DC Motor Speed Research Articles

Implementing optimization of PID controller for DC motor speed control

The point of this paper presents an optimization technique which is flexible and quick tuning by using a genetic algorithm (GA) to obtain the optimum proportional-integral-derivative (PID) parameters for speed control of aseparately excited DC motor as a benchmark for performance analysis. The optimization method is used for searching for the proper value of PID parameters. The speed controller of DC motor using PID tuning method sincludes three types: MATALB PID tunner app., modified Ziegler-Nicholsmethod and genetic algorithm (GA). PID controller parameters (Kp, Ki and Kd) will be obtained by GA to produce optimal performance for the DC motor control system. Simulation results indicate that the tuning method of PID by using a genetic algorithm is shown to create the finest result in system performance such as settling time, rise time, percentage of overshoot and steady state error. The MATLAB/Simulink software is used to model and simulate the proposed DC motor controller system.

Proteus ISIS simulation for power factor calculation using zero crossing detector

One of the important parameters for electrical systems is the power factor (cos phi), which is the ratio of the real power (watt) to the apparent power (volt ampere). The best cos phi value is between 0.85 to 1. A resistive load causes the voltage and current in equal phase angle, while the inductive load causes the current to lag behind the voltage. On the other hand, the capacitive load causes the current to precede the voltage (leading). A simulation to determine the power factor of an electrical network can be done with Proteus ISIS software by creating a phase detection circuit. Automatic control can be done by a microcontroller. This simulation circuit can be used as power factor correction, a trigger angle on SCR trigger for DC motor speed control, for rocket launch angle adjuster, to measure the angle of inclination, and other uses relating to angle adjustments.

ATOM SEARCH OPTIMIZATION – NEURAL NETWORK FOR DRIVING DC MOTOR

DC motor applications are very widely used because DC motors are very suitable for applications, especially control. Thus, a proper DC motor controller design is required. DC motor speed control is very important to maintain the stability of motor operation. A recent type of metaheuristic algorithm that mimics the motion of atoms is introduced. Atom search optimization (ASO) is a mathematical model and duplicates the behavior of atoms in nature. Atoms intercommunicate with each other via the delivering contact force in the form of the Lennard-Jones potential and the constraint force produced from the potential bond length. The algorithm is simple and easy to be applied. In this study, the atomic search optimization (ASO) algorithm is proposed as a speed controller for the control dc motor. First, the ASO proposed by the algorithm is applied for the optimization of the neural network. Second, the ASO-NN proposal was the result compared to other algorithms. This paper compares the performance of two different control techniques applied to DC motors, namely the ASO-NN and proportional integral derivative (PID) methods. The results show that the proposed method has effectiveness. The calculation of the proposed ASO-NN control shows the best performance in the settling time. The ASO-NN method has the capability of settling time 0.04 seconds faster than the PID method.

PID Control System on Brushless DC Motor for Quadcopter Balance

Unmanned Aerial Vehicle (UAV) is an unmanned aircraft system that is no longer a special need but has become a general need for the community, and one example is used to capture everyday moments through photos or videos from the air. Among the models of UAV aircraft is the quadcopter, where there is a flight controller that functions to fly the quadcopter by adjusting the speed of each motor. The flight controller that is often used today is the Pixhawk manufacturer. The Pixhawk module is an integrated system that the factory has provided, so it cannot be modified in terms of control and I/O. This research focuses on making an independent flight controller that can be used to fly a quadcopter. The control method that is implanted is Proportional Integral Derivative or commonly known as PID. The flight controller uses the PID control method to adjust each Brushless DC Motor (BLDC) speed to maintain stability while flying. From the test results, the quadcopter can fly stably with KP parameters of 2.5, KI of 0.6, and KD of 1.0. The response time in processing feedback is 3s.

PID-Based Design of DC Motor Speed Control

DC motor is an easy-to-apply motor but has inconsistent speed due to the existing load. PID (Proportional Integral Differential) is one of the standard controllers of DC motors. This study aimed to know the PID controller's performance in controlling the speed of a DC motor. The results showed that the PID controller could improve the error and transient response of the system response generated from DC motor speed control. Based on the obtained system response data from testing and tuning the PID parameters in controlling the speed of a DC motor, the PID controller parameters can affect the rate of a DC motor on the setpoint of 500, 1000, 1500: Kp = 0.05, Ki = 0.0198, Kd = 0.05.

