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

Algorithms ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 193
Author(s):  
Mohamed A. Shamseldin
Keyword(s):  
Optimization Algorithm ◽  
Rise Time ◽  
Pid Controller ◽  
High Performance ◽  
Harmony Search ◽  
Settling Time ◽  
Optimization Techniques ◽  
Bldc Motor ◽  
Brushless Dc ◽  
The Third

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.

scholarly journals BLDC Motor Speed Control using Fuzzy Logic PID Controller and Comparing It with PI Controller

2019 ◽  
Vol 9 (2) ◽  
pp. 4917-4922
Keyword(s):  
Mathematical Model ◽  
Pid Controller ◽  
High Performance ◽  
Pi Controller ◽  
Dynamic State ◽  
Bldc Motor ◽  
Fuzzy Pid ◽  
Motor Speed ◽  
Brushless Dc ◽  
Fuzzy Pid Controller

In this project, mathematical model of the Brushless DC motor (BLDC) is developed and the closed-loop Fuzzy PID controller has been simulated in MATLAB-Simulink environment. The three-phase (BLDC) is developed and the DC power is supplied to this machine though six step inverter whose switching state is controlled by the hall signal. The hall effect sensor senses the rotor posit ion of the motor and it generates binary digit number which is decoded and given to the six-step inverter. The mathematical model is developed using the back emf equations and torque equation of the BLDC motor. The PI controller doesn’t operate properly during dynamic state and hence the fuzzy-PID-controller is better option to control and regulate the speed of the BLDC motor which has high performance in comparison to the PI controller. And, we can get the smooth speed-torque characteristics using Fuzzy PID controller.

scholarly journals Perancangan Kendali Optimal pada Motor Arus Searah Tanpa Sikat melalui Metode LQRI

2019 ◽  
Vol 7 (2) ◽  
pp. 377 ◽  
Author(s):  
KHOIRUDIN FATHONI ◽  
ARYO BASKORO UTOMO
Keyword(s):  
Rise Time ◽  
Load Condition ◽  
Linear Quadratic Regulator ◽  
Settling Time ◽  
Control Signal ◽  
Bldc Motor ◽  
Linear Quadratic ◽  
Cost Matrix ◽  
R Matrix ◽  
Set Point

ABSTRAKArtikel ini akan menjelaskan perancangan kendali kecepatan MASTS  dengan tujuan diperoleh respon kecepatan MASTS yang tanggap serta memiliki sinyal kendali dan arus minimal. Untuk mencapai hal ini MASTS akan dikendalikan melalui metode Linear Quadratic Regulator (LQR) dengan state yang dipilih adalah arus, kecepatan, dan state integral galat kecepatan. Diperlukan penalaan nilai parameter Q matriks bobot state dan R matriks bobot input untuk mendapatkan performa kecepatan dan arus yang terbaik. Berdasarkan pengujian diperoleh bahwa dengan kendali LQR-I, kecepatan MASTS dapat mengikuti set point dengan respon rise time Tr = 0,03 detik, settling time Ts=0,044 detik, overshoot (OS) 1,6 %, arus Imax=0,16 A dan dutycycle sinyal kontrol umax 56% pada kondisi tanpa beban dan Tr = 0,03 detik, Ts=0,044 detik, OS 1,6 %, Imax=0,16 A dan umax 56% pada kondisi berbeban. Dibandingkan dengan kendali PID ketika tanpa beban mempunyai Tr=0,0176 Ts=0,075 %OS=3,9% umax=96% Imax=0,35 A, LQRI mempunyai respon settling time, sinyal kendali dan arus yang lebih baik.Kata kunci: Motor Arus Searah Tanpa Sikat, Kendali Optimal, Linear  Quadratic Regulator dan Integral ABSTRACTThis paper aimed to discuss further research about BLDC motor speed control so that BLDC not only has fast speed response but also has minimum control signal and current using LQR (Linear Quadratic Regulator) control with chosen states are current, speed of BLDC, and speed error integral state. Tuning of Q and R matrix is required to reach the best speed and current performance. Where Q and R matrix is state cost matrix and input cost matrix, respectively. Result show that LQR-I control can track set point with rise time Tr = 0.03 s, settling time Ts=0,044 s, overshoot (OS) 1,6 %, current Imax=0,16 A and dutycycle control signal umax 56% in no load condition, and Tr = 0,03 s, Ts=0,044 s, OS 1,6 %, Imax=0,16 A dan umax 56% in the load condition. Compared to PID controller which has Tr=0,0176 Ts=0,075 %OS=3,9% umax=96% Imax=0,35 A in no load condition, proposed controller has a better settling time, control signal and current.Keywords: BLDC Motor, Optimal Control, LQR and Integral

