scholarly journals DC Motor Speed Control using Internal Model Controller: Industrial Transformation Strategy

2020 ◽  
Vol 9 (5) ◽  
pp. 300-306
Keyword(s):  
Transfer Function ◽  
Pid Control ◽  
Pid Controller ◽  
Internal Model ◽  
Dc Motor ◽  
Motor Speed ◽  
Matlab Simulink ◽  
Dc Motors ◽  
Control Schemes ◽  
Motor Model

In developed nations, industries are made to function at control engineering costs via the use of appropriate control schemes for dc motors. This paper introduces the role played by dc motors in industries thereby necessitating the analysis and performance validation of dc motor in Internal Model Control (IMC) scheme as against the Proportional– Integral–Derivative (PID) control schemes that is widely used in most industries. Theories on dc motor model, PID and IMC controller were detailed to paved the way for the methodical approach of getting specifications and transfer function for a typical dc motor (model RMCS-3011). Matlab/Simulink software was then used to tune the PID controller for the purpose of finding the values of PID gains that meets the design requirements to achieve best performance, thereby enabling the simulation of the PID controller. Using Matlab m-file environment, IMC controller transfer function was generated and simulated. The IMC controller transfer function aimed at achieving a unity gain that tracks the set-point was approximately realized. In the realization process, it was obvious that a filter is required. The aim of this work is to evaluate the performance of the IMC controller over PID controller. Simulated plots in Matlab-Simulink using the PID gains for the PID controller, and time constants and filter order for the IMC were presented. The quantitative results of the IMC method when compared with that of PID control provides a commendable performance. However, the performance in terms of rise time is small and preferred with the use of Matlab-Simulink tuned PID controller. Conclusively, IMC controller would be the preferred controller where the robustness and accuracy of the dc motor speed control counts more than faster response

scholarly journals Design and implementation speed control system of DC Motor based on PID control and matlab simulink

2020 ◽  
Vol 11 (1) ◽  
pp. 127
Author(s):  
Salman Jasim Hammoodi ◽  
Kareem Sayegh Flayyih ◽  
Ahmed Refaat Hamad
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Speed Control ◽  
Dc Motor ◽  
Motor Speed ◽  
Matlab Simulink ◽  
Dc Motors ◽  
Electronic Controller

<span>In this paper, we first write a description of the operation of DC motors taking into account which parameters the speed depends on thereof. The PID (Proportional-Integral-Derivative) controllers are then briefly described, and then applied to the motor speed control already described , that is, as an electronic controller (PID), which is often referred to as a DC motor. The closed loop speed control of a Brush DC motor is developed applying the well-known PID control algorithm. The objective of this work is to designed and simulate a new control system to keep the speed of the DC motor constant before variations of the load (disturbances), automatically depending to the PID controller. The system was designed and implementation by using MATLAB/SIMULINK and  DC motor.</span>

Straight-Move Robot Control System with LabView-Based Proportional Integral Derivative (PID) Control

2019 ◽  
Vol 3 (2) ◽  
pp. 13-24
Author(s):  
Andrean George W
Keyword(s):  
Pid Control ◽  
Rotational Speed ◽  
Pid Controller ◽  
Dc Motor ◽  
Motor Speed ◽  
Labview Software ◽  
Dc Motors ◽  
Dc Motor Control ◽  
Process System ◽  
Interface Devices

Abstract - Control and monitoring of the rotational speed of a wheel (DC motor) in a process system is very important role in the implementation of the industry. PWM control and monitoring for wheel rotational speed on a pair of DC motors uses computer interface devices where in the industry this is needed to facilitate operators in controlling and monitoring motor speed. In order to obtain the best controller, tuning the Integral Derifative (PID) controller parameter is done. In this tuning we can know the value of proportional gain (Kp), integral time (Ti) and derivative time (Td). The PID controller will give action to the DC motor control based on the error obtained, the desired DC motor rotation value is called the set point. LabVIEW software is used as a PE monitor, motor speed control. Keyword : LabView, Motor DC, Arduino, LabView, PID.