PLC Based DC Motor Speed Monitoring and Controlling System

PLC using rensans microcontroller for speed control of DC Gear Motor. in this project we will use rensans PLC for controlling the speed of operation of DC gear motor DC gear motor we can control with the help of pwm technique pulse width modulation. in this modulation we will very the weed width and control the DC gear motor speed. we will give 12 volt supply to DC motor and for controlling the speed we will put one circuit with the help of transistor between Rensans PLC and DC gear motor circuit used for pwm purpose the microcontroller give the pulses through transistor to the DC motor depending upon the pulses speed will vary in this pulses we will vary the on time and off time of the DC speed water if the on time is larger than the of time the speed of motor is increases and if the of time is larger than of time then speed will decreases this is a pwm technique pulse width modulation we will use in the project.

Optimal Tuning of Fuzzy Logic Controller Based Speed Control of DC Motor

Fuzzy logic controller (FLC) has become popular in the speed control application of DC motors with automatic adjustment function. In this article, the performance of a specific FLC controlled DC motor is studied. The exceed speed is observed with a stabilization time, thus confirming the FLC behavior. Therefore, FLC must be set to obtain the required performance by applying appropriate expert rules, the minimum overshoot and installation time can be maintained within the required values. With the help of FLC, the manual adjustment function is gradually eliminated, and the intelligent adjustment function is at the center position, and the performance is satisfactory. FLC DC motor speed control is implemented in MATLAB environment. The results show that the FLC method has the smallest bypass, smallest transient and steady-state error, and shows higher FLC efficiency as compared with other conventional controllers.

Optimal Coronavirus Optimization Algorithm Based PID Controller for High Performance Brushless DC Motor

This paper presents an efficient coronavirus optimization algorithm (CVOA) to find the optimal values of the PID controller to track a preselected reference speed of a brushless DC (BLDC) motor under several types of disturbances. This work simulates how the coronavirus (COVID-19) spreads and infects healthy people. The initial values of PID controller parameters consider the zero patient, who infects new patients (other values of PID controller parameters). The model aims to simulate as accurately as possible the coronavirus activity. The CVOA has two major advantages compared to other similar strategies. First, the CVOA parameters are already adjusted according to disease statistics to prevent designers from initializing them with arbitrary values. Second, the approach has the ability to finish after several iterations where the infected population initially grows at an exponential rate. The proposed CVOA was investigated with well-known optimization techniques such as the genetic algorithm (GA) and Harmony Search (HS) optimization. A multi-objective function was used to allow the designer to select the desired rise time, the desired settling time, the desired overshoot, and the desired steady-state error. Several tests were performed to investigate the obtained proper values of PID controller parameters. In the first test, the BLDC motor was exposed to sudden load at a steady speed. In the second test, the continuous sinusoidal load was applied to the rotor of the BLDC motor. In the third test, different operating points of reference speed were selected to the rotor of the BLDC motor. The results proved that the CVOA-based PID controller has the best performance among the techniques. In the first test, the CVOA-based PID controller has a minimum rise time (0.0042 s), minimum settling time (0.0079 s), and acceptable overshoot (0.0511%). In the second test, the CVOA-based PID controller has the minimum deviation about the reference speed (±4 RPM). In the third test, the CVOA-based PID controller can accurately track the reference speed among other techniques.

Modeling and Adaptive Control of Novel Electromechanical Inverter

A novel idea of electromechanical inverter (EMI) is proposed. This inverter minimize the complexity and cost of conventional rotating magnetic field inverters. The electromechanical inverter works on phenomena of rotating magnetic field in which changing flux in the external coils through dc motor induced an emf in the output coil. For controlling the speed of dc motor and rotation of coils, the adaptive control is used to avoid the saturation in magnetic field. The adaptive control system that is used for the electromechanical inverter (EMI) is model-reference adaptive control (MRAC) which has four parts i.e plant, reference model, adaptation mechanism and control law. An adaptation mechanism is designed with MIT rule of MRAC. The authenticity of proposed control technique for electromechanical inverter is verified by simulation results. The simulation result shows efficacy of proposed adaptive control technique using MATLAB

