Speed Regulation Of DC Motor Research Articles

Investigating PID Controller Effectiveness: An Extensive Analysis and Wide-ranging Uses

This study offers an in-depth investigation of the performance of proportional-integral-derivative (PID) controllers, providing an extensive evaluation and analyzing a wide range of applications. PID controllers, essential feedback mechanisms in various domains, are recognized as foundational instruments in control systems. This study evaluates PID controllers in in scenarios such as DC motor speed regulation, power system stability, Automatic Voltage Regulator (AVR) performance optimization, time delay processes, load frequency management, DC drive control, systematic process stability, and their developments in industrial control. The purpose of the study is to highlight the adaptability and effectiveness of PID controllers in contemporary control systems, including how artificial intelligence (AI) can be integrated into PID controller tuning.

A regulatory power split strategy for energy management with battery and ultracapacitor

Electric vehicle batteries face fast degradation due to the high frequency of charging/discharging cycles and great peak power demands. Lifetime, continuity of supply and power density of these batteries affect the performance of electric vehicles (EVs). Hybrid energy storage systems (HESS) offers a feasible solution by incorporating other energy storage elements like ultra-capacitor (UC) along with battery. Their combination provides higher efficiency and better performance in terms energy/power density. UC can behave like a power buffer when the EV is accelerating and regenerating. The HESS needs a controller that can split the available power between different sub systems as per demand. This paper presents a regulatory control strategy useful in HESS with battery and UC for the speed regulation of a brushless DC (BLDC) motor using a 3-port bidirectional DC-DC converter. The regulatory control strategy monitors the state of charge (SOC) of UC and a fuzzy logic controller regulates the power flow between HESS and the motor. Simulation in MATLAB validates the efficacy of the strategy. Simulation results and hardware evaluation confirm that the regulatory control scheme is effective in splitting the available power according to the load demand and achieves better energy efficiency.

Comparative study on PID for DC motor speed regulation

Comparative study on PID for DC motor speed regulation

Performance Comparison of PID and LQR Control for DC Motor Speed Regulation

The aim of this research paper is to provide a comprehensive performance comparison of proportional-integral-derivative (PID) and linear quadratic regulator (LQR) control methods for DC motor speed regulation. First, a mathematical description of a permanent magnet DC motor model is offered, followed by the control systems PID and LQR, and finally, findings and discussions of whether the use of both control strategies is advantageous for DC. The results demonstrate how well LQR performs under various operating situations when compared to PID control. Engineers and researchers looking to optimize control system design for DC motor speed regulation may benefit a lot from the results of this study.

Small Fault Diagnosis With Gap Metric

This article proposes a novel data-driven gap metric fault detection and isolation (FDI) approach for small multiplicative fault. First, the scheme of model-based fault classification and gradation is developed by means of the gap metric. Subsequently, the data-driven gap metric is utilized to detect a small fault via the mechanism model. Furthermore, fault detectability criterion is derived with the help of the developed fault detectability indicator. The relationship between fault detectability indicator and fault detection index is then investigated to analyze fault detection performance. To enhance fault isolability, a solution of appropriate fault cluster center model and radius is provided under the condition of fault isolation. Third, a gap metric fault-tolerant control strategy is exploited to guarantee system stability when a large fault is diagnosed by the developed FDI approach. The speed regulation of dc-motor and dc–dc converter are used for simulation and experiment verifications. Moreover, the comparison results and Monte Carlo simulation demonstrate the superiority and reliability of the proposed method.

An Improved Tuning of PID Controller for PV Battery-Powered Brushless DC Motor Speed Regulation Using Hybrid Horse Herd Particle Swarm Optimization

In this study, speed control of PV battery-powered brushless DC motor (BLDC) is controlled by novel hybrid horse herd particle swarm optimization- (HHHPSO-) tuned proportional integral derivative (PID) controller. The optimal gain parameter of the PID controller is tuned by hybrid horse herd optimization algorithm. The purpose of the newly developed HHHPSO algorithm is to enhance the performance of the classic horse herd algorithm (HHA), specifically in two different ways. In the first place, it bolsters HHA’s aptitude for exploratory learning related to the ageing issue. By doing so, it is possible to circumvent the phenomenon of the local minimum stagnation. Second, it permits HHA to have a superior capability of exploitation with the assistance of hybridization through the utilisation of particle swarm optimization. This hybrid technique helps improve the rate convergences of the HHA method. The time domain-based performance indices were considered as an objective function such as addition of integral of squared speed error, integral of squared current error, and integral of squared electromagnetic torque error for finding the optimal gain values for the PID controller using HHHPSO. The proposed HHHPSO-tuned PID controller for PV battery-powered BLDC motor is tested for various working conditions such as constant speed conditions, varying speed conditions, and varying load conditions and also compared with state-of-the-art method. The proposed method has quick rise time around 20-21 msec, quick settling time around 35-39 msec, zero steady-state error, and zero overshoot than state-of-the-art optimization method. The proposed control techniques were also tested in hardware to confirm the suitability for real-time applications.

