Fast and accurate speed regulation of brushless DC motor servo systems via robust composite nonlinear control

2017 ◽  
Author(s):  
Yubin Zhang ◽  
Guoyang Cheng ◽  
Jin-gao Hu ◽  
Yanwei Huang
Keyword(s):  
Nonlinear Control ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Servo Systems ◽  
Brushless Dc ◽  
Speed Regulation

Research on DC Motor Intelligent Control Algorithm

2013 ◽  
Vol 462-463 ◽  
pp. 775-781 ◽  
Author(s):  
Li Fang
Keyword(s):  
Intelligent Control ◽  
High Performance ◽  
Dc Motor ◽  
Regulation System ◽  
Brushless Dc Motor ◽  
Brushless Dc ◽  
Speed Regulation ◽  
The Mathematical Model ◽  
Conventional Algorithm ◽  
Improved Algorithm

Based on analyzing the mathematical model of brushless DC motor and shortcomings of the traditional PID control, combining with the intelligent algorithm and the conventional PID, the paper gives a improved algorithm and simulations in MATLAB environment. A brushless DC motor PWM speed regulation system is designed based on high-performance MCU. The improved algorithm and the conventional algorithm control effects were analyzed and compared in the experiment.

scholarly journals PI Controller of Speed Regulation of Brushless DC Motor Based on Particle Swarm Optimization Algorithm with Improved Inertia Weights

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Wei Xie ◽  
Jie-Sheng Wang ◽  
Hai-Bo Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Dc Motor ◽  
Pi Controller ◽  
Brushless Dc Motor ◽  
Swarm Optimization ◽  
Brushless Dc ◽  
Inertia Weight ◽  
Speed Regulation

The brushless director current (DC) motor is a new type of mechatronic motor that has been developed rapidly with the development of power electronics technology and the emergence of new permanent magnet materials. Based on the speed regulation characteristics, speed regulation strategy, and mathematical model of brushless DC motor, a parameter optimization method of proportional-integral (PI) controller on speed regulation for the brushless DC motor based on particle swarm optimization (PSO) algorithm with variable inertia weights is proposed. The parameters of PI controller are optimized by PSO algorithm with five inertia weight adjustment strategies (linear descending inertia weight, linear differential descending inertia weight, incremental-decremented inertia weight, nonlinear descending inertia weight with threshold, and nonlinear descending inertia weight with control factor). The effectiveness of the proposed method is verified by the simulation experiments and the related simulation results.

Application of ARM in BLDCM Control System

2011 ◽  
Vol 130-134 ◽  
pp. 3489-3492
Author(s):  
Wu Zhang ◽  
Xiao Xu ◽  
Xiao Yi Ying
Keyword(s):  
Control System ◽  
High Performance ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
External Circuit ◽  
Brushless Dc ◽  
Speed Regulation

According to the control characteristics of brushless DC motor, a control system based on the LPC1700 ARM is designed, together with the corresponding external circuit. This system fully utilizes the high-performance 32-bit calculation of ARM chips and abundant hardware resources. It is compact in structure, reliable in operation and superior in speed regulation performance.

scholarly journals Performance Study of Enhanced Non-Linear PID Control Applied on Brushless DC Motor

2018 ◽  
Vol 9 (2) ◽  
pp. 536 ◽  
Author(s):  
Mohamed Shamseldin ◽  
Mohamed Abdel Ghany ◽  
Abdel Ghany Mohamed
Keyword(s):  
Pid Control ◽  
Dc Motor ◽  
Control Technique ◽  
Brushless Dc Motor ◽  
Performance Study ◽  
Brushless Dc ◽  
Speed Regulation ◽  
Speed Tracking ◽  
Motor Drive System ◽  
Fractional Order Pid

<span style="color: black; font-family: 'Times New Roman',serif; font-size: 9pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA; mso-bidi-font-style: italic;">This paper presents an enhanced nonlinear PID (NPID) controller to follow a preselected speed profile of brushless DC motor drive system. This objective should be achieved regardless the parameter variations, and external disturbances. The performance of enhanced NPID controller will be investigated by comparing it with linear PID control and fractional order PID (FOPID) control. These controllers are tested for both speed regulation and speed tracking. The optimal parameters values of each control technique were obtained using Genetic Algorithm (GA) based on a certain cost function. Results shows that the proposed NPID controller has better performance among other techniques (PID and FOPID controller).</span>

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