Improving neural network using a sine tree-seed algorithm for tuning motor DC

A DC motor is applied to delicate speed and position in the industry. The stability and productivity of a system are keys for tuning of a DC motor speed. Stabilized speed is influenced by load sway and environmental factors. In this paper, a comparison study in diverse techniques to tune the speed of the DC motor with parameter uncertainties is showed. The research has discussed the application of the feed-forward neural network (FFNN) which is enhanced by a sine tree-seed algorithm (STSA). STSA is a hybrid method of the tree-seed algorithm (TSA) and Sine Cosine algorithm. The STSA method is aimed to improve TSA performance based on the sine cosine algorithm (SCA) method. A feed-forward neural network (FFNN) is popular and capable of nonlinear issues. The focus of the research is on the achievement speed of DC motor. In addition, the proposed method will be compared with proportional integral derivative (PID), FFNN, marine predator algorithm-feed-forward neural network (MPA-NN) and atom search algorithm-feed-forward neural network (ASO-NN). The performance of the speed from the proposed method has the best result. The settling time value of the proposed method is more stable than the PID method. The ITAE value of the STSA-NN method was 31.3% better than the PID method. Meanwhile, the ITSE value is 29.2% better than the PID method.

Circuit design and modeling for DC motor speed control

Circuit design and modeling for DC motor speed control

DEVELOPMENT OF DIRECTIONAL ALGORITHM FOR THREE-WHEEL OMNIDIRECTIONAL AUTONOMOUS MOBILE ROBOT

A The proposed system developed an omnidirectional algorithm to control autonomous mobile robots with three wheels. The implementation system consists of three Planet DC motors with rated power of 80 W for three wheels, three encoders for speed feedback, one encoder for distance feedback, and one digital compass sensor for angle feedback. The main system with an STM32F407 microcontroller is designed for directional control of wheels based the signal received from compass sensor and encoder and then controls three subsystems to adjust the steering speed of each wheel. The sub-system is built to control only one DC motor for each wheel with the built-in proportional integral derivative controller (PID) algorithm by an STM32F103 microcontroller. Furthermore, the directional control algorithm is developed for three omnidirectional wheels and a PID algorithm is designed to control the speed of DC motor for each wheel. From the results the proposed system has the advantages: (1) to auto adjust the angle and position; (2) to erase the sensor for tracking line of the automobile robot; (3) cost-effectiveness and high accuracy

Teaching method of designing experiment from the perspective of teacher in power electronics course

In order to solve the problem of lacking active learning and independent problem-solving ability in the verification experiment, an experimental teaching method of designing experiment from the perspective of the teacher is proposed, in which the roles of students and teachers are changed. Students are made familiar with the platform through a verification experiment in which the teacher gives the experiment guidebook and provides guidance. Then, the target of another experiment is given. The students design the experiment from the perspective of the teacher, and write the experiment guidebook, including the experimental objectives, the experimental contents and the implementation methods. Then the students do the experiment. The power electronics experiment course is taken as an example to introduce the proposed method. The Sinusoidal Pulse Width Modulation (SPWM) inverter circuit experiment is taken as the verification experiment. After the students are familiar with the platform functions, they design a DC motor speed regulation experiment with a full bridge DC-DC circuit, write a guidebook, and complete the experiment according to the steps in the guide book. Finally, according to the success rate and the correct rate of the results, most students can complete the design experiment from the perspective of the teacher, and the answers to the thinking questions are basically correct. According to the questionnaire survey, the method proposed improves the students' ability of autonomous learning and problem-solving with good results.

