EFFECTIVE DOUBLE LOOP CONTROL FOR A SQUARE WAVE BRUSHLESS DC MOTOR

A new type of brushless DC motor has been developed by using a square wave rare earth permanent magnet synchronous motor with its double loop control circuit. The double loop control scheme of the drive system yields a combination of desired characteristics including simplified control structure, small ripple torque, high speed accuracy, wide operating speed range, and fast dynamic response. Experimental results confirm excellent characteristics of the motor.

Robust Control Strategy for the Speed Control of Brushless DC Motor

Brushless DC motor ( BLDCM) speed servo system is multivariable,nonlinear and strong coupling. The parameter variation, the cogging torque and the load disturbance easily influence its performance. Therefore,it is difficult to achieve superior performance by using the conventional PID controller. To solve the deficiency,the paper represents the algorithm of active-disturbance rejection control ( ADRC) based on back-propagation ( BP) neural network. The ADRC is independent on accurate system and its extended-state observer can estimate the disturbance of the system accurately. However,the parameters of Nonlinear Feedback ( NF) in ADRC are difficult to obtain. So in this paper,these parameters are self-turned by the BP neural network. The simulation and experiment results indicate that the ADRC based on BP neural network can improve the performances of the servo system in rapidity,control accuracy,adaptability and robustness.

An Advance Commutation Control Method for Low Torque Ripple of Brushless DC Motors

该文给出一种优化的无刷直流电动机变母线电压六拍控制方法。既解决了传统六拍控制策略中由于绕组电感所造成的电流滞后问题,又改善了由于换相所造成的电流脉动问题。该方法是通过在每两拍之间插入一小段缓冲区来实现的,该缓冲区使下一拍将要切入的电流提前切入,同时使当前拍将要切出的电流延迟切出。通过确定缓冲区的起始位置,即超前换相角的大小,保证每一拍所对应的相电流的中心和反电动势的中心重合。通过选取缓冲区开关器件PWM调制的占空比,降低电机运行过程中的换相转矩脉动。该文方法只需根据负载大小选取超前换相角,一旦选定适用于所有转速。文中给出了该方法的理论推导过程和实验验证波形,从实验结果可以发现,电流滞后被消除,换相电流脉动显著减小,电机的利用率得到提高。

Design and implementation of a position sensorless control method for brushless DC motors

Because brushless direct current(BLDC) motors have the advantages of a compact size, high power density, high efficiency, and long operating life time, they are widely used in many industrial products and electric traction systems. It is known that the BLDC motors have no brushes for commutation. They are commutated with electronically commutation. So, the rotor position information of the BLDC motors must be known to understand which winding will be energized according to the energizing sequence. In most of the existing BLDC motor drivers, rotor position information is detected by Hall effect sensors. This kind of mechanical position sensors will bring additional connections and costs, reliability decrease and noise increase. In order to improve the control performance and extend the range of speed regulation for BLDC motors, a position sensorless control method is proposed in this paper. In the proposed control method, rotor position information of the BLDC motors is detected from the back electromagnetic forces(back-EMFs) which are estimated by an unknown-input observer with line to line currents and line to line voltages. For the purpose of verifying the effectiveness of the proposed control method, a model is built and simulated on the Matlab/Simulink platform. The simulation results show that the speed regulation performance of BLDC motors is improved compared with using Hall effect sensors. At the same time, the reliability of the BLDC motors is improved and the costs of them are reduced because the position sensor is eliminated.

Sensorless Control of Four-Switch Inverter for Brushless DC Motor Drive and Its Simulation

The major function of this proposed research is to control the speed of the brushless DC motor with sensor less control for four-switch three phase inverter. This proposed system is simplified the topological structure of the conventional six-switch three phase inverter. In this proposed method, a new structure of four-switch three phase inverter [1] with reduced number of switches for system is introduced to reduce the mechanical commutation, switching losses that occur in the six-switch method. The proposed inverter fed brushless DC motor used in sensorless control schemes which is used for sensing positioning signals. To improve sensor less control performance, four-switch electronic commutation modes based proportional intergral controller scheme is implemented. In this four-switch three phase inverter reduction of switches, low cost control and saving of hall sensor were incorporated. The feasibility of the proposed sensor less control four-switch three phase inverter fed brushless DC motor drive is implemented, analysed using MATLAB/SIMULINK, effective simulation results have been validated out successfully.

