32F4 geliştirme kiti ve Matlab destekli Waijung blok seti kullanılarak uygulama geliştirilmiştir. Denetleyici performansı, sisteme referans girişler verilmesi sonucu deney düzeneği üzerinde gerçek zamanlı sonuçların gözlenmesi ile test edilmiştir. Her iki yöntem tasarım sürecinin işleyişi ve yöntemlerin uygulanabilirliği gerçek zamanlı olarak gösterilmiş ve tasarlanan denetleyicilerin başarılı performans sergilediği gözlenmiştir. Gerçekleştirilen uygulamada kullanılan test düzeneği ve yöntemler, kontrol uygulamaları için hem güvenilir çalışma hem de ekonomik çözüm sunmaktadır.

Speed and Position Control of DC Motor using LabVIEW

New applications requiring both speed and position control have emerged as a result of technological advancements. In many applications, a DC motor's speed and position can be adjusted. The PID controller controls the speed and position of individually stimulated DC motors. Using LabVIEW software, this study attempts to control the speed and position of a DC motor as well as calculate the closed loop system model. Nonlinearity in any system has undesirable implications in normal operation. Unwanted outcomes including dead zones, saturation, and system reaction.

Comparison between butterfly optimization algorithm and particle swarm optimization for tuning cascade PID control system of PMDC motor

In this paper, two optimization methods are used to adjust the gain values for the cascade PID controller. These algorithms are the butterfly optimization algorithm (BOA), which is a modern method based on tracking the movement of butterflies to the scent of a fragrance to reach the best position and the second method is particle swarm optimization (PSO). The PID controllers in this system are used to control the position, velocity, and current of a permanent magnet DC motor (PMDC) with an accurate tracking trajectory to reach the desired position. The simulation results using the Matlab environment showed that the butterfly optimization algorithm is better than the particle swarming optimization (PSO) in terms of performance and overshoot or any deviation in tracking the path to reach the desired position. While an overshoot of 2.557% was observed when using the PSO algorithm, and a position deviation of 7.82 degrees was observed from the reference position.

Design of DC motor position tracking system based on LQR

In order to realize the accurate tracking of the desired position by the DC motor position tracking system, a control method of the DC motor position tracking system based on LQR was proposed. Based on the modeling of the DC motor position tracking system, the stability, controllability and observability of the system are analyzed. Then, the LQR optimal control theory and the design process of the controller are introduced, and the output angular position of the DC motor is taken as the control object, and several common control methods are compared with the controller algorithm designed in this paper through MATLAB software. Experimental results show that the designed controller algorithm can track the desired position, and the system also has the characteristics of short adjustment time, small overshoot and high tracking accuracy.

Didactic platform for DC motor speed and position control in Z-plane

This paper describes how to implement a low-cost didactic platform designed to teach or reinforce discrete control theory concepts. The controllers used in this work (P, PI, PD, and PID) are suitable for undergraduate students but the same platform could be used to explain and test advanced controllers to graduate students. This document shows, step by step, how to control a DC motor speed and position, along with the most common problems and its solutions, commonly overlooked in the literature. It also explains how to simulate the system behavior and compares the simulations with the real data, showing an average correlation coefficient of ρ=0.983.

Pole Placement Based State Feedback for DC Motor Position Control

The paper proposes DC Motor position controller by applying state feedback control which is tuned by pole placement method. DC motor is one of most widely-used industrial and robotics actuators. Hence, DC Motor controller is supposed to have good performance with high efficiency. The research designed state feedback controller which functions to set position of DC motor with best pole parameter value. DC Motor simulation with pole placement is made in MATLAB. Based on test results, best pole values for the DC Motor is [-10+j10-10-10-j10] with system response performance as: 0% overshoot, 0.4459 second in settling time, and 0.2558 second in rise time.

Design of a Low-Order Harmonic Disturbance Observer with Application to a DC Motor Position Control

Among various tools implemented to counteract undesired effects of time-varying uncertainties, disturbance observer (DOB)-based controller has gained wide popularity as a result of its flexibility and efficacy. In this paper, a low-order DOB that is capable of compensating for the effects of a biased harmonic disturbance, as well as plant uncertainties is presented. The proposed low-order DOB can asymptotically estimate a harmonic disturbance of known frequency but unknown amplitude and phase, by using measurable output variables. An analysis carried out by using the singular perturbation theory shows that the nominal performance of the system can be recovered from a real uncertain system when the observer gain is sufficiently large. The observer gains that result in the performance recovery of the real uncertain system are obtained from the stability condition of the boundary-layer system. To test the performance of the proposed observer, computer simulations with a numerical example and laboratory experiments using a DC motor system have been carried out. The experimental results show that the proposed low-order DOB-based control scheme can provide enhanced performance.

Modified WCA-Based Adaptive Control Approach Using Balloon Effect: Electrical Systems Applications

This paper suggests an adaptive control approach using water cycle algorithm optimization method (WCA) modified by a new technique called “Balloon Effect”. The main concept of Balloon Effect is to increase the ability of the WCA to tune individually the gains of the controller online. The proposed technique has been used to tune the gains of PID controller and applied to control both of the load frequency control in micro-grid power system (which minimize the fundamental frequency variations) and the position of armature-controlled DC motor. Digital simulations have been carried out to prove the efficiency of the proposed adaptive controller-based WCA with Balloon Effect. The obtained results showed that the proposed adaptive controller maintains robust performance, and effectively reduces the impact of identified disturbances and uncertainties.

Identification and Adaptive Position and Speed Control of Permanent Magnet DC Motor with Dead Zone Characteristics Based on Support Vector Machines

Identification and Adaptive Position and Speed Control of Permanent Magnet DC Motor with Dead Zone Characteristics Based on Support Vector Machines