scholarly journals Brushless DC Motor Speed Controller for Electric Motorbike

2018 ◽  
Vol 9 (2) ◽  
pp. 859
Author(s):  
Mohd Syakir Adli ◽  
Noor Hazrin Hany Mohamad Hanif ◽  
Siti Fauziah Toha Tohara
Keyword(s):  
Pid Controller ◽  
Dc Motor ◽  
Battery Pack ◽  
Brushless Dc Motor ◽  
Bldc Motor ◽  
Motor Speed ◽  
Brushless Dc ◽  
Speed Controller ◽  
Optimum Speed ◽  
Control Scheme

<p>This paper presents a control scheme for speed control system in brushless dc (BLDC) motor to be utilized for electric motorbike. While conventional motorbikes require engine and fuel, electric motorbikes require DC motor and battery pack in order to be powered up. The limitation with battery pack is that it will need to be recharged after a certain period and distance. As the recharging process is time consuming, a PID controller is designed to maintain the speed of the motor at its optimum state, thus ensuring a longer lasting battery time (until the next charge). The controller is designed to track variations of speed references and stabilizes the output speed accordingly. The simulation results conducted in MATLAB/SIMULINK® shows that the motor, equipped with the PID controller was able to track the reference speed in 7.8x10<sup>-2</sup> milliseconds with no overshoot.  The result shows optimistic possibility that the proposed controller can be used to maintain the speed of the motor at its optimum speed.</p>

scholarly journals Comparison and Speed Control of DC Motor and DC Servomotor Using IMC Based PID Controller

2021 ◽  
Vol 6 (12) ◽  
pp. 493-501
Author(s):  
Amarapini Divya and Dr.Prasadarao Bobbili
Keyword(s):  
Time Domain ◽  
Rise Time ◽  
Pid Controller ◽  
Speed Control ◽  
Dc Motor ◽  
Settling Time ◽  
Peak Amplitude ◽  
Pid Controllers ◽  
Frequency Method ◽  
Dc Servomotor

IMC based PID controllers are being used to speed control of DC motor and DC servomotor in industry. As this controller offer good performance comparitive to conventional controllers like PI, PID and Ziegler Nichols frequency method controllers. This paper presents the speed control of the DC motor and DC servomotor using PI, PID, Ziegler Nichols method and IMC-PID controllers, to realize the optimization of control action. A mathematical calculation of DC motor and DC servomotor has developed and simulations are carried out in MATLAB/ Simulink environment. From the results, it is observed that time domain parameters like rise time 0.6 secs, settling time 2 secs, speed for peak over shoot 1450, peak amplitude 1, with no oscillations using IMC-PID controller on DC motor. And for DC servomotor its rise time is 0.3 seconds, settling time is 1 second, speed for peak overshoot 1450 rpm, peak amplitude 1 with absence of oscillations by using IMC-PID controller

scholarly journals Analisis Penalaan Kontrol PID pada Simulasi Kendali Kecepatan Putaran Motor DC Berbeban menggunakan Metode Heuristik

