scholarly journals Kontrol Proporsional Integral Derivatif (PID) pada Kecepatan Sudut Motor DC dengan Pemodelan Identifikasi Sistem dan Tuning

2021 ◽  
Vol 9 (2) ◽  
pp. 374
Author(s):  
ALFIAN MA'ARIF ◽  
RYAN ISTIARNO ◽  
SUNARDI SUNARDI
Keyword(s):  
System Identification ◽  
Direct Current ◽  
Pid Control ◽  
Rise Time ◽  
Motor System ◽  
Input Voltage ◽  
Dc Motor ◽  
Settling Time ◽  
System Model ◽  
Pid Tuning

ABSTRAKPenelitian ini mengusulkan tentang sistem kontrol kecepatan sudut Motor Direct Current (DC) menggunakan kontrol Proporsional Integral Derivatif (PID). Pemodelan motor DC menggunakan model identifikasi sistem agar model sistem dapat mendekati sistem sesungguhnya. Data identifikasi sistem adalah nilai masukan tegangan dan nilai keluaran kecepatan sudut. Representasi model adalah model fungsi alih. Nilai kontrol PID didapatkan dengan fitur Tuning PID dengan Matlab. Perangkat penelitian adalah Arduino, sensor encoder, driver motor dan Motor DC. Pada pengujian, kendali motor DC dengan PID mampu untuk mendapatkan respon yang baik dengan nilai respon terbaik, rise time 9,4286 detik, settling time 18,5 detik dan overshoot 2 persen. Nilai variasi PWM untuk memperoleh model dan respon sistem motor DC yang bagus yaitu nilai variasi PWM 5, nilai variasi PWM 10 dan nilai variasi PWM 50, 150, 255. Dengan menggunakan metode ini, proses tuning kontrol PID dapat lebih efektif dan efisien.Kata kunci: Motor DC, Identifikasi Sistem, Kontrol PID, Tuning Matlab, Kecepatan ABSTRACTThis study proposes a direct current (DC) motor angular speed control system using Proportional Integral Derivative (PID) control. DC motor modeling uses a system identification model so that the system model can approach the real system. The system identification data is the input voltage value and the angular velocity output value. Model representation is a transfer function model. PID control values are obtained with the PID Tuning feature with Matlab. The research devices are Arduino, encoder sensor, motor driver and DC motor. In testing, the DC motor control with PID was able to get a good response with the best response value, rise time of 9.4286 seconds, settling time of 18.5 seconds and overshoot 2 percent. The PWM variation values to obtain a good DC motor system model and response are the PWM variation value 5, the PWM variation value 10 and the PWM variation value 50, 150, 255. By using this method, the PID control tuning process can be more effective and efficient.Keywords: DC Motor, System Identification, PID Control, Matlab Tuning, Speed

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 Sintesis Kendali PID Digital dengan Diskritisasi Langsung dan Backward Difference

2021 ◽  
Vol 9 (2) ◽  
pp. 467
Author(s):  
FENI ISDARYANI ◽  
MOHAMAD FADHILAH VIERI HESYA ◽  
FERIYONIKA FERIYONIKA
Keyword(s):  
Difference Equation ◽  
Pid Control ◽  
Difference Method ◽  
Rise Time ◽  
Computer Programming ◽  
Settling Time ◽  
Digital Controller ◽  
Discretization Method ◽  
Analog To Digital ◽  
Digital Pid

ABSTRAKKendali PID analog, yang realisasinya menggunakan komponen elektronika, memiliki keterbatasan yaitu nilai toleransi yang terbatas. Saat ini spesifikasi kontroler dituntut untuk dapat berkomunikasi dengan sistem yang lebih besar seperti SCADA dan DCS sehingga lebih cocok menggunakan pengendali digital. Penelitian ini menganalisis metode konversi PID analog ke digital agar dihasilkan difference equation yang dapat direalisasikan ke dalam pemrograman komputer. Metode yang dipakai adalah diskritisasi langsung dan Backward Difference. Perbandingan kedua metode dilakukan dengan menganalisis respons berdasarkan initial paramater yang dihasilkan oleh metode Ziegler Nichols. Hasil pengujian menunjukkan kendali PID diskrit menggunakan Backward Difference menghasilkan respons sistem yang lebih baik dibandingkan metode diskritisasi langsung dengan nilai Kp, Ti, dan Td adalah 50, 80 dan 0,001 menghasilkan respons dengan nilai rise time, settling time dan overshoot berturut-turut sebesar 33,66s, 90,39s dan 0,9%.Kata kunci: PID diskrit, diskritisasi langsung, Backward Difference, Ziegler Nichols ABSTRACTThe analog PID control, where its parameters are realised using the electronic component, has disadvantages due to the limitation of its tolerance value. Currently, the specifications of controller are required to be able to communicate with larger systems such as SCADA and DCS, therefore digital controller is more appropriate to use. This study analyzes the analog to digital PID conversion method to generate a difference equation that can be realized in computer programming. The direct discretization and Backward Difference method are used. Comparison of both methods is by analyzing response based on initial parameters obtained of Ziegler Nichols method. The results show that discrete PID control using the Backward Difference indicates a better response than using the direct discretization method with Kp, Ti, and Td values are 50, 80, and 0,001, respectively. Those parameters generate response with rise time, settling time, and overshoot values of 33,66s, 90,39s, and 0,9%, respectively.Keywords: discrete PID, direct discretization, Backward Difference, ZieglerNichols

