scholarly journals Speed Control of DC Motor using PID Controller FED H-Bridge

2020 ◽  
Vol 9 (10) ◽  
pp. 274-282
Keyword(s):  
Steady State ◽  
Transient Response ◽  
Pid Controller ◽  
Dc Motor ◽  
Pi Controller ◽  
Pd Controller ◽  
Integral Controller ◽  
The Stability ◽  
Proportional Controller ◽  
State Error

In the present scenario, DC motor is widely used in industries. So, if DC motor is used for industrial purpose, the controlling is necessary. But there are various methods to control any system or plant such as via Proportional controller (P), Integral controller (I), Derivative controller (D), PI controller, PD controller, PID controller. Each controller is used on the basis of requirement. Proportional controller reduces the rise time, improves the steady state accuracy, and reduces the steady state error. But Integral controllers eliminate the steady state error but the process is too slow so it produces the worse transient response. Derivative controller improves the transient response, reduces the overshoots and improves the stability. So, for obtaining the accurate output of any plant, PID controller is best for many others. And for operating the DC motor in forward and backward both, H-bridge MOSFET is also used in this dissertation. Any other power electronics device is not suitable.

scholarly journals Adaptive neural PD controllers for mobile manipulator trajectory tracking

2021 ◽  
Vol 7 ◽  
pp. e393
Author(s):  
Jesus Hernandez-Barragan ◽  
Jorge D. Rios ◽  
Javier Gomez-Avila ◽  
Nancy Arana-Daniel ◽  
Carlos Lopez-Franco ◽  
...  
Keyword(s):  
Steady State ◽  
Pid Controller ◽  
Poor Performance ◽  
Industrial Applications ◽  
Mobile Manipulator ◽  
Pid Controllers ◽  
Mobile Manipulators ◽  
Pd Controller ◽  
Adaptive Neuron ◽  
State Error

Artificial intelligence techniques have been used in the industry to control complex systems; among these proposals, adaptive Proportional, Integrative, Derivative (PID) controllers are intelligent versions of the most used controller in the industry. This work presents an adaptive neuron PD controller and a multilayer neural PD controller for position tracking of a mobile manipulator. Both controllers are trained by an extended Kalman filter (EKF) algorithm. Neural networks trained with the EKF algorithm show faster learning speeds and convergence times than the training based on backpropagation. The integrative term in PID controllers eliminates the steady-state error, but it provokes oscillations and overshoot. Moreover, the cumulative error in the integral action may produce windup effects such as high settling time, poor performance, and instability. The proposed neural PD controllers adjust their gains dynamically, which eliminates the steady-state error. Then, the integrative term is not required, and oscillations and overshot are highly reduced. Removing the integral part also eliminates the need for anti-windup methodologies to deal with the windup effects. Mobile manipulators are popular due to their mobile capability combined with a dexterous manipulation capability, which gives them the potential for many industrial applications. Applicability of the proposed adaptive neural controllers is presented by simulating experimental results on a KUKA Youbot mobile manipulator, presenting different tests and comparisons with the conventional PID controller and an existing adaptive neuron PID controller.

scholarly journals Modifications of Control Loop to Improve the Depth Response of Autonomous Underwater Vehicles

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Sheng-Ping Hsu ◽  
Tzong-Shi Liu
Keyword(s):  
Steady State ◽  
Transient Response ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Vertical Plane ◽  
Control Loop ◽  
Depth Control ◽  
Integral Controller ◽  
Proportional Controller ◽  
Depth Response

During a constant depth maneuver of an autonomous underwater vehicle (AUV), its pitch attitude and stern plane deflections create forces and moments to achieve equilibrium in the vertical plane. If an AUV has a proportional controller only in its depth control loop, then different weights or centers of gravity will cause different steady-state depth errors at trimmed conditions. In general, a steady-state depth error can be eliminated by adding an integral controller in the depth control loop. However, an improper integrator may lead to a bad transient response, even though the steady-state depth error can finally be eliminated. To remove the steady-state depth error, this study proposes methods that adjust the depth command and add a switching integral controller in the depth control loop. Simulation results demonstrate that the steady-state depth error can be eliminated and the transient response can be improved.

scholarly journals Performance Evaluation of Balancing Bicopter using P, PI, and PID Controller