An effective speed regulation of brushless DC motor using hybrid approach

In this paper, a hybrid method is proposed to achieve an effective control of the speed of the BLDC motor with the established specifications. The proposed hybrid system is the joined execution of Radial Basis Function Neural Network (RBFNN) and Student psychology optimization algorithm (SPOA) and hence it is named as RBFNN-SPOA strategy. The RBFNN is trained and processed first, then that output is given to the SPOA approach, which drives the BLDC motor. The proposed RBFNN-SPOA approach is tune the parameter of PID controller, through which the speed regulation process of motor is achieved. Based on the load variation and the variation of input, the proposed approach is analyzed. The best gain parameter of the PID controller is utilized to control the speed of the motor. The proposed approach is considering the constraints, which are utilized to obtain the objective of the system. The factors like rise time, peak time, peak overshoot, settling time and steady-state error is assessed using the proposed approach. By then, the performance of the proposed method is executed on MATLAB platform and compared with existing methods. The proposed method Peak overshoot, Peak undershoot value becomes 9.67 rpm and 2.05 rpm. The settling time of proposed approach is 0.009 s. The steady state error at speed and steady state error percentage of proposed approach is 0.25 rpm, 0.008 rpm; it is less than the existing approach under no load condition.

Speed Regulation of a Permanent Magnet DC Motor with Sliding Mode Control Based on Washout Filter

The accuracy of control systems applied to motors is influenced by uncertainties and abrupt variations of the load and system parameters. Some robust control strategies have been proposed in the literature for responding to disturbances and uncertainties, parametric variations, and non-linearities, adding complex control rules and considerable computational efforts. Therefore, this paper presents the application of a sliding mode control method based on a washout filter (SMC-w) for speed control in a permanent magnet DC motor. In addition, the dynamic behavior of the SMC-w is evaluated under changes in the reference speed and load torque. The response of the control system under variations of the speed reference signal and load torque were studied. The results were contrasted with conventional proportional integral derivative (PID) control to evaluate the efficiency and improvement of the SMC-w. The qualitative shape of the transient response of the speed and current concerning changes in the reference speed is symmetric for the SMC-w controller, but the values of overshoot, settling time, and steady-state error are different. This technique has a great potential for industrial application as it controls efficiently with low computational cost and a simple design, which benefits its implementation in practical environments.

Desain Hibrid Menggunakan PID-ANFIS Controller Pada Motor DC Berbasis PSO (Particle Swarm Optimization)

DC motors can be used as generators or motors. For this reason, it is necessary to design the best DC motor speed regulation in order to obtain the best optimization. DC motor setting modeling must be adjusted to the DC motor characteristics and setting model. The results of the performance of the DC control model have a different steady-state error, settling time, and overshoot. From the results of running the program, it is found that the PID-PSO-ANFIS hybrid control model produces the best output performance. The results of PID-PSO-ANFIS optimization show that there is no overshot and undershot, settling time is 0.04 seconds, the motor speed reaches a constant and stable state. This design will be developed using artificial intelligence methods and other controllers in order to obtain the best optimization.

Teaching method of designing experiment from the perspective of teacher in power electronics course

In order to solve the problem of lacking active learning and independent problem-solving ability in the verification experiment, an experimental teaching method of designing experiment from the perspective of the teacher is proposed, in which the roles of students and teachers are changed. Students are made familiar with the platform through a verification experiment in which the teacher gives the experiment guidebook and provides guidance. Then, the target of another experiment is given. The students design the experiment from the perspective of the teacher, and write the experiment guidebook, including the experimental objectives, the experimental contents and the implementation methods. Then the students do the experiment. The power electronics experiment course is taken as an example to introduce the proposed method. The Sinusoidal Pulse Width Modulation (SPWM) inverter circuit experiment is taken as the verification experiment. After the students are familiar with the platform functions, they design a DC motor speed regulation experiment with a full bridge DC-DC circuit, write a guidebook, and complete the experiment according to the steps in the guide book. Finally, according to the success rate and the correct rate of the results, most students can complete the design experiment from the perspective of the teacher, and the answers to the thinking questions are basically correct. According to the questionnaire survey, the method proposed improves the students' ability of autonomous learning and problem-solving with good results.

