DC Motor Speed Research Articles

Application of Soft Computing Techniques for Speed Control of Brushless DC Motors

Nowadays Brushless DC (BLDC) motors are treated as the most popular motors, which are applied widely due to their higher efficiency and excellent torque characteristics. Moreover they are operated with DC supply and without using brushes. But BLDC motor operate with wide speed range and therefore it is required to regulate the speed of DC motor using different advanced techniques. In this work, the fuzzy sliding mode control (FSMC) is employed for controlling the speed of BLDC motor. The proposed method is compared with the conventional Sliding mode control (SMC) and the results are analyzed using MATLAB/ Simulink tool.

DC 모터 속도 제어시스템을 위한 내부모델 원리 기반 제어기와 외란 관측기 기반 제어기의 등가 조건

Asymptotic tracking of a reference model and nonlinear disturbance rejection are two of the most important attributes of an effective control system. A DOB-based controller, which is designed based on an augmented system model including the disturbance dynamics, relies mainly on the disturbance estimation to provide robust reference tracking performance. While IMP-based controller design technique achieves the same result by including a dynamic model of the reference and disturbance in the control system model. However, the similarity of these two control techniques extends beyond basic design consideration. This paper presents an analytical study that reaches an equivalent condition between the two classes of controllers for a DC motor speed control problem. Based on the obtained condition, it is proposed that the DOB-based controller can be designed such that it shows the same performance as the IMP-based controller. This has been further verified through a simulation which shows the same robust performance in both cases.

Interleaved Boost Integrated Flyback Converter for Power Factor Correction in Brushless DC Motor Drive

The scope of this research is to manage the speed of Permanent Magnet Brushless DC Motor Drive (PMBLDCMD) for various less capacity applications. In the circuit, a 1ϕ AC power is given to Diode Rectifier and the converted DC supply is given to condenser, which leads to abnormal pulsating current. Because of this pulsating current, the power quality disturbances arise at the supply point. Hence, the PMBLDCMD requires Power Factor Correction (PFC) converter for many household and profitable applications. The rotors of PMBLDCMD are driven by 3ϕ voltage source inverter (VSI), which performs electronic commutation. The range of PFC converter for feeding PMBLDCMD has high emphasis on the power quality (PQ) norms, cost and performance of controllers. The proposed converter requires very less components, which imposes less stress, low ripple and less power loss with positive voltage polarity. The chopper is used to correct the power factor. Various chopper layouts like buck boost Converters and boost converters with single switch are used. The mostly used regulated structures for PFC converters govern the current with continuous conduction technique and to govern the potential differential tracker using discontinuous conduction method (DCM). The processes like examining, modelling and governing of PFC converters are applied for upgrading the quality of power in AC supply.

Online self-adaptive proportional-integral-derivative control for brushless DC motor based on variable universe fuzzy inference system optimized by genetic algorithm

In this study, we propose a novel robust online self-adaptive Proportional-Integral-Derivative (PID) control design for Brushless DC Motor (BLDCM) speed system under different operating conditions. The online adaptive tuning for PID parameters is realized accurately by optimizing the control rules of variable universe fuzzy inference with a modified genetic algorithm (GA). Based on the variable fuzzy inference theory, the method of solving contraction–expansion factor in real-time through fuzzy inference is proposed. Furthermore, the process to optimize two inference rules by GA is improved to get optimal control rules for adjusting PID parameters. Finally, multiple sets of simulations and experiments are conducted to validate the proposed controller in different conditions by building Simulink models and setting up experiment platforms. The results of this study not only demonstrate the effectiveness of the proposed controller but also provide technical suggestions for the speed control of BLDCM.

Low speed sensorless control method of brushless DC motor based on pulse high frequency voltage injection

A low speed sensorless position control method for brushless DC motor based on pulse pulse high frequency voltage injection is proposed according to the characteristic that the brushless DC motor (BLDCM) which is produced at present makes the counter electromotive force waveform show sinusoidal waveform in view of the problem that it is difficult to accurately obtain the rotor position and speed of the brushless DC motor at zero and low speed. Its principle is to inject high frequency sinusoidal voltage signal on the estimated direct axis of the synchronous rotating coordinate system so that the motor can generate saturated salient effect, obtain the estimation error containing the rotor position information, and by detecting the output current of PI regulator of quadrature axis current loop, and then estimate the initial position of the rotor and judges the magnetic pole, realize the determination of the actual rotor position, finally, realize the non-position static low speed control of BLDCM by adding current and speed rings. According to the simulation test, it shows that this method can detect the position and speed of the motor rotor well at both zero speed and low speed.

