scholarly journals BLDC Motor Control Optimization Using Optimal Adaptive PI Algorithm

2020 ◽  
Vol 20 (2) ◽  
pp. 47
Author(s):  
Supriyanto Praptodiyono ◽  
Hari Maghfiroh ◽  
Chico Hermanu
Keyword(s):  
Fuzzy Logic Controller ◽  
Absolute Error ◽  
Pi Controller ◽  
Settling Time ◽  
The Other ◽  
Step Response ◽  
Pi Control ◽  
Bldc Motor ◽  
Motor Speed ◽  
Control Effort

The main problem of using a Proportional Integral (PI) Controller in Brushless Direct Current (BLDC) motor speed control is tuning the PI’s parameter and its performance cannot adapt to the system behavior changes. Particle Swarm Optimization (PSO) has been chosen to optimize the tuning. Fuzzy Logic Controller (FLC) is used to online tuning PI’s parameters to adapt to system conditions. Optimal adaptive PI, which combines the PSO method and FLC method to tune PI, is proposed. It was successfully implemented in the simulation environment. The test was carried out in three conditions: step responses, set-point changes, and disturbance rejection. The proposed algorithm is superior with no overshoot/undershoot. Whereas in terms of settling time is in between PI and PI-PSO. PI controller has the smallest control effort. However, the other parameter is the worst. PI-PSO is superior in terms of settling time and Integral of Absolute Error (IAE) except for the step response test. The proposed method has lower IAE and higher control effort by 78.73 % and 60 % compared to PI control. On the other hand, it has a higher IAE dan lower control effort by 11.82 % and 33.88 % compared to PI-PSO. Therefore, the optimal adaptive PI control can reduce energy consumption compared to optimal PI with better performance than PI control.

scholarly journals PERFORMANCE IMPROVEMENT ON MOTOR BLDC SPEED CONTROLLER BY USING MULTI CONTROLLER WITH SUMMATION TECHNIQUE

2021 ◽  
pp. 1-8
Author(s):  
Widjonarko ◽  
Cries Avian ◽  
Setya Widyawan Prakosa ◽  
Bayu Rudiyanto
Keyword(s):  
Control System ◽  
Fuzzy Logic Controller ◽  
Absolute Error ◽  
Bldc Motor ◽  
Motor Speed ◽  
Electric Cars ◽  
Speed Controller ◽  
The Difference ◽  
Increasing Demand ◽  
Artificial Neural Network Ann

BLDC motor is the most widely used in the industrial world, especially in electric vehicles. With this increasing demand, a variety of research topics emerged in BLDC motors. One popular research is on BLDC motor speed control topics to maintain speed for its application, such as intelligent cruise technology in electric cars and conveyors for line assembly. However, from several existing studies, the BLDC Motor controller still uses a single controller model. The controller's output is purely from the controller without any improvement in characteristics and has a problem with the oscillating speed setpoint (error problem). In this study, the researcher proposed a combining control with the concept of summation output to handle this problem. With this concept, the control techniques used can improve each other so that better control can be produced following the control system assessment parameters. The authors used a Fuzzy Logic Controller, Artificial Neural Network (ANN), and PID, which were combined and obtained seven control systems. The results show that the control system can improve several parameters using the summation concept from the seven controllers model. It has a positive overall correlation when viewed in terms of the difference between the Error and the setpoint or MAE (Mean Absolute Error) as parameter assessment.