A New Fusion of ASO with SA Algorithm and Its Applications to MLP Training and DC Motor Speed Control

An improved version of atom search optimization (ASO) algorithm is proposed in this paper. The search capability of ASO was improved by using simulated annealing (SA) algorithm as an embedded part of it. The proposed hybrid algorithm was named as hASO-SA and used for optimizing nonlinear and linearized problems such as training multilayer perceptron (MLP) and proportional-integral-derivative controller design for DC motor speed regulation as well as testing benchmark functions of unimodal, multimodal, hybrid and composition types. The obtained results on classical and CEC2014 benchmark functions were compared with other metaheuristic algorithms, including two other SA-based hybrid versions, which showed the greater capability of the proposed approach. In addition, nonparametric statistical test was performed for further verification of the superior performance of hASO-SA. In terms of MLP training, several datasets were used and the obtained results were compared with respective competitive algorithms. The results clearly indicated the performance of the proposed algorithm to be better. For the case of controller design, the performance evaluation was performed by comparing it with the recent studies adopting the same controller parameters and limits as well as objective function. The transient, frequency and robustness analysis demonstrated the superior ability of the proposed approach. In brief, the comparative analyses indicated the proposed algorithm to be successful for optimization problems with different nature.

DC Motor Speed Regulation Using Speech Recognition

One of the uses of this sound technology is controlling the speed of a DC motor. Sound in the form of a spectrum signal can be converted to digital. Digital signals can be used as a microcontroller input to adjust the speed of a DC motor using the PWM (pulse width modulation) method. The design of the tool uses the V3 voice recognition module to convert the voice into digital. A microcontroller as a voice data processor by changing the input voltage to a DC motor. Voice command to set DC motor speed. Based on the results of tests carried out in good environmental conditions, 90% of voice commands can be recognized. Meanwhile, in bad environmental conditions by 50%. Manual measurement is done by entering the input voltage from 1 volt to 10 volts. The results of the comparison show that the speed is almost the same, namely 2727 rpm for manual calculation and 2915 rpm for the whole tool. This difference occurs because the test when manually inputting the tension is not very accurate. It can be concluded that the tool is working properly and as desired. If the environmental conditions are bad only 50% can be recognized from 30 voice commands, then there is a difference in voice intonation during the training process.

Comparative Study between the PID Regulator and the Fuzzy Regulator Applied to the Operation of a Brushless DC Motor

This paper presents the results of research on speed regulation of a brushless DC motor. This is mainly a comparative study between a PID regulator and a fuzzy regulator applied to the operation of this type of engine in order to find the best control. The BLDC engine must operate under various speed and load conditions with improved performance and robust and complex speed control. Because of this complexity, the traditional PID command encounters difficulties in controlling the speed of a BLDC. Another control technique is currently developing and is producing good results. This is the fuzzy controller that handles process control problems, that is, managing a process based on a given set point per action on the variables that describe the process. To achieve the desired results, the brushless DC machine model will be studied. With the model obtained, both types of regulator will be tested. A synthesis of the observed comparison results will enable a conclusion to be drawn on the performance of the two types of regulators driving a BLDC (Brushless DC).

Performance Comparison of PI Control and Fuzzy Logic for Speed Control of DC Shunt Motor Using Matlab / Simulink

DC motor speed regulation is an important role in the industrial process so it can run easily and efficiently. A good DC motor speed control system must have a fast and accurate response. However, it is rare to find a DC motor that has controlled to get a constant speed. This research presents an analytical comparison of PI controller and Fuzzy Logic Controller for Speed Control of DC Shunt Motor. The disadvantages of PI controller like it do not operate properly when the system has a high degree of load disturbances [1]. FLC is a good for load disturbances and can be easily implemented. The simulation of both speed controller have been made by Matlab Simulink software.