A Hybrid Approach for Noise Reduction in Acoustic Signal of Machining Process Using Neural Networks and ARMA Model.

Intelligent machining has become an important part of manufacturing systems because of the increased demand for productivity. Tool condition monitoring is an integral part of these systems. Airborne acoustic emission from the machining process is a vital indicator of tool health, however, it is highly affected by background noise. Reducing the background noise helps in developing a low-cost system. In this research work, a feedforward neural network is used as an adaptive filter to reduce the background noise. Acoustic signals from four different machines in the background are acquired and are introduced to a machining signal at different speeds and feed-rates at a constant depth of cut. These four machines are a three-axis milling machine, a four-axis mini-milling machine, a variable speed DC motor, and a grinding machine. The backpropagation neural network shows an accuracy of 75.82% in classifying the background noise. To reconstruct the filtered signal, a novel autoregressive moving average (ARMA)-based algorithm is proposed. An average increase of 71.3% in signal-to-noise ratio (SNR) is found before and after signal reconstruction. The proposed technique shows promising results for signal reconstruction for the machining process.

Fuzzy algorithm implementation in microcontroller for DC motor control

In industrial automation, motor control technique plays the vital role. Motor consists of inductor or electromagnet. Causing inductor or electromagnet, magnetic inductions are produces which resists any change of motor speed. Hence, according to set point, precise speed control is challenging. However, using various control technique can be controls the speed of DC motor. The aim of the present paper is to implement hardware and control the speed of DC motor using embedded fuzzy logic. Set point have been applied externally and recorded the speed of motor through opto-isolator sensor module. In the hardware of DC motor control keypad, 2x16 LCD, DC motor driver and opto-isolator module are interfaced to PIC microcontroller. The Fuzzy algorithm is embedded in the microcontroller wherein input fuzification signals ‘error (Δe)’ and ‘change in error (e(n))’ and output fuzification signal ‘PWM’. The both of inputs of fuzzy algorithm are varied and record output of fuzzy algorithm which is PWM. Moreover, the hardware implementation has been tested for real time control of DC Motor.

Hands on Remote Learning Using a DC Motor Controller

An Electrical and Computer Engineering Laboratory exercise has been included in the junior year fall term to partially bridge the theory to practice gap for multiple basic electrical and computer engineering topics. The laboratory investigates facets of power electronics and computer control for students who have recently been introduced to the theory of transistor bridge circuits for voltage polarity control in their electronics class, and digital pulse width modulation for DC motor speed control in their first computer logic class. After brief study of its specification, students follow a lab sequence to set up and instrument a commercial H-bridge to first record polarity and magnitude of output voltages under specified input conditions, and subsequently to observe DC motor response to the same inputs. DC power polarity and averaging through Pulse Width Modulation (PWM), as well as the collateral realities of brushed DC motor noise and logic versus power supply levels become clear to most student for the very first time.

Kalman Filter to Improve Performance of PID Control Systems on DC Motors

A proportional–integral–derivative (PID) controller is a type of control system that is most widely applied in industrial world. Various tuning models have been developed to obtain optimal performance in PID control. However, the methods are designed under ideal circumstances. This means that the control system which has been built will not work optimally when noise exists. Noise can come from electrical vibrations, inference of electronic components, or other noise sources. Thus, it is necessary to design PID control system that can work optimally without being disturbed by noise. In this research, Kalman filter was used to improve the performance of PID controllers. The application of Kalman filter was used to reduce the noise of the input signal so that it could generate output signal which is in accordance with the expected output. Simulation result showed that the PID performance with Kalman filter was more optimal than the ordinary one to minimize the existing noise. The resulting speed of DC motor with Kalman filter had a lower overshoot than PID control without Kalman filter. This method resulted lower integral of absolute error (IAE) than ordinary PID controls. The IAE value for the PID controller with the Kalman filter was 25.4, the PID controller with the observer was 31.0, while the IAE value in the ordinary controller was only 60.9.