Controller Design for Induction and Brushless Motors Using Matlab with Digital Signal Processor (DSP)

The automation process is a very important pillar for Industry 4.0.One of the first steps is the control of motors to improve production efficiency and generate energy savings.In mass production industries,techniques such as digital signal processing(DSP)systems are implemented to control motors.These systems are efficient but very expensive for certain applications.From this arises the need for a controller capable of handling AC and DC motors that improves efficiency and maintains low energy consumption.This project presents the design of an adaptive control system for brushless AC induction and DC motors,which is functional to any type of plant in the industry.The design was possible by implementing Matlab software and tools such as digital signal processor(DSP)and Simulink.Through an extensive investigation of the state of the art,three models needed to represent the control system have been specified.The first model for the AC motor,the second for the DC motor and the third for the DSP control;this is done in this way so that the probability of failure is lower.Subsequently,these models have been programmed in Simulink,integrating the three main models into one.In this way,the design of a controller for use in AC induction motors,specifically squirrel cage and brushless DC motors,has been achieved.The final model represents a response time of 0.25 seconds,which is optimal for this type of application,where response times of 2e-3 to 3 seconds are expected.

Anti-reverse rotation startup method for sensorless brushless DC motor

In order to start up the brushless DC motor （BLDCM） without reverse rotation and smoothly switch the running state of the motor, a novel startup and smoothly switching method for a sensodess BLDCM is presented. Based on the saturation effect of the stator iron, six short voltage pulses are applied to determine the initial rotor position and the rotor can be found within 60°. After that, a series of short and long voltage pulses are used to accelerate the motor and the variation of the response current is utilized to detect the rotor position dynamically. When the motor reaches a certain speed at which the back-electromotive force （EMF） method can be applied, all the power devices are turned off and the running state of the motor is smoothly switched at the moment determined by the relationship between the terminal voltage waveform and the commutation phases. The experimental results verify the feasibility and validity of the proposed method.

Comparative Study between the PID Regulator and the Fuzzy Regulator Applied to the Operation of a Brushless DC Motor

This paper presents the results of research on speed regulation of a brushless DC motor. This is mainly a comparative study between a PID regulator and a fuzzy regulator applied to the operation of this type of engine in order to find the best control. The BLDC engine must operate under various speed and load conditions with improved performance and robust and complex speed control. Because of this complexity, the traditional PID command encounters difficulties in controlling the speed of a BLDC. Another control technique is currently developing and is producing good results. This is the fuzzy controller that handles process control problems, that is, managing a process based on a given set point per action on the variables that describe the process. To achieve the desired results, the brushless DC machine model will be studied. With the model obtained, both types of regulator will be tested. A synthesis of the observed comparison results will enable a conclusion to be drawn on the performance of the two types of regulators driving a BLDC (Brushless DC).

A neural network-based commutation optimization strategy and drive system design for brushless DC motor

An optimized commutation method based on backpropagation(BP)neural network is proposed to resolve the low stability and high-power consumption caused by inaccurate commutation point prediction in conventional commutation strategy during acceleration and deceleration.This article also builds a complete brushless DC motor drive system based on the GD32F103 micro control unit(MCU),with an Artix-7 XC7A35T field programmable gate array(FPGA)to meet the performance requirements of neural network calculation for real-time motor commutation control.Experimental results show that the proposed optimization strategy can effectively improve the system stability during system acceleration and deceleration,and reduce the current spikes generated during speed chan-ges.The system power consumption is reduced by about 11.7%on average.

Optimal state feedback control of brushless direct-current motor drive systems based on Lyapunov stability criterion

This paper develops a unified methodology for a real-time speed control of brushless direct-current motor drive systems in the presence of measurement noise and load torque disturbance. First, the mathematical model and hardware structure of system is established. Next, an optimal state feed back controller using the Kalman filter state estimation technique is derived. This is followed by an adaptive control algorithm to compensate for the effects of noise and disturbance. Those two algorithms working together can provide a very-high-speed regulation and dynamic response over a wide range of operating conditions. Simulated responses are presented to highlight the effectiveness of the proposed control strategy.

Design of BLDCM Driving and Control System for Motorized Treadmill

To satisfy the requirement of developing a new generation of motorized treadmill for a famous domestic manufacturer, a brushless DC motor （BLDCM） driving and control system for motorized treadmill is developed. High integration and reliability of this system are ensured under the condition that intelligent power module （IPM） is used and the protection module is included. Periodic current control method is applied to reduce the average current flowing through the armature winding of the motor when the treadmill is required to start with low speed while large load is added. Piecewise proportion-integration-differentiation （PID） control algorithm is applied to solve the problem of speed fluctuation when impulse load is added. The motorized treadmill of a new generation with the driving and control system has the advantages of high reliability, good speed stability, wide timing scope, low cost, and long life-span. And it is very promising for practical applications.