2019 ◽  
Vol 11 (2) ◽  
pp. 44-49
Author(s):  
Esa Apriaskar ◽  
Fahmizal Fahmizal ◽  
Nur Azis Salim ◽  
Dhidik Prastiyanto
Keyword(s):  
Performance Evaluation ◽  
Steady State ◽  
Pid Controller ◽  
Performance Test ◽  
Pulse Width Modulation ◽  
Pi Controller ◽  
Settling Time ◽  
Proportional Integral ◽  
Rising Time ◽  
State Error

Due to potential features of unmanned aerial vehicles for society, the development of bicopter has started to increase. This paper contributes to the development by presenting a performance evaluation of balancing bicopter control in roll attitude. It aims to determine the best controller structure for the balancing bicopter. The controller types evaluated are based on Ziegler-Nichols tuning method; they are proportional (P), proportional-integral (PI), and proportional-integral-derivative (PID) controllers. Root locus plot of the closed-loop balancing bicopter system is used to decide the tuning approach. This work considers a difference in pulse-width-modulation (PWM) signal between the left and right rotors as the signal control and bicopter angle in roll movement as the output. Parameters tuned by the method are Kp, Ti, and Td which is based on the ideal PID structure. The performance test utilizes rising time, settling time, maximum overshoot, and steady-state error to determine the most preferred controller. The result shows that PI-controller has the best performance among the other candidates, especially in maximum overshoot and settling time. It reaches 8.34 seconds in settling time and 3.71% in maximum overshoot. Despite not being the best in rising time and resembling PID-controller performances in steady-state error criteria, PI-controller remains the most preferred structure considering the closeness of the response to the desired value.

scholarly journals Evaluasi Performa Fuzzy Logic Controller untuk mengatur kecepatan Motor DC Penguatan Terpisah

2020 ◽  
Vol 12 (2) ◽  
pp. 100-110
Author(s):  
Muhammad Aditya Ardiansyah ◽  
Renny Rakhmawati ◽  
Hendik Eko Hadi Suharyanto ◽  
Era Purwanto
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Duty Cycle ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Boost Converter ◽  
Voltage Source ◽  
Single Output ◽  
Multiple Input ◽  
State Error

Beragamnya metode yang ditawarkan oleh fuzzy logic kontroller membuat sebagaian orang meneliti mengenai perbedaan metode inferensi yang digunakan oleh fuzzy logic controller. Sejauh ini terdapat tiga metode fuzzy logic kontroller yang telah dikembangkan yaitu Mamdani, Sugono dan Sukamoto. Pada jurnal ini penggunaan fuzzy logic kontroller akan dievaluasi dengan menggunakan motor dc penguat terpisah sebagai beban untuk melakukan pengaturan kecepatan motor dc. Pada paper ini tujuan utamanya adalah dapat mengendalikan kecepatan dari motor DC Penguatan Terpisah dengan mengatur tegangan jangkar dari motor tersebut. DC motor merupakan salah satu jenis motor memiliki banyak aplikasi dan memiliki kemudahan untuk mengatur kecepatan pada motor tersebut. Logika fuzzy yang digunakan pada studi ini adalah inferensi sugeno dimana dengan konfigurasi Multiple Input Single Output (MiSo). Dimana input berupa error dan perubahan error dan output berupa duty cycle dikarenakan yang dikendalikan oleh logika fuzzy adalah Boost Converter selaku controlled voltage source. Target pada jurnal ini adalah dari kecilnya nilai steady – state error dan minimnya osilasi sehingga mampu membuat sistem lebih stabil. Pada studi ini, Hasil pengujian dilakukan dengan menggunakan Simulink by Matlab dengan Hasil pengujian berupa error rata rata sebesar 5.36%.

A mathematical model of a brushed DC motor system

2021 ◽  
Vol 2 (2) ◽  
pp. 60-68
Author(s):  
N. N. A. Rahman ◽  
N. M. Yahya
Keyword(s):  
Mathematical Model ◽  
Steady State ◽  
Motor System ◽  
Dc Motor ◽  
Positioning System ◽  
Pd Controller ◽  
Trial And Error ◽  
Trial And Error Method ◽  
Low Torque ◽  
Error Method