Optimization of DC motor speed control based on fuzzy logic-PID controller

In this paper the PID controller and the Fuzzy Logic Controller (FLC) are used to control the speed of separately excited DC motors. The proportional, integral and derivate (KP, KI, KD) gains of the PID controller are adjusted according to Fuzzy Logic rules. The FLC cotroller is designed according to fuzzy rules so that the system is fundamentally robust. Twenty-five fuzzy rules for self-tuning of each parameter of the PID controller are considered. The FLC has two inputs; the first one is the motor speed error (the difference between the reference and actual speed) and the second one is a change in the speed error (speed error derivative). The output of the FLC, i.e. the parameters of the PID controller, are used to control the speed of the separately excited DC Motor. This study shows that the precisiom feature of the PID controllers and the flexibllity feature of the fuzzy controller are presented in the fuzzy self-tuning PID controller. The fuzzy self – tuning approach implemented on the conventional PID structure improved the dynamic and static response of the system. The salient features of both conventional and fuzzy self-tuning controller outputs are explored by simulation using MATLAB. The simulation results demonstrate that the proposed self-tuned PID controller i.plementd a good dynamic behavior of the DC motor i.e. perfect speed tracking with a settling time, minimum overshoot and minimum steady state errorws.

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.

Making the PI and PID Controller Tuning Inspired by Ziegler and Nichols Precise and Reliable.

This paper deals with the design of a DC motor speed control implemented by an embedded controller. The design is simple and brings some important changes to the traditional Ziegler–Nichols tuning. The design also includes a novel anti-windup implementation of the controller and an integrated noise-reduction filter design. The proposed tuning method considers all important aspects of the control, such as pre-processing of the measured signals and filtering (to attenuate the measurement noise), time delays of the process, modeling and identification of the process, and constraints on the control signal. Three important aspects of designing PI and PID controllers for processes with noisy output on Arduino-type embedded computers are considered. First, it deals with the integrated design of the input filter and the controller parameters, since both are interdependent. Secondly, the method of setting the controllers from step responses by Ziegler and Nichols is modified for the case of digital signal processing (without drawing the tangent), while it recommends the suitability of its modification in terms of the use of both integral and static models. Third, the most suitable anti-windup solution for the given controller structure is proposed. In summary, the paper shows that an appropriate design of the embedded controller can achieve excellent closed-loop performance even in a noisy process environment with limited control signals.

A Study on Pesticide Sprayer Powered by Solar Energy Appropriate for Small Farms

The study was conducted on a knapsacksprayer powered by a DC motor through a 12 V lead acid battery charged from a solar panel (photovoltaic) directed to sun rays. The system was installed and tested in the western desert on a small-scale farm at Frafra Oasis (New val-ley). This study aimed to evaluate and develop a knapsack sprayer powered by a solar energy for overcoming operator fatigue and shortage of traditional energy in Egypt’s western desert. The experiments were conducted during the period which starts in August 2019 till Febru-ary 2020. The main parts of the system consist of photovoltaic (PV) or solar cells, charger controller, rechargeable battery, and DC motor speed control with dimmer and pump which was attached with a tank 20 liters capacity for sucking and pressurizing the liquid to the boom of the sprayer through a flexible hose. The main results of experiments were as fol-lows: The time for recharging the battery com-pletely was found 330 minutes (5.5 hours) to charge completely from 10.55 V – 13.85 V, with current intensity 1.67 Ampere. The bat-tery discharge time was varied due to drop the battery voltage from 13.85 – 10.55 Volts. De-pending on the motor speed, which is the time for discharging the battery was found 4 – 9 hours, when motor pulled 0.85 - 1.85 Amps at 2000 - 3400 rpm and this time at deferent speed is enough to spray area 3 - 6.82 fed/day day work = 6 hours with application rate 67 - 104.7 l/fed. The number of droplets and the area coverage percentage ranges from 30 – 146.33 drops and 13.96 – 27.97% for one cm2 of simulator targets at a speed ranging from 2000 – 3400 rpm, respectively.

Web-Based DC Motor Speed Design and Control

This research discusses about web based speed control of DC motor. This research is a development research. The development that is design and assemble a speed control of DC motor so that becomes function work well. The result of research is speed control of DC motor and monitoring value of voltage, current and rotation speed from DC motor. Speed control of DC motor using PWM on the NodeMCU while monitoring of voltage, current and rotation speed from DC motor using voltage sensor, current sensor, and inductive proximity sensor. The results show that the system is great working. On the readings of the voltage value using voltage sensor and multimeter digital, there is a difference value between 0,01 to 0,13 Volt. While for the readings of the current value using current sensor ACS712 and multimeter digital, there is a difference average 0,01 Ampere. Proximity sensors are used by monitoring of the rotation speed of DC motor. The result is this sensor is working and function well.
 Penelitian ini membahas tentang pengendalian kecepatan motor DC menggunakan web. Penelitian ini merupakan penelitian pengembangan. Pengembangan yang dilakukan ialah merancang dan merakit sebuah web dan alat pengendali kecepatan motor DC sehingga menjadi satu kesatuan dan dapat berfungsi dengan baik. Hasil dari penelitian ini adalah mengatur kecepatan motor DC serta monitoring nilai tegangan, nilai arus dan nilai kecepatan putaran pada motor DC. Pengendalian kecepatan motor DC dilakukan dengan mengatur PWM pada NodeMCU sedangkan monitoring tegangan, arus dan kecepatan putaran motor DC menggunakan sensor tegangan, sensor arus ACS712 dan sensor proximity induktif. Hasil penelitian menunjukkan bahwa sistem bekerja dengan baik. Pada pembacaan tegangan menggunakan sensor tegangan dan multimeter digital terdapat selisih antara 0,01 sampai 0,13 Volt. Sedangkan untuk pembacaan nilai arus menggunakan sensor arus ACS712 dengan multimeter digital, terdapat selesih rata-rata 0,01 Ampere. Sensor proximity digunakan sebagai monitoring kecepatan putaran pada motor DC. Hasil menunjukkan bahwa sensor ini bekerja dengan baik sesuai dengan fungsinya.