Auto PID Tuning of Speed Control of DC Motor Using Particle Swarm Optimization Based on FPGA

2015 ◽  
Vol 776 ◽  
pp. 390-395 ◽  
Author(s):  
Hilal Tayara ◽  
Deok Jin Lee ◽  
Kil To Chong
Keyword(s):  
Particle Swarm Optimization ◽  
Steady State ◽  
Rise Time ◽  
Particle Swarm ◽  
Speed Control ◽  
Dc Motor ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Swarm Optimization ◽  
Pid Tuning

This paper introduces auto tuning of proportional-integral-derivative (PID) controllers of DC motor using particle swarm optimization (PSO) method. The DC motor was modeled in Simulink and PSO was implanted on FPGA “cyclone IV E” using the soft processor NIOS II. The results were efficient in reducing the steady state error, settling time, rise time and maximum overshoot in speed control of a DC motor.

scholarly journals Optimization of PID Tuning Using Genetic Algorithm

1970 ◽  
Vol 2 (2) ◽  
Author(s):  
Tengku Ahmad Faris Ku Yusoff ◽  
Mohd Farid Atan ◽  
Nazeri Abdul Rahman ◽  
Shanti Faridah Salleh ◽  
Noraziah Abdul Wahab
Keyword(s):  
Genetic Algorithm ◽  
Population Size ◽  
Rise Time ◽  
Distillation Column ◽  
Settling Time ◽  
Tuning Method ◽  
Pid Tuning ◽  
The Cost ◽  
Large Improvement

Controller tuning is one of the important aspect in industry. With a good tuning method, it can ensure the quality of the process and product produce. Apart from that, it can protect the environment and help the company to reduce the cost. Genetic algorithm is one of the tuning method that increase usage and awareness in industry. Thus, the objective of this research is to compare the performance of the conventional tuning method with the performance of tuning method by using genetic algorithm can be seen. Optimization was done on stripping section of distillation column by using genetic algorithm with population size of 20, 40, 60 and 80 and comparing the result with previous optimization using Ziegler-Nichols method. The result obtain showed large improvement in the process response especially on rise time from 1.33 s to 1.31s and settling time from 4.56 to 4.46. Finally, population size of 40 deliver the fastest rise time and settling time.

scholarly journals Tuning of PID Controller Parameters with Genetic Algorithm Method on DC Motor

2021 ◽  
Vol 1 (1) ◽  
pp. 41-53
Author(s):  
Eka Widya Suseno ◽  
Alfian Ma'arif
Keyword(s):  
Genetic Algorithm ◽  
Rise Time ◽  
Biological Evolution ◽  
Parameter Tuning ◽  
Dc Motor ◽  
Settling Time ◽  
Trial And Error ◽  
Genetic Algorithm Method ◽  
Trial And Error Method ◽  
Error Method

Proportional Integral Derivative (PID) controllers are used in general to control a system, for example a DC motor system. The difficulty of using the controller is parameter tuning, because the tuning parameters still use the trial and error method to find the PID parameter constants, namely Proportional Gain (KP), Integral Gain (KI) and Derivative Gain (KD). In this case, the genetic algorithm method is used which can give better results in each iteration. Genetic algorithms are one of the smart methods inspired by the process of natural selection, the process that causes biological evolution, this concept is applied to tuning PID parameters. This research uses the Matlab simulation method and applies the simulation results to the DC motor hardware using the Arduino Uno. The genetic algorithm method gives a system that has a better steady time and a smaller maximum spike than the Trial and Error method. The test process produced the two best data with an overshoot value = 2, settling time = 13.5 and rise time of 2.7872 and the PID parameter value for mutation of 1 was KP = 3.7500; KI = 1.3184 and KD = 0.2051. Then the value of the best PID parameter on Crossover is 0.4, which is KP = 4.2090; KI = 1.2012 and KD = 0.2539 with an overshoot value = 2, settling time = 18 and rise time = 2.6462.

scholarly journals A PID-Type Fuzzy Logic Controller-Based Approach for Motion Control Applications

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5323 ◽  
Author(s):  
José R. García-Martínez ◽  
Edson E. Cruz-Miguel ◽  
Roberto V. Carrillo-Serrano ◽  
Fortino Mendoza-Mondragón ◽  
Manuel Toledano-Ayala ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Motion Control ◽  
Rise Time ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Industrial Applications ◽  
Settling Time ◽  
Self Tuning ◽  
S Curve ◽  
Tuning Strategy

