The Brushless DC motor control system Based on neural network fuzzy PID control of power electronics technology

Zhang, Ran; Gao, Lianxue

doi:10.1016/j.ijleo.2022.169879

Cited by 26 publications

(11 citation statements)

References 15 publications

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“…The operator commands the robot system using an interface or joystick [8] for tasks like turning and obstacle traversal. Sensor data from the robot system can be displayed on the interface or a mobile terminal for comprehensive monitoring [9] . The STM32 microcontroller at the core of the robotic system is the main controller that outputs the control signals.…”

Section: Control System Architecturementioning

confidence: 99%

Design and implementation of firefighting reconnaissance robot control system based on master-slave control

Jiang,

Li,

Qin

et al. 2024

J. Phys.: Conf. Ser.

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In response to issues related to casualties and property damage caused by fires, this paper primarily investigates a deformable wheeled firefighting reconnaissance robot with functions such as fire source detection, obstacle avoidance, and map transmission. The control system of the robot is elaborated, with the main motion control system utilizing STM32 technology. Tests were conducted on the robot’s two motion capabilities (wheeled and legged), obstacle avoidance ability, reconnaissance capability, etc. The results indicate compliance with the design requirements.

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Section: Control System Architecturementioning

confidence: 99%

Design and implementation of firefighting reconnaissance robot control system based on master-slave control

Jiang,

Li,

Qin

et al. 2024

J. Phys.: Conf. Ser.

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“…For PID control, the majority of the tuning methods, applied to the DC motor, are parametric and direct tuning methods, as they employ a simple search algorithm to tune the gains of the PID while minimizing a certain cost functional; examples of such implementations are particle swarm optimization [17], gravitational search algorithm [18], and genetic algorithm [19]. AI based methods have also been employed, for example, Artificial Neural Networks (ANN)s [20], fuzzy logic as a supervisory control to perform the tuning of the PID [21] or as a self-tuning control to regulate the position of the DC motor [22].…”

Section: Motor the Most-used Actuator For Manipulatorsmentioning

confidence: 99%

Autotuning of PID controller using the modified relay feedback test and optimization under uncertainty principle for robotic manipulators

Rehan,

Boiko,

Zweiri

2023

IET Control Theory & Appl

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The development of an autotuning mechanism for robotic manipulators, inspired by the success of autotuners in industrial systems, aims to reduce the time and cost of tuning robotic manipulators. This paper introduces an auto‐tuning method for PID controllers in robotic manipulators using the Modified Relay Feedback Test (MRFT) and the Optimization Under Uncertainty (OUU) principle. The mechanism is versatile, suitable for manipulators of varying scales and motor power capacities. It incorporates actuator dynamics and a combined model of Brushless DC motors with an n‐link manipulator for TR development. Various manipulator models, including commercial and open‐source types were used to refine and test the TR. An algorithm is also proposed for tuning commercial manipulators' controllers without changing the existing closed‐loop system structure. Experimental and simulation tests demonstrate the method's effectiveness, showing better performance than traditional approaches, particularly in reducing overshoot and settling time.

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“…Considering the multivariable, nonlinear, and strong coupling characteristics of brushless DC motor [5] , in the practical application process of modern aircraft rudder control, traditional PID controller uses a set of fixed and unchanging control parameters, which makes it difficult to achieve precise control of aircraft rudder deflection angle. In this paper, the brushless DC motor was used as the power source, the aircraft control surface was used as the controlled object, and the double closed loop speed regulation system was used as the basis.…”

Section: Introductionmentioning

confidence: 99%

Design of brushless DC motor simulation action system based on Fuzzy PID

Liu,

Li,

Zhou

et al. 2024

Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023)

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This article designed a simulation actuation system using a brushless DC motor to drive the aircraft control surface, enabling it to deflect the control surface to a specified angle as needed. Firstly, the working principle of brushless DC motor was studied and a simulation model of a double closed-loop speed control system was established. Then, considering the multivariable, nonlinear, and strong coupling characteristics of brushless DC motor, fuzzy PID is introduced for controller design to achieve precise control of rudder surface deflection angle. Finally, the simulation results indicate that the system performance using fuzzy PID controllers has significantly improved compared to traditional PID controllers in terms of Transient Time, Overshoot and Steady-State Error, indicating the effectiveness and superiority of the designed system.

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The Brushless DC motor control system Based on neural network fuzzy PID control of power electronics technology

Cited by 26 publications

References 15 publications

Design and implementation of firefighting reconnaissance robot control system based on master-slave control

Design and implementation of firefighting reconnaissance robot control system based on master-slave control

Autotuning of PID controller using the modified relay feedback test and optimization under uncertainty principle for robotic manipulators

Design of brushless DC motor simulation action system based on Fuzzy PID

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