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 A Heuristics-Based Parthenogenetic Algorithm for the VRP with Potential Demands and Time Windows

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Chenghua Shi ◽  
Tonglei Li ◽  
Yu Bai ◽  
Fei Zhao
Keyword(s):  
Genetic Algorithm ◽  
Time Windows ◽  
Computation Time ◽  
Routing Problem ◽  
Split Delivery ◽  
Soft Time Windows ◽  
Comparison Results ◽  
Potential Demand ◽  
The Cost

We present the vehicle routing problem with potential demands and time windows (VRP-PDTW), which is a variation of the classical VRP. A homogenous fleet of vehicles originated in a central depot serves customers with soft time windows and deliveries from/to their locations, and split delivery is considered. Also, besides the initial demand in the order contract, the potential demand caused by conformity consuming behavior is also integrated and modeled in our problem. The objective of minimizing the cost traveled by the vehicles and penalized cost due to violating time windows is then constructed. We propose a heuristics-based parthenogenetic algorithm (HPGA) for successfully solving optimal solutions to the problem, in which heuristics is introduced to generate the initial solution. Computational experiments are reported for instances and the proposed algorithm is compared with genetic algorithm (GA) and heuristics-based genetic algorithm (HGA) from the literature. The comparison results show that our algorithm is quite competitive by considering the quality of solutions and computation time.

Tuning pi untuk stabilitas kecepatan putaran motor induksi 1 fasa pada mesin penyaring bubur kedelai

JURNAL ELTEK ◽  
2020 ◽  
Vol 18 (2) ◽  
pp. 48
Author(s):  
Achmad Afandi ◽  
Mila Fauziyah Fauziyah ◽  
Denda Dewatama
Keyword(s):  
Steady State ◽  
Conventional Method ◽  
Rise Time ◽  
Settling Time ◽  
Screening Process ◽  
Pi Method ◽  
Filter Tube ◽  
Manual Methods ◽  
No Innovation

Perusahaan tahu di Indonesia pada umumnya, masih menggunakan cara manual, dalam pembuatannya khususnya pada proses penyaringan bubur kedelai yang membutuhkan waktu yang, lama. Hal tersebut didasarkan pada belum ditemukannya mesin pemeras bubur kedelai. Dewasa ini telah ditemukan inovasi mesin, pemeras bubur kedelai yang bisa meningkatkan kuantitas dan, kualitas produksi dibanding dengan cara manual. Penerapan, teknologinya adalah bubur kedelai diletakkan pada tabung, penyaring kemudian tabung tersebut diputar menggunakan motor, yang dihubungkan melalui fanbelt dan pulley. Ketika motor, diputar, tabung akan ikut berputar sehingga menimbulkan gerak, sentrifugal dimana air kedelai akan terpisah dari ampas. Kecepatan putar motor yang dikontrol adalah 750 rpm dengan, nilai Kp 0,108 , Ki 0,83 sehingga mendapatkan air sari kedelai, sebesar 1,3 liter dengan perbandingan 1 kg kedelai : 1 liter air. Parameter dari penerapan metode PI ini meliputi rise time 4 detik, settling time 4,5 detik, overshoot 0 dan error steady state 2,4%. Dengan penerapan metode PI maka hasil perasan kedelai dari, peyaringan menjadi semakin banyak dan waktu yang dibutuhkan 4 menit lebih singkat dibandingkan dengan cara konvensional.   Tofu companies in Indonesia generally still use manual methods in their manufacture, especially in the soybean slurry screening process which certainly has many disadvantages such as extortion time needed. This was based on the fact that there was no innovation in the soybean pulp squeezer. Currently, it has been found that innovations of soybean slurry machines can increase the quantity and quality of production compared to manual methods. The application of the technology is soybean slurry placed on the filter tube then the tube is rotated using a motor connected with fanbelt and pulley. When the motor is rotated, the tube will rotate, causing centrifugal motion where the soybean water will separate from the pulp. The speed of the motor controlled in 750 rpm with the Kp 0,108, Ki 0,83, to get soybean essence up to 1,3 liter within comparison 1 kg soybean : 1 liter water. The parameter PI method including rise time 4 second, settling time 4,5 second, overshoot 0 and error steady state 2,4%. By applying PI method, the result of filtering is 4 minute faster comparing with conventional method.

scholarly journals Implementing optimization of PID controller for DC motor speed control

2021 ◽  
Vol 23 (2) ◽  
pp. 657
Author(s):  
Yasir G. Rashid ◽  
Ahmed Mohammed Abdul Hussain
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Optimization Technique ◽  
Speed Control ◽  
Optimization Method ◽  
Dc Motor ◽  
Motor Speed ◽  
Tuning Method ◽  
Pid Tuning ◽  
Dc Motor 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.

