Improved LQR Control Using PSO Optimization and Kalman Filter Estimator

Maghfiroh, Hari; Nizam, Muhammad; Anwar, Miftahul; Ma’arif, Alfian

doi:10.1109/access.2022.3149951

Cited by 27 publications

(13 citation statements)

References 35 publications

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“…Because energy usage is a major concern today [26], [27]. The energy profile of the motor is drawn as shown in Figure 10 for the same test conditions.…”

Section: Resultsmentioning

confidence: 99%

Speed control of brushless DCmotors using (conventional, heuristic, and intelligent) methods-based PID controllers

Shary

Nekad

Alawan

2023

IJEECS

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One of the most often utilized types of direct current (DC) motors in both the industrial and automotive sectors are brushless DC motors (BLDC). This research presents a comparative analysis on brushless DC motor speed management. A mathematical model of the BLDC motor is developed using MATLAB/Simulink, and its speed is tested using three alternative controller types. The first controller is a traditional proportional integral derivative (PID) controller for BLDC motor speed control. The second controller used the particle swarm optimization (PSO) approach with PID which give the best response for BLDC motor speed. The PID controller in the third method based on neural network also give best reaction on motor speed. Finally, comparison made in speed and torque profiles by using sudden changes in speed and load torque under the three proposed methods. The results show when using first controller the speed rise to 1,526 r.p.m and drop to 1,400 r.p.m at the test conditions. These oscillations will disappear when using the second and third controller.

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“…Because energy usage is a major concern today [26], [27]. The energy profile of the motor is drawn as shown in Figure 10 for the same test conditions.…”

Section: Resultsmentioning

confidence: 99%

Speed control of brushless DCmotors using (conventional, heuristic, and intelligent) methods-based PID controllers

Shary

Nekad

Alawan

2023

IJEECS

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“…Its versatility and reliability have made it a popular choice in various fields. The Kalman Filter can effectively handle situations where the system model is unknown, enabling accurate estimation of current and past data while also providing predictions for future data [44].…”

Section: Kalman Filtermentioning

confidence: 99%

Enhancing Speed Estimation in DC Motors using the Kalman Filter Method: A Comprehensive Analysis

Setiawan,

Ma'arif,

Rekik

et al. 2024

J. Ilm. Tek. Elektro Komput. Dan Inform

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The accurate estimation of speed is crucial for optimizing the performance and efficiency of DC motors, which find extensive applications in various domains. However, the presence of noise ripple, caused by interactions with magnetic or electromagnetic fields, poses challenges to speed estimation accuracy. In this article, we propose the implementation of the Kalman Filter method as a promising solution to address these challenges. The Kalman Filter is a recursive mathematical algorithm that combines measurements from multiple sources to estimate system states with improved accuracy. By employing the Kalman Filter, it becomes possible to estimate the true speed of DC motors while effectively reducing the adverse effects of noise ripple. This research focuses on determining the optimal values for the Kalman Filter parameters and conducting experiments on a DC motor to evaluate the performance of the proposed approach. The experimental results demonstrate that the Kalman Filter significantly improves the control of speed oscillations and enhances the stability of the DC motor system. Furthermore, a comprehensive analysis of the system's response and parameter tuning reveals the impact of different parameter combinations on settling time, overshoot, and rise time. By carefully selecting appropriate parameters, the proposed approach contributes to accurate speed estimation and effective control of DC motors, advancing the understanding and application of the Kalman Filter in various relevant fields. Overall, this research provides valuable insights into enhancing the performance and efficiency of DC motors through the integration of the Kalman Filter method.

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“…Command-Generator Tracker is a control design that provides a compensator according to the system requirements in order to obtain a small tracking error for the desired reference inputs [10], [11]. The equation of the plant and the output performance z(t) is.…”

Section: Lqr Output Feedback With the Command Generator Tracker's Mul...mentioning

confidence: 99%

Quadcopter Movement Analysis Using Output Feedback Control Based on Line of Sight

Nugraha¹,

Ramadhan²,

Shiddiq³

2023

JEEMECS

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Quadcopter UAV is a non-linear system which underactuated and unstable. Those charateristics will be the focus on this study for the development of quadcopter’s control. In this study, the output feedback control used to control the attitude and the position of the quadcopter. This control has H∞ performance which is used to maintain the quadcopter’s stability and toughness. Then, the gain controller is obtained by using the numerical iterative of Linear Matrix Inequality (LMI). Where as, the CommandGenerator Tracker (CGT) used for tracking position control on the X and Y axes. Based on the research problems, this study will present the tracking control design in the horizontal area by adding the Line of Sight algorithm in order to change the path into the zero. The simulation result shows that the control method used is able to bring the yaw, pitch, and roll to the expected values on a circular path.

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Improved LQR Control Using PSO Optimization and Kalman Filter Estimator

Cited by 27 publications

References 35 publications

Speed control of brushless DCmotors using (conventional, heuristic, and intelligent) methods-based PID controllers

Speed control of brushless DCmotors using (conventional, heuristic, and intelligent) methods-based PID controllers

Enhancing Speed Estimation in DC Motors using the Kalman Filter Method: A Comprehensive Analysis

Quadcopter Movement Analysis Using Output Feedback Control Based on Line of Sight

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