Response Based Comparative Analysis of Two Inverter Fed Six Phase PMSM Drive by Using PI and Fuzzy Logic Controller

2016 ◽  
Vol 6 (6) ◽  
pp. 2643 ◽  
Author(s):  
Anurag Singh Tomer ◽  
Saty Prakash Dubey
Keyword(s):  
Fuzzy Logic ◽  
Comparative Analysis ◽  
Fuzzy Logic Controller ◽  
Permanent Magnet Synchronous Motor ◽  
Sudden Change ◽  
Pi Controller ◽  
Settling Time ◽  
Steady State Current ◽  
Speed Level ◽  
Starting Torque

<p>This Paper gives a complete modeling and simulation of a two inverter fed six phase permanent magnet synchronous motor drive system, Then response based comparative analysis is done on starting torque ,settling time, Steady state current at various speed levels and torque levels by changing  proportional- integral (PI) controller to  Fuzzy logic controller. The PI controller has some disadvantages like, more settling time, sluggish response due to sudden change in load torque etc. So an intelligent controller, based on fuzzy logic is introduced which replaces the PI-controller and its drawbacks. The performance of both the controller has been investigated and studied by comparing the different plots obtained by setting various speed level both incremented and decremented speed  , at different load conditions like No-load, fix load and dynamic load through Matlab/Simulink environment. Finally it is concluded from the result that fuzzy logic based controller is robust, reliable gives quick response with high starting torque and more effective than the conventional PI controller. It is also observed that both the proposed model can also run above rated speed significantally.</p>

scholarly journals BLDC Motor Speed Control using Fuzzy Logic PID Controller and Comparing It with PI Controller

2019 ◽  
Vol 9 (2) ◽  
pp. 4917-4922
Keyword(s):  
Mathematical Model ◽  
Pid Controller ◽  
High Performance ◽  
Pi Controller ◽  
Dynamic State ◽  
Bldc Motor ◽  
Fuzzy Pid ◽  
Motor Speed ◽  
Brushless Dc ◽  
Fuzzy Pid Controller

In this project, mathematical model of the Brushless DC motor (BLDC) is developed and the closed-loop Fuzzy PID controller has been simulated in MATLAB-Simulink environment. The three-phase (BLDC) is developed and the DC power is supplied to this machine though six step inverter whose switching state is controlled by the hall signal. The hall effect sensor senses the rotor posit ion of the motor and it generates binary digit number which is decoded and given to the six-step inverter. The mathematical model is developed using the back emf equations and torque equation of the BLDC motor. The PI controller doesn’t operate properly during dynamic state and hence the fuzzy-PID-controller is better option to control and regulate the speed of the BLDC motor which has high performance in comparison to the PI controller. And, we can get the smooth speed-torque characteristics using Fuzzy PID controller.

scholarly journals Speed Control Using Fuzzy Controller for a Four Switch Sensorless BLDC Motor

2020 ◽  
Vol 5 (8) ◽  
pp. 1668-1674
Author(s):  
Niba Shoby ◽  
Deepika Vasanthakumar ◽  
Anupama P K
Keyword(s):  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
High Reliability ◽  
Speed Control ◽  
Bldc Motor ◽  
Motor Speed ◽  
Zero Crossing ◽  
Loop Control ◽  
Speed Regulation ◽  
Loop Control System

- Brushless Direct Current (BLDC) motors are highly efficient motors with high reliability and a longer life span. The advent of sensor less technology has improved the performance and reliability of BLDC motor drives. This work is to analyze a drive system for BLDC motor with Four-Switch Three-Phase Inverter (FSTPI). Back Electromotive Force (EMF) Zero Crossing Detection (ZCD) method is used to estimate the rotor position. Speed control of motor is achieved by using Fuzzy Logic Controller (FLC) based closed loop control system. The Simulation was carried out using MATLAB software and motor the performance was analyzed with FLC for motor speed regulation.

scholarly journals Desain dan Implementasi Pengaturan Kecepatan Motor BLDC Melalui Pengaturan Fluks

2019 ◽  
Vol 1 (1) ◽  
pp. 36
Author(s):  
Ony Asrarul Qudsi ◽  
Syechu Dwitya Nugraha
Keyword(s):  
Speed Control ◽  
Pi Controller ◽  
Bldc Motor ◽  
Test Results ◽  
Motor Speed ◽  
Additional Load ◽  
Design And Implementation ◽  
Speed Regulation ◽  
Input Signals ◽  
Regulation Method