DC Motor Speed Control Using Hybrid PID-Fuzzy with ITAE Polynomial Initiation

2019 ◽  
Vol 3 (1) ◽  
pp. 7
Author(s):  
Hari Wibawa ◽  
Oyas Wahyunggoro ◽  
Adha Imam Cahyadi
Keyword(s):  
Transfer Function ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Industrial Sector ◽  
Pid Controllers ◽  
Motor Speed ◽  
Dc Motors ◽  
Working Parameters ◽  
Motor Operation ◽  
Load Simulation

DC motors are widely applied in industrial sector, especiallyprocesses of automation and robotics. Given its role in the sector, DC motor operation needs to be optimized. One of optimization steps is controlling speed using several control methods, for example conventional PID methods, PID Ziegler Nichols, PID based on ITAE polynomials, and Hybrid PID-Fuzzy. From these methods, Hybrid PID-Fuzzy was chosen as a method to be proposed in this paper because it can anticipate shortcomings of PID controllers and fuzzy controllers so as to produce system responses that are fast and adaptive to errors. This paper aimed to design a Hybrid PID-Fuzzy system based on ITAE polynomials (Hybrid-ITAE), to analyze its performance parameters values, and tp compare Hybrid-ITAE performance with conventional PID method. Working parameters being reviewed include overshoot, rise time, settling time, and ITAE. First of all, JGA25-370 DC motor was modeled in a form of a third order transfer function equation. Based on the transfer function, PID parameters were calculated using PID Output Feedback and ITAE polynomial methods. The best ITAE polynomial PID controllers were then be combined with a Fuzzy Logic Controller to form a Hybrid-ITAE system. Simulation and experimental stages were carried out in two conditions, namely no load and loaded. Simulation and experimental results showed that Hybrid-ITAE (l = 0.85) was the best controller for no-load simulation conditions. For loaded simulation Hybrid-ITAE (l=1) was a better controller. In no-loads experiment, the best controller was Hybrid PID-Ziegler Nichols, while for loaded condition the best controller was Hybrid PID-Ziegler Nichols.

The Controller Design for DC Motor Speed System Based on Improved Fuzzy PID

2012 ◽  
Vol 466-467 ◽  
pp. 1246-1250 ◽  
Author(s):  
Bin Ma ◽  
Qing Bin Meng ◽  
Feng Yu ◽  
Zhong Hua Han ◽  
Chang Tao Wang
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Controller Design ◽  
Fast Response ◽  
Dc Motor ◽  
Fuzzy Pid ◽  
Motor Speed ◽  
Fuzzy Pid Control ◽  
Fuzzy Control Algorithm

In this paper, a controller is designed based on improved fuzzy PID to solve the problem that the dc motor performance of speed and dynamic is poor when using the conventional PID controller for the lack of adaptive capacity of the controller parameters. The improved fuzzy control algorithm is used for the tuning of PID controller to get good speed performances, which automatically adjust the parameter of PID controller according to the motor speed. The simulation results show that the improved fuzzy PID control with the advantages of fast response, small overshoot and strong anti-interference capability can effectively improve the dynamic characteristics and steady state accuracy.

scholarly journals PID-Based Design of DC Motor Speed Control

2021 ◽  
Vol 2 (1) ◽  
pp. 7
Author(s):  
Irfan Irhamni ◽  
Riries Rulaningtyas ◽  
Riky Tri Yunardi
Keyword(s):  
Transient Response ◽  
Pid Controller ◽  
Speed Control ◽  
Dc Motor ◽  
System Response ◽  
Motor Speed ◽  
Proportional Integral ◽  
Response Data ◽  
Dc Motors

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.

Optimal Control of DC Motors Using PSO Algorithm for Tuning PID Controller

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Arnisa Myrtellari ◽  
Petrika Marango ◽  
Margarita Gjonaj
Keyword(s):  
Pid Controller ◽  
High Performance ◽  
Industrial Process ◽  
Speed Control ◽  
Pso Algorithm ◽  
Dc Motor ◽  
Step Response ◽  
Pid Controllers ◽  
Motor Speed ◽  
Dc Motors

The DC motors are widely used in the mechanisms that require control of speed. Different speed can be obtained by changing the field voltage and the armature voltage. The classic PID controllers are widely used in industrial process for speed control. But they aren’t suitable for high performance cases, because of the low robustness of PID controller. So many researchers have been studying various new control techniques in order to improve the system performance and tuning PID controllers. This paper presents particle swarm optimization (PSO) method for determining the optimal PID controller parameters to find the optimal parameters of DC Motor speed control system. The DC Motor system drive is modeled in MATLAB/SIMULINK and PSO algorithm is implemented using MATLAB toolbox. The results obtained through simulation show that the proposed controller can perform an efficient search for the optimal PID controller. Simulation results show performance improvement in time domain specifications for a step response (no overshoot, minimal rise time, steady state error = 0).

