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All Journal International Journal of Electrical and Computer Engineering Buletin Ilmiah Sarjana Teknik Elektro Control Systems and Optimization Letters
MAJDOUBI, Rania
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Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Parameters estimation of BLDC motor based on physical approach and weighted recursive least square algorithm Majdoubi, Rania; Masmoudi, Lhoussaine; Bakhti, Mohammed; Elharif, Abderrahmane; Jabri, Bouazza
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp133-145

Abstract

Brushless DC motors (BLDCM) are widely used when high precision converters are required. Model based torque control schemes rely on a precise representation of their dynamics, which in turn expect reliable system parameters estimation. In this paper, we propose two procedures for BLDCM parameters identification used in an agriculture mobile robot’s wheel. The first one is based on the physical approach or equations using experimentation data to find the electrical and mechanical parameters of the BLDCM. The parameters are then used to elaborate the model of the motor established in Park’s reference frame. The second procedure is an online identification based on recursive least square algorithm. The procedure is implemented in a closed-loop scheme to guarantee the stability of the system, and it provide parameter matrices obtained by transforming electrical equations, established in Parks reference frame, and mechanical equation to discrete-time domain. From these matrices, and using well formulated intermediate variables, all desired parameters are deduced simultaneously. The identification procedures are being verified using simulation under Matlab-Simulink software.
Motion System of a Four-Wheeled Robot Using a PID Controller Based on MPU and Rotary Encoder Sensors Sagita, Muhamad Rian; Ma’arif, Alfian; Furizal, Furizal; Rekik, Chokri; Caesarendra, Wahyu; Majdoubi, Rania
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.150

Abstract

This research addresses the challenge of developing an effective motion system for a four-wheeled omnidirectional robot configured with wheels at a 45-degree angle, allowing for holonomic movement—motion in any direction without changing orientation. In this system, inverse kinematics calculates each wheel's angular velocity to optimize movement. PID control is implemented to stabilize motor speeds, while odometry guides and determines the robot’s position using initial and target coordinates. The robot operates on a 12-volt power supply and two STM32F103C microcontrollers, utilizing an MPU6050 sensor to maintain orientation and optical rotary encoders for accurate positional tracking. Experimental results demonstrate that the robot achieves optimal motion on x and y axes with PID settings of kP = 0.8, kI = 1.0, and kD = 0.08. This configuration yields a rise time of 0.95 seconds, overshoot of 7.36%, and steady-state error of -0.5 RPM at a setpoint of 350 RPM. Using odometry, the robot successfully navigates various movement patterns with average position errors of 1.2% on the x-axis and 1.6% on the y-axis for rectangular patterns, 2.1% on the x-axis and 2.2% on the y-axis for zig-zag patterns, and 1.75% on the x-axis and 1.15% on the y-axis for triangular patterns. The MPU6050 sensor maintains orientation with an error of 0.65% in triangular patterns and 0.85% in rectangular patterns. Through inverse kinematics, PID control, and sensor integration, the robot reliably follows designated coordinate points.
Implementation of Kalman Filter on Pid Control System for DC Motor Under Noisy Condition Setiawan, Nurman; Caesarendra, Wahyu; Majdoubi, Rania
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 3 (2024): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i3.11236

Abstract

DC motors are actuators that are widely used in various fields. The reason is that DC motors are easy to control, high torque at low speed, and fast response. Angular velocity of DC motor is regulated automatically by using certain controls method, the most commonly used of which is PID control. The performance of the control system decreases in the presence of disturbance or noise. The presence of noise give has negative impacts such as instability in control response, decreased accuracy, and difficulty in tuning PID gain. The most common disturbance comes from the inaccuracy data due to measurement noise and process noise. In this study, the Kalman filter is proposed as a state estimator to reduce the influence of noise, both process noise and measurement noise. The Kalman filter provides an optimal estimate of the angular velocity of DC motor by minimizing the mean squared error. The estimated angular velocity from Kalman Filter is utilized as input for PID control. Simulation results show that the Kalman filter is capable to reduces the influence of measurement noise. In nominal condition, PID control give an Integral Absolute Error (IAE) of 344.56. Under noisy condition, PID control (without Kalman filter) has an IAE of 517.27, while Kalman filter-based PID control has an IAE of 345.25. The IAE reduction of 99.6% indicates that the proposed control system effectively minimizes errors, resulting in better performance and stability.
Co-Authors Alfian Ma’arif BAKHTI, Mohammed ELHARIF, Abderrahmane Furizal, Furizal JABRI, Bouazza Masmoudi, Lhoussaine REKIK, Chokri Sagita, Muhamad Rian Setiawan, Nurman Wahyu Caesarendra