Wireless Networked Optimal Controllers for Multiple Plants

The wireless communication technologies nowadays are the most common ubiquitous innovations used in our life. It is much easier to run than wired one, and its applications are increasing steadily. It is now extensively utilized in wireless equipment controlling during the continuous development. That is, from a reasonable distance, we can monitor and control our electronics and electrical equipment. It can be said that tools can only be managed with a controller in hand from a distance without being close to the controller. One of the popular technology requirements in the present time is wireless technology. In this article, the proposed multi plant multi controller (MPMC) system is based on wireless sensor networks (WSNs). The aims are to design and implement of wireless closed-loop optimal control system for multiple plants. The system consists of two main parts: the station part and the sensing part. The station part is designed for the purpose to control the system through the graphical user interface (GUI) designed in the LabVIEW program that gives signals to the sensing part wirelessly through the ZigBee nodes. The sensing part receives a signal from the station part wirelessly through the ZigBee node and used a wireless speed sensor to calculate the speed of connecting DC motors. Then, the sensing part returns the measure reading to the station side through another ZigBee node, to show the result in the GUI controlling the operations of the two plants. The work proves the feasibility of implementing the optimal MPMC systems through wireless networks using ZigBee technology.

Learning and Adaptation-Based Position-Tracking Controller for Rover Vehicle Applications Considering Actuator Dynamics

This article suggests an intelligent position-tracking control algorithm for rover vehicles considering actuator (dc motor) dynamics. The parameter and load uncertainties in the vehicle and dc motor dynamics are explicitly handled by modifying the original open-loop system dynamics. The proposed controller forms the conventional multiloop structure including disturbance observers for each loop. The features of this article fall into the following three parts: first, the learning part from the real-time feedback gain mechanism (named the self-tuner) in the closed-form for outer loop; second, the adaptation part from the online wheel radius estimation securing the outer-loop control accuracy; and third, the parameter-independent angular acceleration observer-based pole-zero cancellation dc motor speed controller without current feedback considering the inner- and outer-loop vehicle control algorithms. Experimental evidence is also provided to demonstrate the practical merits of the proposed technique with the use of the TETRIX, myRIO-1900, and LabVIEW.

Performance Evaluation of Different Objective Function in PID Tuned by PSO in DC-Motor Speed Control

The electric motor is an electromagnetic device that converts electrical energy into mechanical energy. There are many industrial sectors using electrical motors. Almost 90% of industries still use PID control because of its simplicity, applicability, and reliability. However, the weakness of PID is that it takes a long time to tune. PSO is one of the optimization methods which can be used to tune PID. The objective function is needed when using PSO to tune PID control. Five different objective functions which are ISE, IAE, ITSE, ITAE, and MSE is compared in terms of performance and control energy. The PID controller is applied in DC motor speed control in a simulation environment. Three testing condition is carried out which is step responses, set-point changes, and disturbance rejection. The simulation result shows that in terms of performance, ITSE is the best one. On the other hand, in terms of control energy, ISE is using the lowest energy to control the plant.

Design Controller depend in his work on Neural Fuzzy Networks to Control DC Motor's Speed

Design Controller depend in his work on Neural Fuzzy Networks to Control DC Motor's Speed

Design Controller depend in his work on Neural Fuzzy Networks to Control DC Motor's Speed

Design Controller depend in his work on Neural Fuzzy Networks to Control DC Motor's Speed

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.

A New Fusion of ASO with SA Algorithm and Its Applications to MLP Training and DC Motor Speed Control

An improved version of atom search optimization (ASO) algorithm is proposed in this paper. The search capability of ASO was improved by using simulated annealing (SA) algorithm as an embedded part of it. The proposed hybrid algorithm was named as hASO-SA and used for optimizing nonlinear and linearized problems such as training multilayer perceptron (MLP) and proportional-integral-derivative controller design for DC motor speed regulation as well as testing benchmark functions of unimodal, multimodal, hybrid and composition types. The obtained results on classical and CEC2014 benchmark functions were compared with other metaheuristic algorithms, including two other SA-based hybrid versions, which showed the greater capability of the proposed approach. In addition, nonparametric statistical test was performed for further verification of the superior performance of hASO-SA. In terms of MLP training, several datasets were used and the obtained results were compared with respective competitive algorithms. The results clearly indicated the performance of the proposed algorithm to be better. For the case of controller design, the performance evaluation was performed by comparing it with the recent studies adopting the same controller parameters and limits as well as objective function. The transient, frequency and robustness analysis demonstrated the superior ability of the proposed approach. In brief, the comparative analyses indicated the proposed algorithm to be successful for optimization problems with different nature.