2013 ◽  
Vol 1 (2) ◽  
pp. 79 ◽  
Author(s):  
WALUYO WALUYO ◽  
ADITYA FITRIANSYAH ◽  
SYAHRIAL SYAHRIAL
Keyword(s):  
Steady State ◽  
Rise Time ◽  
Pid Controller ◽  
Settling Time ◽  
Control Parameters ◽  
Motor Speed ◽  
Set Point ◽  
Dc Motors ◽  
And Control ◽  
Peak Value

ABSTRAKMotor DC banyak digunakan di industri kecil dan besar.Kecepatan motor DC sering tidak stabil akibat gangguan dari luar maupun perubahan parameter dan torsi beban sehingga perlu dilakukan rancangan kontroler.Kontroler yang dirancang menggunakan PID yang terdiri dari tiga jenis cara pengaturan yang dikombinasikan, yaitu kontrol P (Proportional), kontrol I (Integral) dan kontrol D (Derivatif).Kontroler yang dirancang disimulasikan menggunakan perangkat lunak. Hasil simulasi menunjukan kontroler PID untuk kendali kecepatan motor DC ini menghasilkan kondisi robust (kokoh) saat nilai Kp = 1,1, Ti = 0,1, Td = 3,7. Hasil dari parameter kendali yang dirancang memiliki error steady state 0,99 % dan dengan settling time 3,7 detik pada rise time 2,00 detik dan nilai peak terletak pada 0,99. Kecepatan awal yang dihasilkan mendekati set point yang diinginkan pada detik ke 6 dan kecepatannya tidak ada penurunan atau tetap konstan sampai dengan detik ke 100.Kata kunci: Motor DC, PID, Heuristik, Steady State, Rise Time ABSTRACT DC motors are widely used in small and large industries. Their speeds are often unstable due to interference from outside or change the parameters and load torque, so that it was necessary to design a controller. The controller was designed using a PIDconsists of three types of arrangements, which are mutually combined way, namely the control P (Proportional), control I (Integral) and control D (Derivative). The controllers were designed using software for simulation. The simulation results showed the PID controller for DC motor speed control produced robust conditionswhen the value of Kp, Ti and Tdwere 1.1,  0.1 and 3.7 respectively. The results of the control parameters had error steady state 0.99 % and the settling time of 3.7 seconds at 2.0 sec rise time and the peak value was 0,99. The resulted initial velocity was very fast to approach the desired set point in the sixth second and its speed was remain constant until 100thsecond.Keywords: Motor DC, PID, Heuristic, Steady State, Rise Time

scholarly journals Speed Control of BLDC Motor using Open Loop, PID Controller and Neural Network

2019 ◽  
Vol 9 (1) ◽  
pp. 2210-2213
Keyword(s):  
Neural Network ◽  
Simulation Study ◽  
Pid Controller ◽  
Speed Control ◽  
Open Loop ◽  
Bldc Motor ◽  
Variable Speed ◽  
Brushless Dc Motors ◽  
Brushless Dc ◽  
Dc Motors

is main goal of upcoming and present applications. However, its possible to achive these aims using brushless DC motors (BLDC), due to its use in many applications. The applications such as sppining, drilling, elevators, lathes, etc can be exicuted using BLDC motor and can replace conventional DC brush motor. The effective vechiel control required for applications of variable speed can be achived using BLDC motors. This paper presents speed control of BLDC motor for open loop using PID and neural network techniques and their comparative study. From the simulation study it is observed that neural network gives better performance compaiered to other technique.

scholarly journals Optimization of Proportional Integral Derivative Parameters of Brushless Direct Current Motor Using Genetic Algorithm

2020 ◽  
pp. 24-32
Author(s):  
Isaiah Adebayo ◽  
David Aborisade ◽  
Olugbemi Adetayo
Keyword(s):  
Genetic Algorithm ◽  
Direct Current ◽  
Pid Controller ◽  
Absolute Error ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Bldc Motor ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Brushless Dc