Opposition based Henry gas solubility optimization as a novel algorithm for PID control of DC motor

This paper proposes Henry gas solubility optimization with opposition-based learning (OBL/HGO) as a novel optimization approach for DC motor speed regulation. The proposed approach was used to obtain the best parameters (proportional, integral, derivative) of PID controller by minimizing the integral of time multiplied absolute error (ITAE) as the objective function. The optimized controller was used to regulate the speed of a DC motor. The analysis of statistical tests, convergence profile, performance index, robustness, and disturbance rejection along with transient and frequency responses were all conducted in order to validate the effectiveness of the proposed approach. Also, the performance of the proposed OBL/HGSO tuned PID (OBL/HGSO-PID) controller was not only compared with the PID controller tuned by the original HGSO algorithm but also with other controllers that were tuned by the state-of-the art meta-heuristic algorithms such as atom search optimization (ASO), stochastic fractal search (SFS), grey wolf optimization (GWO) and sine–cosine algorithm (SCA). The conducted simulation results and comparisons with the proposed HGSO-PID controller and other existing controllers have showed that the proposed OBL/HGO-PID controller has superior control performance and excellent robustness even under the conditions of both system uncertainties and load disturbances.

PI Controller Based Performance Analysis of Brushless DC Motor, Utilizing MATLAB Simulink Environment

Brushless DC Motor (BLDC) is gaining more and more popularity as one of the best electrical drives nowadays due to advantages like high efficiency, low maintenance, good reliability & wide dynamic response. The traditional brushed motor speed regulation is essentially effective in low speed and unable to lower the commutation torque ripple in high speed range. Speed regulation of Brushless DC (BLDC) motor is done by utilizing PI controller. The PI controller output act as the input to the variable voltage block. The mathematical modeling of BLDC motor is additionally shown here. The BLDC motor is supplied from the inverter while the rotor position and speed are the input here. The detailed mathematical model of the anticipated drive system is developed and simulated using MATLAB/Simulink environment. Principle of operation of using component is examined and therefore the simulation results are reported here to verify the theoretical analysis.

Control of brushless DC motor based on fuzzy rules optimized by genetic algorithm used in hybrid vehicle

To improve the control precision of the closed-loop speed regulation of the brushless DC motor (Brushless DC motor, BLDCM) used in hybrid vehicles, the paper established a fuzzy controller for closed loop control of speed, taking the speed difference and the conversion rate of the speed difference as the inputs, and the increment of the supply voltage as the output, and proposed a method of optimizing fuzzy control rules based on genetic algorithm. Established the mathematical model of BLDCM in MATLAB/Simulink, simulated the traditional PID controller, the fuzzy controller and the fuzzy controller optimized by genetic algorithm. Then the hardware-in-the-loop motor control system is constructed based on dSPACE. The simulation and experiment prove that the optimization of fuzzy rules by genetic algorithm is an effective method to improve the accuracy of speed control, and it has good tracking performance for frequently changing speed requirements in hybrid vehicle.

Output feedback‐based sliding mode control for disturbed motion control systems via a higher‐order ESO approach

This study presents an output feedback-based sliding mode control approach for motion control systems with mismatched/matched disturbances. The key idea of this study is to reconstruct the unmeasured auxiliary states and disturbances synchronously online by constructing a higher-order extended state observer (HOESO). It is shown that the resulting sliding mode controller based on HOESO can drive the system output to an ultimately bounded region, which can be regulated arbitrarily small by assigning a sufficiently large scaling gain. Different from the existing extended state observer methods, the newly proposed HOESO treats the known dynamics satisfying the Lipschitz condition and the unknown higher-order disturbances separately. As such, it provides a feasible way for higher-precision states/disturbance estimation. Thanks to the utilisation of HOESO, the upper bound of disturbances is not necessarily required as a priori and the switching gain is adaptively chosen based on the estimation error such that the chattering effects can be significantly reduced. Experiments for speed regulation of a brushless DC motor are conducted to verify the effectiveness of the proposed method.

Design of DC Motor Speed Regulation System Based on ARM

This paper mainly studies the design of DC motor speed control system based on ARM. The STM32 micro controller is used to design the corresponding hardware peripheral circuit, and the microcontroller programming, with the hardware circuit to achieve the corresponding function. Using the speed closed-loop PID control algorithm, the speed of the DC motor can be adjusted to improve the dynamic characteristics of the motor. The actual operation results show that the design of this topic is to meet the requirements of the control of the motor, such as start and stop, forward and reverse, acceleration and deceleration, and no steady state error.

Design and Simulation of Double Closed-loop DC Motor Speed Regulation System with Fuzzy PID Controller

This paper introduced the principle of one dual closed-loop DC motor speed control system with fuzzy PID controller. The algorithm could reduce the setting time and the over-shoot of the step response of the speed-current loop control system, with comparison of the traditional PID after simulation.