PID control of robot manipulators actuated by BLDC motors

Hernández-Guzmán, Victor Manuel; Orrante-Sakanassi, Jorge Alberto

doi:10.1080/00207179.2019.1590648

Cited by 15 publications

(5 citation statements)

References 16 publications

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“…The inclusion of BLDC motor dynamics with manipulator dynamics has received limited investigation in the literature and the majority of existing works rely on full state measurements. In References 24,25, PID‐based controllers have been designed for robot manipulators driven by BLDC motors. However, they rely on knowledge of the electrical model and require full state measurements.…”

Section: Introductionmentioning

confidence: 99%

Tracking control of robot manipulators actuated by brushless DC motors: Elimination of joint velocity measurements with a robust observer

Unver,

Selim,

Saka

et al. 2024

Intl J Robust & Nonlinear

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This work introduces an innovative robust partial state feedback controller designed for robotic manipulators actuated by brushless DC motors. The proposed controller/observer structure relies solely on actuator current and robot joint position measurements, while effectively compensating for dynamic uncertainties in both the electrical (actuator dynamics) and mechanical (robot's dynamical terms) subsystems. Specifically, a model–based robust observer, eliminating the need of joint velocity measurements, is combined with a backstepping‐type controller design. As opposed to the previous model based observers that depend on the actual model parameters, the proposed observer structure utilizes the best guest estimates of the system parameters supported with a robust compensation term. This approach eliminates the need for precise knowledge of system parameters of the observer design which is a significant improvement over most of the previous results. This approach ensures the semi‐global, uniformly ultimately bounded joint tracking error signal. The overall stability of the closed‐loop system is affirmed through Lyapunov‐based arguments. Experimental studies conducted on an in‐house‐built two‐link robotic manipulator, actuated by brushless DC motors, are presented to demonstrate the effectiveness and feasibility of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Tracking control of robot manipulators actuated by brushless DC motors: Elimination of joint velocity measurements with a robust observer

Unver,

Selim,

Saka

et al. 2024

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…To compensate for this, the BLDC has grown into one of the most prevalent machines in power systems owing to its improved torque, vital speed, and exceptional preciseness [1]. As a consequence of its improved dynamic performance and lack of frequent servicing, it is regarded as one of the top selections for applications such as electric vehicles [2], [3].…”

Section: Introductionmentioning

confidence: 99%

A Comparison of PI and RBF Brushless DC Motor Speed Control Methods

Farrag,

Lai,

Darwish

2023

2023 58th International Universities Power Engineering Conference (UPEC)

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Brushless Direct Current (BLD widely used in electromobility and industrial robots.BLDC motors are essential in many production applications. However, they encounter significant challenges when it comes to executing control of speed. Due to their simplicity, speed controllers are often designed using Proportional Integral (PI) regulation. The saturation of standard PI control makes the system unreliable, hence an online radial basis function (RBF) neural network is proposed. The paper compares and evaluates the speed response of two regulators under a reference speed of 3000 RPM. The purpose is to examine and contrast the performance of these regulators in regulating the speed of the system. In comparison to the traditional PI controller, the presented controller demonstrates superior characteristics such as lower overshoot, improved response speed and greater anti-disturbance capability. The studies are conducted in MATLAB/Simulink.

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“…At present, the commonly used dynamic control methods mainly include intelligent PID control [3][4][5], iterative learning control [6][7][8][9], adaptive neural network control [10][11][12][13], sliding mode control [14][15][16], and active disturbance rejection control [17,18]. Aiming at ndegree-of-freedom rigid robots, Hernández-Guzmán and Orrante-Sakanassi [4] proposed a control scheme for directdrive brushless direct-current (BLDC) motors, which solved the position control problem of n direct-drive BLDC with complex, nonlinear, and highly coupled mechanical loads. Bouakrif and Zasadzinski [7] designed a high-order iterative learning controller for the trajectory tracking of robot manipulators subject to external disturbances and performing repetitive tasks.…”

Section: Introductionmentioning

confidence: 99%

Modified Linear Active Disturbance Rejection Control for Uncertain Robot Manipulator Trajectory Tracking

Xiao

Shen

2021

Mathematical Problems in Engineering

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To solve the problems of model uncertainties, dynamic coupling, and external disturbances, a modified linear active disturbance rejection controller (MLADRC) is proposed for the trajectory tracking control of robot manipulators. In the computer simulation, MLADRC is compared to the proportional-derivative (PD) controller and the regular linear active disturbance rejection controller (LADRC) for performance tests. Multiple uncertain factors such as friction, parameter perturbation, and external disturbance are sequentially added to the system to simulate an actual robot manipulator system. Besides, a two-degree-of-freedom (2-DOF) manipulator is constructed to verify the control performance of the MLADRC. Compared with the regular LADRC, MLADRC is significantly characterized by the addition of feedforward control of reference angular acceleration, which helps robot manipulators keep up with target trajectories more accurately. The simulation and experimental results demonstrate the superiority of the MLADRC over the regular LADRC for the trajectory tracking control.

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PID control of robot manipulators actuated by BLDC motors

Cited by 15 publications

References 16 publications

Tracking control of robot manipulators actuated by brushless DC motors: Elimination of joint velocity measurements with a robust observer

Tracking control of robot manipulators actuated by brushless DC motors: Elimination of joint velocity measurements with a robust observer

A Comparison of PI and RBF Brushless DC Motor Speed Control Methods

Modified Linear Active Disturbance Rejection Control for Uncertain Robot Manipulator Trajectory Tracking

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