Optimal performance of the Brushless Direct Current (BLDC) motor is to be realized using an efficient Proportional Integral Derivative (PID) controller. However, conventional tuning technique fails to perform satisfactorily under parameter variations, nonlinear conditions and time delay. Also using conventional technique to tune the parameters gain of the PID controller is a difficult task. To overcome these difficulties, modern heuristic optimization technique are required to optimally tune the Proportional, Integral, Derivative of the controller for optimal speed control of three phase BLDC motor. Thus, genetic algorithm (GA) based PID controller was used to achieve a high dynamic control performance. The Brushless DC Motor mathematical equation which describes the voltage and corresponding rotational angular speed and torque of the brushless DC motor was employed using electrical DC Machines theorem. The Genetic algorithm was further analyzed by adopting the three common performance indices i.e. Integral Time Absolute Error (ITAE), Integral Square Error (ISE) and Integral Absolute Error (IAE) in order to capture and compare the most suitable BLDC Motor speed and torque control characteristics. All simulations were done using MATLAB (R2018a). The simulation result showed that the system with GA-PID controller had the better system response when compared with the existing technique of ZN-PID controller.

scholarly journals Design and Simulation of Adaptive PID Controller Based on Fuzzy Q-Learning Algorithm for a BLDC Motor

2020 ◽  
Author(s):  
Reza Rouhi Ardeshiri ◽  
Nabi Nabiyev ◽  
Shahab S. Band ◽  
Amir Mosavi
Keyword(s):  
Reinforcement Learning ◽  
Pid Controller ◽  
Control Method ◽  
Learning Algorithm ◽  
Bldc Motor ◽  
Motor Speed ◽  
Q Learning ◽  
Brushless Dc ◽  
Intelligent Control Systems ◽  
And Control

Reinforcement learning (RL) is an extensively applied control method for the purpose of designing intelligent control systems to achieve high accuracy as well as better performance. In the present article, the PID controller is considered as the main control strategy for brushless DC (BLDC) motor speed control. For better performance, the fuzzy Q-learning (FQL) method as a reinforcement learning approach is proposed to adjust the PID coefficients. A comparison with the adaptive PID (APID) controller is also performed for the superiority of the proposed method, and the findings demonstrate the reduction of the error of the proposed method and elimination of the overshoot for controlling the motor speed. MATLAB/SIMULINK has been used for modeling, simulation, and control design of the BLDC motor.

scholarly journals Objective functions modification of GA optimized PID controller for brushed DC motor

2020 ◽  
Vol 10 (3) ◽  
pp. 2426
Author(s):  
A.A.M. Zahir ◽  
Syed Sahal Nazli Alhady ◽  
A.A.A Wahab ◽  
M.F. Ahmad
Keyword(s):  
Steady State ◽  
Objective Function ◽  
Rise Time ◽  
Pid Controller ◽  
Optimization Method ◽  
Settling Time ◽  
Performance Parameter ◽  
Objective Functions ◽  
Performance Requirement ◽  
State Error

PID Optimization by Genetic Algorithm or any intelligent optimization method is widely being used recently. The main issue is to select a suitable objective function based on error criteria. Original error criteria that is widely being used such as ITAE, ISE, ITSE and IAE is insufficient in enhancing some of the performance parameter. Parameter such as settling time, rise time, percentage of overshoot, and steady state error is included in the objective function. Weightage is added into these parameters based on users’ performance requirement. Based on the results, modified error criteria show improvement in all performance parameter after being modified. All of the error criteria produce 0% overshoot, 29.51%-39.44% shorter rise time, 21.11%-42.98% better settling time, 10% to 53.76% reduction in steady state error. The performance of modified objective function in minimizing the error signal is reduced. It can be concluded that modification of objective function by adding performance parameter into consideration could improve the performance of rise time, settling time, overshoot percentage, and steady state error

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