This journal presents the design and implementation of BLDC motor speed control. Speed control of the BLDC motor can be done by controlling the flux produced by the BLDC motor coil. The current reading by the sensor will be processed in the flux estimator to get the flux value in the motor. By using the PI controller, the flux value generated by the coil will be controlled so that it is equal to the setpoint value that has been determined. Flux values that have the same setpoint will be converted to PWM values which will be used as input signals on the six step inverter. The test results by providing disturbance form the additional load on the motor, shows that the motor is able to maintain its speed according to the value of the speed provided. Thus, the proposed speed regulation method can work well.

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 Response Based Comparative Analysis of Two Inverter Fed Six Phase PMSM Drive by Using PI and Fuzzy Logic Controller

2016 ◽  
Vol 6 (6) ◽  
pp. 2643
Author(s):  
Anurag Singh Tomer ◽  
Saty Prakash Dubey
Keyword(s):  
Fuzzy Logic ◽  
Comparative Analysis ◽  
Fuzzy Logic Controller ◽  
Permanent Magnet Synchronous Motor ◽  
Sudden Change ◽  
Pi Controller ◽  
Settling Time ◽  
Steady State Current ◽  
Speed Level ◽  
Starting Torque

<p>This Paper gives a complete modeling and simulation of a two inverter fed six phase permanent magnet synchronous motor drive system, Then response based comparative analysis is done on starting torque ,settling time, Steady state current at various speed levels and torque levels by changing  proportional- integral (PI) controller to  Fuzzy logic controller. The PI controller has some disadvantages like, more settling time, sluggish response due to sudden change in load torque etc. So an intelligent controller, based on fuzzy logic is introduced which replaces the PI-controller and its drawbacks. The performance of both the controller has been investigated and studied by comparing the different plots obtained by setting various speed level both incremented and decremented speed  , at different load conditions like No-load, fix load and dynamic load through Matlab/Simulink environment. Finally it is concluded from the result that fuzzy logic based controller is robust, reliable gives quick response with high starting torque and more effective than the conventional PI controller. It is also observed that both the proposed model can also run above rated speed significantally.</p>

scholarly journals Speed control of the asynchronous motor using LabVIEW

2021 ◽  
Vol 8 (5) ◽  
pp. 59-66
Author(s):  
Petru Livinti ◽  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Asynchronous Motor ◽  
Speed Control ◽  
Pi Controller ◽  
Motor Speed ◽  
Experimental Stand ◽  
Three Phase ◽  
Adjustment System ◽  
Speed Adjustment

This paper was presented a comparative study on the methods of adjusting the speed of a three-phase asynchronous motor with a rotor in a short circuit. For the same structure of the experimental stand used, two programs were created, implemented, and validated in LabVIEW. For the first method, the program in LabVIEW was made with the PI (proportional-integrative) controller and for the second method, the program in LabVIEW was made with the Fuzzy Logic controller. Following the analysis of the resulting graphs, it was found that the speed control system made with the fuzzy logic controller ensures an increase in its performance compared to the speed control system made with the conventional PI type controller. The indicial responses of the adjustment system of the three-phase asynchronous motor speed with PI controller or Fuzzy Logic controller have been determined in real-time by means of the experimental stand. The override of the speed adjustment system is decreased from the value of 26.9% corresponding to the PI controller to the value of 2.3% corresponding to the Fuzzy Logic controller and the duration of the transient time is decreased from the value of 2.2 s related to the PI controller to the value of 0.5 s, related to the Fuzzy Logic controller. By using the Fuzzy Logic controller, the amount of electrical energy required to supply the electric drive system made with a three-phase asynchronous motor will be reduced. This three-phase asynchronous motor speed adjustment algorithm can be implemented for other electric drive systems from different industrial applications.

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