Optimizing the Manufacturing of Laminated Dies

2009 ◽  
Author(s):  
Hossein Ahari ◽  
Amir Khajepour ◽  
Sanjeev Bedi
Keyword(s):  
Genetic Algorithm ◽  
Surface Quality ◽  
Laser Cutting ◽  
Production Costs ◽  
Layer By Layer ◽  
Promising Technology ◽  
Cooling Channels ◽  
Minimum Surface ◽  
The Cost

Laminated tooling where parts are manufactured layer by layer is a promising technology. It can help to reduce production costs and make complex tools with conformed cooling channels. Laminated tooling is based on taking sheets of metal and laser cutting profiles on them before stacking them to produce the final product. If the sheets are thin, the surface quality of final product will be good; however the cost of laser cut is increased in this case. Therefore, finding the optimum set of layers thicknesses to have the minimum surface jaggedness and the number of slices at the same is the aim of this research. A modified version of Genetic Algorithm is used for optimization purpose.

scholarly journals OPTIMIZATION OF 2D LATTICE CELLULAR AUTOMATA FOR PSEUDORANDOM NUMBER GENERATION

2005 ◽  
Vol 16 (03) ◽  
pp. 479-500 ◽  
Author(s):  
MARIE THERESE ROBLES QUIETA ◽  
SHENG-UEI GUAN
Keyword(s):  
Genetic Algorithm ◽  
Cellular Automata ◽  
Neighborhood Characteristics ◽  
Structure And Properties ◽  
Pseudorandom Number Generation ◽  
The Cost ◽  
Number Of Cells ◽  
Better Than ◽  
2D Array

This paper proposes a generalized approach to 2D CA PRNGs — the 2D lattice CA PRNG — by introducing vertical connections to arrays of 1D CA. The structure of a 2D lattice CA PRNG lies in between that of 1D CA and 2D CA grid PRNGs. With the generalized approach, 2D lattice CA PRNG offers more 2D CA PRNG variations. It is found that they can do better than the conventional 2D CA grid PRNGs. In this paper, the structure and properties of 2D lattice CA are explored by varying the number and location of vertical connections, and by searching for different 2D array settings that can give good randomness based on Diehard test. To get the most out of 2D lattice CA PRNGs, genetic algorithm is employed in searching for good neighborhood characteristics. By adopting an evolutionary approach, the randomness quality of 2D lattice CA PRNGs is optimized. In this paper, a new metric, #rn is introduced as a way of finding a 2D lattice CA PRNG with the least number of cells required to pass Diehard test. Following the introduction of the new metric #rn, a cropping technique is presented to further boost the CA PRNG performance. The cost and efficiency of 2D lattice CA PRNG is compared with past works on CA PRNGs.

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 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

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.

ANFIS based Control Scheme for Binary Distillation Column

2017 ◽  
Vol 12 (1) ◽  
Author(s):  
Amit Kumar Singh ◽  
Barjeev Tyagi ◽  
Vishal Kumar
Keyword(s):  
Flow Rate ◽  
Performance Indicators ◽  
Rise Time ◽  
Disturbance Rejection ◽  
Distillation Column ◽  
Settling Time ◽  
Reference Tracking ◽  
Composition Control ◽  
Control Scheme ◽  
Process Composition

Abstract In distillation process, composition control is very important. A continuous column has to be operated as precisely as possible to meet the purity specifications. In this work, ANFIS controllers are designed to control the methanol composition in BDC. The controller controls the methanol composition in BDC by the variation of reflux flow-rate and reboiler heat duty. Two separate ANFIS controllers namely: ANFIS A and ANFIS B are designed for the reflux flow-rate and the reboiler heat duty respectively. Each ANFIS controller has three inputs. The performance of this ANFIS control scheme is compared with NN-IMC control scheme on the basis of considered performance indicators (rise time, settling time, MSE). Performance of the ANFIS control scheme is evaluated for reference tracking and disturbance rejection cases. A perturbation of +10 % is incorporated in feed flow-rate for disturbance rejection case. In case of reference tracking, the obtained result shows that there is an improvement of 7 % in the settling time whereas, 14 % improvement in MSE with ANFIS scheme as compared to NN-IMC scheme. In case of disturbance rejection, the obtained result shows that there is an improvement of 14 % in the rise time, 41 % improvement in settling time whereas, 7 % improvement in MSE with ANFIS scheme as compared to NN-IMC scheme.

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