基于DSP的储能飞轮用BLDCM数字控制系统

储能飞轮系统为了实现卫星飞行姿态控制和能量储存,要求系统中的无刷直流电机同时具有电动和发电两种功能。本文研究了基于DSP储能飞轮用无刷直流电机的数字控制系统。DSP实现控制PI算法和软件换相,功率驱动由IPM实现。

基于模糊BP神经网络的智能轮椅BLDCM控制

现阶段多数轮椅电机仍使用传统PID控制,该控制方式存在控制精准度较低、超调量较大以及抗扰动能力差等问题。为解决以上问题,通过对无刷直流电机进行研究,在分析了其控制方法后,提出一种基于模糊BP神经网络的BLDCM控制方法。首先,研究了BLDCM结构并搭建数学模型。其次,在模型基础上构建了模糊BP神经网络PID控制器。最后,在Matlab/Simulink中搭建整个电机控制系统进行三种不同工况下的运动控制仿真,并与传统PID控制算法进行对比。实验结果表明:模糊BP神经网络PID控制策略能获得更好的PID控制参数,具有良好的抗扰动能力,有效的改善了整个轮椅控制系统的动态性能。

The Design of New Sensorless BLDCM Control System for Electric Vehicle

In order to meet the requirement of reliably running which is by Electric Vehicle for motor controller, the paper is focused on a sensorless brushless DC motor controller design and a commutation point method. By utilizing the saturation effect of stator iron core, six short voltage pulses are employed to estimate the initial rotor position. After that a series of voltage pulses are used to accelerate the motor. When the motor reaches a certain speed at which the back-electromotive force (EMF) method can be applied, the running state of the motor is smoothly switched at the moment determined by the relationship between the terminal voltage waveform and the commutation phases. “Lagging 90?-α commutation” is bring forward to overcome the shortages existing in the traditional method. The experimental results verify the feasibility and validity of the proposed method.

Speed Control of Motor Based on Improved Glowworm Swarm Optimization

To better regulate the speed of brushless DC motors,an improved algorithm based on the original Glowworm Swarm Optimization is proposed.The proposed algorithm solves the problems of poor robustness,slow convergence,and low accuracy exhibited by traditional PID controllers.When selecting the glowworm neighborhood set,an optimization scheme based on the growth and competition behavior of weeds is applied to a single glowworm to prevent falling into a local optimal solution.After the glowworm’s position is updated,the league selection operator is introduced to search for the global optimal solution.Combining the local search ability of the invasive weed optimization with the global search ability of the league selection operator enhances the robustness of the algorithm and also accelerates the convergence speed of the algorithm.The mathematical model of the brushless DC motor is established,the PID parameters are tuned and optimized using improved Glowworm Swarm Optimization algorithm,and the speed of the brushless DC motor is adjusted.In a Simulink environment,a double closed-loop speed control model was established to simulate the speed control of a brushless DC motor,and this simulation was compared with a traditional PID control.The simulation results show that the model based on the improved Glowworm Swarm Optimization algorithm has good robustness and a steady-state response speed for motor speed control.

基于参数自整定模糊PID的BLDC控制研究

为解决传统PID控制在无刷直流电机调速系统中的控制精度低、效果不佳等问题,设计了一种基于参数自整定模糊PID控制的调速系统。通过在Matlab/Simulink仿真软件中建立了无刷直流调速系统的模型,分别采用传统PID控制、模糊PID控制和参数自整定模糊PID控制来对转速环进行调控,而电流环则采用PID控制。通过对比研究结果发现,采用参数自整定模糊PID控制的调速系统具有许多优势。系统的超调量较小,控制效果较好,同时提高了系统的鲁棒性。通过搭建模型并进行仿真实验,证明了采用参数自整定模糊PID控制的调速系统在解决无刷直流电机调速系统控制精度低、效果不佳等问题方面具有优势。这一方法能够有效提升系统的控制性能,并增强系统的鲁棒性。该无刷直流电机的调速系统可以稳定、可靠运行,满足使用需求。

开绕组BLDCM直接转矩控制电压矢量特性研究

基于直接转矩控制(DTC)的开绕组无刷直流电机(BLDCM)具有运行效率高、电压矢量多样、控制结构简单等优点,适用于工业领域。根据共直流母线开绕组BLDCM控制拓扑搭建了相应的数学模型,对该拓扑下电压矢量的特性进行理论分析及分类,并将电压幅值不为零的电压矢量分为大、中、小三类。分析结果表明:在相同的运行条件下,大矢量作用下转矩变化率最大,小矢量作用下转矩变化率最小,中矢量居于两者之间。仿真结果验证了理论分析的正确性和控制方法的可行性。

基于DSP的无刷直流电机无传感器控制系统设计

针对以往无刷直流电动机反电势法无传感器控制系统存在的一些问题，设计了一种基于数字信号处理器（ＤＳＰ）的无刷直流电动机无传感器控制系统，详细介绍了系统的控制方案。实验结果表明，系统的硬件和软件设计合理，具有良好的调速性能。

基于DSP永磁无刷直流电动机位置伺服系统

提出了一种基于数字信号处理 (DSP)无刷直流电动机位置伺服系统 ,该系统充分利用了DSP周边端口丰富 ,运算速度快的特点 ,使系统硬件结构简单。实验表明 ,系统具有良好的定位性能。