Motor DC Speed Adjustment By Propotional Integral Derivative (PID) Based on LabView

2016 ◽  
Vol 4 (2) ◽  
pp. 13-24
Author(s):  
Alifa Restu Janwar Wiriawan
Keyword(s):  
Pid Controller ◽  
Rotation Speed ◽  
Dc Motor ◽  
Motor Speed ◽  
Labview Software ◽  
Dc Motors ◽  
Time Integral ◽  
Parameters Tuning ◽  
And Control ◽  
Speed Adjustment

Abstract - DC motors are widely used in small and large industries. DC motor speed is often unstable due to outside interference and changes in the parameters of the fabrication so it is necessary to design a controller. Motor DC speed adjustment and monitoring is a crucial system as it i implemented in industrial. This motor DC speed adjustment and monitoring using computer interface where in industial this system will support operator for adjusting and monitoring motor speed. For acquiring best control parameters, tuning is needed for acquiring best Proportional Integral Derivative(PID) value. This tuning is used for find the best proportional gain, time integral, derivative time. PID controller will give a better control respond to the DC Motor based on the error, the DC motor rotation speed needed is called Setpoint. The labview software used as an interface of monitor and control. Keyword : LabView, Motor DC, Arduino, Ouptocoupler, Computer

Design and application of an optimally tuned PID controller for DC motor speed regulation via a novel hybrid Lévy flight distribution and Nelder–Mead algorithm

2021 ◽  
pp. 014233122110196
Author(s):  
Davut Izci
Keyword(s):  
Pid Controller ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Absolute Error ◽  
Dc Motor ◽  
Cuckoo Search Algorithm ◽  
Lévy Flight ◽  
Motor Speed ◽  
Levy Flight ◽  
Speed Regulation

This paper deals with the design of an optimally performed proportional–integral–derivative (PID) controller utilized for speed control of a direct current (DC) motor. To do so, a novel hybrid algorithm was proposed which employs a recent metaheuristic approach, named Lévy flight distribution (LFD) algorithm, and a simplex search method known as Nelder–Mead (NM) algorithm. The proposed algorithm (LFDNM) combines both LFD and NM algorithms in such a way that the good explorative behaviour of LFD and excellent local search capability of NM help to form a novel hybridized version that is well balanced in terms of exploration and exploitation. The promise of the proposed structure was observed through employment of a DC motor with PID controller. Optimum values for PID gains were obtained with the aid of an integral of time multiplied absolute error objective function. To verify the effectiveness of the proposed algorithm, comparative simulations were carried out using cuckoo search algorithm, genetic algorithm and original LFD algorithm. The system behaviour was assessed through analysing the results for statistical and non-parametric tests, transient and frequency responses, robustness, load disturbance, energy and maximum control signals. The respective evaluations showed better performance of the proposed approach. In addition, the better performance of the proposed approach was also demonstrated through experimental verification. Further evaluation to demonstrate better capability was performed by comparing the LFDNM-based PID controller with other state-of-the-art algorithms-based PID controllers with the same system parameters, which have also confirmed the superiority of the proposed approach.

scholarly journals Parameter Estimation of DC Motor using Adaptive Transfer Function Based on Nelder-Mead Optimisation

2018 ◽  
Vol 9 (3) ◽  
pp. 696 ◽  
Author(s):  
Byamakesh Nayak ◽  
Sangeeta Sahu ◽  
Tanmoy Roy Choudhury
Keyword(s):  
Experimental Data ◽  
Transfer Function ◽  
Adaptive Method ◽  
Dc Motor ◽  
Model Parameters ◽  
Current Response ◽  
Adaptive Model ◽  
Unknown Parameters ◽  
Dc Motors ◽  
Estimated Parameters

<p>This paper explains an adaptive method for estimation of unknown parameters of transfer function model of any system for finding the parameters. The transfer function of the model with unknown model parameters is considered as the adaptive model whose values are adapted with the experimental data. The minimization of error between the experimental data and the output of the adaptive model have been realised by choosing objective function based on different error criterions. Nelder-Mead optimisation Method is used for adaption algorithm. To prove the method robustness and for students learning, the simple system of separately excited dc motor is considered in this paper. The experimental data of speed response and corresponding current response are taken and transfer function parameters of  dc motors are adapted based on Nelder-Mead optimisation to match with the experimental data. The effectiveness of estimated parameters with different objective functions are compared and validated with machine specification parameters.</p>

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