Adaptive PID Controller Using for Speed Control of the BLDC Motor

Mahmud, Md. Zobair Al; Motakabber, S. M. A.; Alam, A. H. M. Zahirul; Nordin, Anis Nurashikin

doi:10.1109/icse49846.2020.9166883

Cited by 47 publications

(15 citation statements)

References 9 publications

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“…Fuzzy PID attitude control of a vehicle is considered in [11]. An adaptive PID controller is presented in [12] for controlling speed of a brushless DC motor. Another speed control application is proposed in [13] using intelligent PID control with applications to an ultrasonic motor.…”

Section: Related Workmentioning

confidence: 99%

A Comparative Study on The Tuning of The PID Flight Controllers Using Swarm Intelligence

Kaba

2020

IJAST

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QUAVs have some shortcomings in terms of nonlinearities, coupled dynamics, unstable open–loop characteristics, and they are prone to internal and external disturbances. Therefore, control problem of the QUAVs is still an open issue. Designed controllers based on the linear dynamics have limited operating ranges. Therefore, nonlinear dynamics of the QUAVs must be derived and used in the control problem. Although some advanced controllers are presented for QUAV control, PID controllers are the most employed, well–known controllers with the simple structure, ease of implementation, solid functionality and robustness amongst the variations up to a degree. In this paper, PID based controllers are proposed for the nonlinear attitude dynamics to overcome the control problem of the QUAVs. However, since optimality and tuning of the PID controllers are fuzzy because of trial and error approaches, swarm intelligence based meta-heuristic algorithms (ABC, ACO and PSO) are employed to optimize the PID coefficients. Results are compared in terms of transient analysis and MC analysis to cover the rise time, settling time, percentage overshoot, steady–state error for the former and stochastic fitness evaluation for the latter, respectively.

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Section: Related Workmentioning

confidence: 99%

A Comparative Study on The Tuning of The PID Flight Controllers Using Swarm Intelligence

Kaba

2020

IJAST

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“…In the previous study, the use of PID control was implemented on a quadcopter as an Unmanned Aerial Vehicle (UAV) [1], Multiple motor synchronization [2], Control of Twin Rotor MIMO System [3], BLDC Motor [4] [5], 2DOF Rotary Torsion Plant [6] [7], Unmanned Agricultural Vehicle [8], Active Magnetic Bearing Rotor System [9], DC Motor Speed Control [10] [11] and Marine Diesel Control Speed [12]. The PID control system starts with finding the motor characteristics using transfer function modeling.…”

Section: Introductionmentioning

confidence: 99%

DC Motor PID Control System for Tamarind Turmeric Herb Packaging on Rotary Cup Sealer Machine

Fauziyah

Adhisuwignjo

Ifa³

et al. 2022

KINETIK

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The end of this research is to find PID tuning value on the packaging automation process using the PID method. By finding the most suitable PID tuning value, a fast packaging process is obtained. Herbal ingredients in herbs that are left in the open for a long time tend to be damaged more quickly. So after the production process ends, the herbs must be packaged quickly. With the packaging automation method, the product can be hygienic and does not spoil quickly. One of the most widely and easy-to-use for automation methods in the industry is the PID control method because it can accelerate the system response, stabilize the system to match the setpoint and minimize overshoot. This study will discuss how the design of the PID control system using DC motor transfer function modeling in Matlab and the Second Ziegler-Nichols PID tuning method, the effect of the load on the motor response, and the effect of PID on the production speed. The system was tested with PID tuning values are Kp = 12, Ki = 12,506, Kd = 0.0028785, speed motor 24 RPM and a load of 3,160 Kg produces a good output response are delay time = 0.502 s, rise time = 0.804 s, settling time = 4.023 s, peak time = 133.084 s, Overshoot = 0.125% and Steady State Error = 0%. The effect of PID control on production speed is 83% faster than manual production and 29% faster than systems without PID.

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“…The PID controller is one of the most common used classical control systems in different industries because of its flexibility, satisfactory results [ 23 , 24 ], ease of implementation in a control system and wide usage in industries [ 25 , 26 ]. In order to enhance the accuracy and robustness of classical PID control, one of the techniques is to combine it with optimization methods [ 27 , 28 ].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Trajectory Tracking Behavior of a Multi-Joint Robotic Arm via Genetic–Swarm Optimization for the Inverse Kinematic Solution

Amiri

Ramli

2021

Sensors

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It is necessary to control the movement of a complex multi-joint structure such as a robotic arm in order to reach a target position accurately in various applications. In this paper, a hybrid optimal Genetic–Swarm solution for the Inverse Kinematic (IK) solution of a robotic arm is presented. Each joint is controlled by Proportional–Integral–Derivative (PID) controller optimized with the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), called Genetic–Swarm Optimization (GSO). GSO solves the IK of each joint while the dynamic model is determined by the Lagrangian. The tuning of the PID is defined as an optimization problem and is solved by PSO for the simulated model in a virtual environment. A Graphical User Interface has been developed as a front-end application. Based on the combination of hybrid optimal GSO and PID control, it is ascertained that the system works efficiently. Finally, we compare the hybrid optimal GSO with conventional optimization methods by statistic analysis.

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Adaptive PID Controller Using for Speed Control of the BLDC Motor

Cited by 47 publications

References 9 publications

A Comparative Study on The Tuning of The PID Flight Controllers Using Swarm Intelligence

A Comparative Study on The Tuning of The PID Flight Controllers Using Swarm Intelligence

DC Motor PID Control System for Tamarind Turmeric Herb Packaging on Rotary Cup Sealer Machine

Intelligent Trajectory Tracking Behavior of a Multi-Joint Robotic Arm via Genetic–Swarm Optimization for the Inverse Kinematic Solution

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