EFFECT OF MOVING AVERAGE FILTER WITH PID CONTROLLER USING HIL TECHNIQUE

Designing fast response controller that can achieving steady state with minimum error is big challenge in control application. Proportional Integral Derivate (PID) controllers are conventional controllers for their simplicity and wide range of applications in industrial. Many efforts have been made in improving the PID controller performance by enhancing the controller with different techniques for tuning its operation or filtering the feedback signal. In this paper, the effect of using Moving Average filter with the PID controller for controlling the speed of Permanent Magnet DC (PMDC) Motor with noisy speed sensor is discussed. PID controller and the moving average filter are modeled in MATLAB/Simulink software, where the Hardware in the Loop (HIL) technique with aid of microcontroller was used for the controlled plant which is a PMDC motor in this study. Comprehensive study on the available techniques used to modeling the PID controller is done as well. Furthermore, full practical tests prove that the controller behavior is more stable when moving average filter used and its effect minimized time needed to reach the steady state point clearly by 76%.

Control of BLDC motor using MRPID controller with modified landsman converter

PurposeThe principal intention behind the activity is to regulate the speed, current and commutation of the brushless DC (BLDC) motor. Thereby, the authors can control the torque.Design/methodology/approachIn order to regulate the current and speed of the motor, the Multi-resolution PID (MRPID) controller is proposed. The altered Landsman converter is utilized in this proposed suppression circuit, and the obligation cycle is acclimated to acquire the ideal DC-bus voltage dependent on the speed of the BLDC motor. The adaptive neuro-fuzzy inference system-elephant herding optimization (ANFIS-EHO) calculation mirrors the conduct of the procreant framework in families.FindingsBrushless DC motor's dynamic properties are created, noticed and examined by MATLAB/Simulink model. The performance will be compared with existing genetic algorithms.Originality/valueThe presented approach and performance will be compared with existing genetic algorithms and optimization of different structure of BLDC motor.

Comparison of PI DC Motor Speed Controller and Fuzzy PI DC Motor Speed Controller

Comparison of PI DC Motor Speed Controller and Fuzzy PI DC Motor Speed Controller

Speed and Position Control of DC Motor using LabVIEW

New applications requiring both speed and position control have emerged as a result of technological advancements. In many applications, a DC motor's speed and position can be adjusted. The PID controller controls the speed and position of individually stimulated DC motors. Using LabVIEW software, this study attempts to control the speed and position of a DC motor as well as calculate the closed loop system model. Nonlinearity in any system has undesirable implications in normal operation. Unwanted outcomes including dead zones, saturation, and system reaction.

Double closed-loop PI controller tuning for motor control

This paper demonstrates an algebraic algorithm performed in the control loop of a Brushless DC Motor (BLDCM) speed controller by computing the PI controller parameter that can be accepted. Using methodology of PI controller stability analysis, accurate stability conditions can be derived for the BLDC Motor speed controller. The results of applying the new method ensure the system stability and fast response by tuning the PI controller in the order of the motor and mechanical constant.

Параметрическая оптимизация системы автоматического регулирования частоты вращения вала двигателя постоянного тока судна

DC motor speed control can be done either manually or by using an automatic controlling tool. In order to perform parametric optimization of a DC motor rotational speed automatic control system, we have developed a simplified methodology. The said methodology is able to obtain a transfer function for an automatic control system being based on several initially given system parameters. It is a tree-step way according to the research goals. We offer model patterns where parameters can be designated. Time constant for a PI controller is being presented by a process time constant for a controlled DC motor for the purpose of this particular research.