Mathematical model has been proposed for some system that involves a brushed DC motor and it is widely used in industry. Brushed DC motor ideals for applications with a low- torque, manage to change pace or speed and it is widely used in many applications such as x-y table positioning system, conveyor systems and other system that required to use the features that brushed DC motor have. Mathematical model of brushed DC motor in order to verify the performance of the DC motor. In this paper, mathematical model of brushed DC motor will be derived from a brushed DC motor circuit that consist of two parts that are electrical and mechanical part. To validate the functionality of mathematical model, the performance of the brushed DC motor without any controller will be compared with the brushed DC motor with the presence of PI-PD controller that will be tuned by trial-and-error method. Performances of both brushed DC motor with and without controller will be compared in terms of transient response which are, rise time, Tr, settling time, Ts, steady state error, ess and lastly percentage overshoot. At the end of the study, the brushed DC motor with PI-PD controller show a better performance compared to the brushed DC motor without any controller.

scholarly journals Evaluation of SIPIC01 and SIPIC02 on Motor Speed Control

2018 ◽  
Vol 152 ◽  
pp. 02010
Author(s):  
Kah Kit Wong ◽  
Choon Lih Hoo ◽  
Mohd Hardie Hidayat Mohyi
Keyword(s):  
Control System ◽  
Steady State ◽  
Dynamic Performance ◽  
Pi Controller ◽  
Settling Time ◽  
Motor Speed ◽  
Proportional Integral ◽  
Integral Controller ◽  
Proportional Integral Controller ◽  
Decoupling Effect

Due to its simplicity, Proportional-Integral (PI) controller still remains as the widely used controller for motor speed control system. However, PI controller exhibits windup phenomenon when the motor operates in a saturated state, which may cause degradation to the control system. In order to overcome the windup phenomenon, many researches have introduced various types of anti-windup methods such as the Conditioning Technique (CI), Tracking Back Calculation (TBC), Integral State Prediction (ISP), Steady-state Integral Proportional Integral Controller-01 (SIPIC01) and Steady-state Integral Proportional Integral Controller-02 (SIPIC02). These are anti-windup techniques with integral control switching mechanism, coupling of proportional gain, kp, and integral gain, ki. Due to the coupled kp and ki, tuning motor performance is a difficult task with short settling time without experiencing overshoot. SIPIC01 and SIPIC02 are robust anti-windup methods without a switching mechanism and exhibit decoupling feature. SIPIC01 and SIPIC02 have shown better dynamic performance compared to CI, TBC and ISP. However, SIPIC01 has not been compared to SIPIC02 in terms of their decoupling effect flexibility and dynamic performance. The decoupling effect was verified using MATLAB simulation, while the performance analysis was verified through hardware simulation and testing by using Scilab. The results obtained from the simulation showed that both SIPIC01 and SIPIC02 consist of decoupling features that allow a performance with coexistence of zero or minimum overshoot with short settling time. However, SIPIC02 consists of longer rise and settling time as compared to SIPIC01. Therefore, it can be concluded that SIPIC01 is better than SIPIC02 in term of dynamic performance.

scholarly journals Performance enhancement of split-phase induction motor by using fuzzy-based PID controller

2019 ◽  
Vol 70 (2) ◽  
pp. 103-112
Author(s):  
Mohamed I. Abdelwanis ◽  
Ragab A. El-Sehiemy
Keyword(s):  
Steady State ◽  
Induction Motor ◽  
Pid Controller ◽  
Pulse Width Modulation ◽  
Performance Enhancement ◽  
Fine Tuning ◽  
Motor Speed ◽  
Pumping System ◽  
Total Oscillation ◽  
State Error

Abstract This paper presents control and analysis of a split-phase induction motor (SPIM) to drive a centrifugal pumping system. An optimized proportional- integral and derivative (PID) controller, that is capable with a vector closed-loop split-phase induction motor control, is presented and its simulation results are discussed. The fine-tuning procedure is employed for fuzzy PID (FPID) controller parameters in order to sustain the motor speed at the predefined reference values. To assess the performance of the competitive controllers, conventional PID (CPID) and FPID, four operational indices for are suggested for measure the capability of the two controllers. These indices involve individual steady state error (ISSE) for each operating period, total steady state error (TSSE) for overall loading cycle, Individual oscillation index (IOI) and Total oscillation index (TOI), in order to measure the capability of the FPID compared with CPID. The performance of the SPIM accomplished with these performance indices is checked and tested on high and low speed levels. Pulse width modulation (PWM) based simulation studies were employed for SPIM using MATLAB/SIMULINK software. The results show that the overall performance of the SPIM operated with vector control that is tuned by FPID is enhanced compared with CPID.

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