Motion control is widely used in industrial applications since machinery, robots, conveyor bands use smooth movements in order to reach a desired position decreasing the steady error and energy consumption. In this paper, a new Proportional-Integral-Derivative (PID) -type fuzzy logic controller (FLC) tuning strategy that is based on direct fuzzy relations is proposed in order to compute the PID constants. The motion control algorithm is composed by PID-type FLC and S-curve velocity profile, which is developed in C/C++ programming language; therefore, a license is not required to reproduce the code among embedded systems. The self-tuning controller is carried out online, it depends on error and change in error to adapt according to the system variations. The experimental results were obtained in a linear platform integrated by a direct current (DC) motor connected to an encoder to measure the position. The shaft of the motor is connected to an endless screw; a cart is placed on the screw to control its position. The rise time, overshoot, and settling time values measured in the experimentation are 0.124 s, 8.985% and 0.248 s, respectively. These results presented in part 6 demonstrate the performance of the controller, since the rise time and settling time are improved according to the state of the art. Besides, these parameters are compared with different control architectures reported in the literature. This comparison is made after applying a step input signal to the DC motor.

scholarly journals Fuzzy Control of a Direct Current Motor System and Stability Analysis

1999 ◽  
Vol 3 (6) ◽  
pp. 515-518
Author(s):  
Euntai Kim ◽  
◽  
Heejin Lee ◽  
Dongyon Kim ◽  
Keyword(s):  
Fuzzy Logic ◽  
Stability Analysis ◽  
Fuzzy Control ◽  
Direct Current ◽  
Motor System ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Asymptotically Stable ◽  
Electromechanical Systems ◽  
Control Methodology

One of the most common ways of driving electromechanical systems is through the use of a DC motor. In this paper, fuzzy control methodology for a DC motor system using a singleton fuzzy logic controller (FLC) is proposed. As opposed to conventional works, fuzzy control methodology proposed here is guaranteed to be asymptotically stable on the whole. Finally, the validity of the suggested methodology is highlighted via an illustrative example.

Penerapan Advanced Pid Tuning Pada Plant Yang Critically Stable: Height Levitation Pingpong Ball

2019 ◽  
Vol 9 (01) ◽  
pp. 41-46
Author(s):  
M Iqbal Nugraha ◽  
Aan Febriansyah ◽  
A F Khoiri ◽  
D Pratama
Keyword(s):  
Steady State ◽  
Rise Time ◽  
Pid Controller ◽  
Simple Algorithm ◽  
Good Control ◽  
Settling Time ◽  
Experimental Result ◽  
Pid Tuning ◽  
Tuning Methods ◽  
State Error

PID controller is the most popular feedback controller in industry. It has been known that PID controller is capable to provide a good control performance despite having a simple algorithm and easy to understand. However, the most common problem of using this control system is that it is difficult to stipulate the most appropriate constants to each controller or tuning. This project implemented advanced PID tuning which involves several tuning methods to acquire best performance on system or plant which is volatile or critically stable such as controlling height levitation pingpong ball. The tuning methods used and compared were Ziegler-Nichols (ZN) and Chien-Hrones-Reswick (CHR). Tuning process and monitoring were performed in real time using Simulink-Arduino. Based on experimental result, CHR method gave better performance compared to ZN method. ZN resulted in overshoot, rise time, settling time, and steady state error of 48%, 0.85s, 3.8s, and ±2cm respectively, while CHR method resulted in overshoot, rise time, settling time, and steady state error of 14%, 1.15s, 1.4s, and ±1cm respectively.

scholarly journals Two-Stage Control Design of a Buck Converter/DC Motor System without Velocity Measurements via aΣ−Δ-Modulator

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
R. Silva-Ortigoza ◽  
J. R. García-Sánchez ◽  
J. M. Alba-Martínez ◽  
V. M. Hernández-Guzmán ◽  
M. Marcelino-Aranda ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Motor System ◽  
Control Design ◽  
Input Voltage ◽  
Dc Motor ◽  
Power Converter ◽  
Buck Converter ◽  
Two Stage ◽  
Second Stage ◽  
Flatness Property

This paper presents a two-stage control design for the “Buck power converter/DC motor” system, which allows to perform the sensorless angular velocity trajectory tracking task. The differential flatness property of the DC-motor model is exploited in order to propose a first-stage controller, which is designed to achieve the desired angular velocity trajectory. This controller provides the voltage profiles that must be tracked by the Buck converter. Then, a second-stage controller is meant to assure the aforementioned. This controller is based on flatness property of the Buck power converter model, which provides the input voltage to the DC motor. Due to the fact that the two-stage controller proposed uses the average model of the system, as a practical and effective implementation of this controller, aΣ − Δ-modulator is employed. Finally, in order to verify the control performance of this approach, numerical simulations are included.

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