Application of Diagonal Recurrent Neural Network toDC Motor Speed Control Systems

A new kind of dynamic neural network--diagonal recurrent neural network (DRNN) and its learning method and architecture are presented. A direct adaptive control scheme is also developed that is applied to a DC (Direct Current) speed control system with the ability to auto-tune PI (Proportion Integral) parameters based on combining DRNN with PI controller. The simulation results of DRNN show better control performances and potential practical use in comparison with PI controller.

Design and Test of Motor Double Fed Speed Regulating System for Conveyer Belt

This paper introduces the design of doubly fed system for conveyor belt motor, the system adopts stator flux orientation vector control technology and AC-AC inverter motor speed and power factor control, and carried on the test in transmission field. This paper introduces in detail the structure and characteristic of DSP system, and gives a design scheme of Doubly Fed Speed Control System of motor based on this chip.

A Model-Based Unmatched Disturbance Rejection Control Approach for Speed Regulation of a Converter-Driven DC Motor Using Output-Feedback

The speed regulation problem with only speed measurement is investigated in this paper for a permanent magnet direct current(DC)motor driven by a buck converter.By lumping all unknown matched/unmatched disturbances and uncertainties together,the traditional active disturbance rejection control(ADRC)approach provides an intuitive solution for the problem under consideration.However,for such a higher-order disturbed system,the increase of poles for the extended state observer(ESO)therein will lead to drastically growth of observer gains,which causes severe noise amplification.This paper aims to propose a new model-based disturbance rejection controller for the converter-driven DC motor system using output-feedback.Instead of estimating lumped disturbances directly,a new observer is constructed to estimate the desired steady state of control signal as well as errors between the real states and their desired steady-state responses.Thereafter,a controller with only speed measurement is proposed by utilizing the estimates.The performance of the proposed method is tested through experiments on dSPACE.It is further shown via numerical calculations and experimental results that the poles of the observer within the proposed control approach can be largely increased without significantly increasing magnitude of the observer gains.

Current Search: Performance Evaluation and Application to DC Motor Speed Control System Design

This paper proposes the current search (CS) metaheuristics conceptualized from the electric current flowing through electric networks for optimization problems with continuous design variables. The CS algorithm possesses two powerful strategies, exploration and exploitation, for searching the global optimum. Based on the stochastic process, the derivatives of the objective function is unnecessary for the proposed CS. To evaluate its performance, the CS is tested against several unconstrained optimization problems. The results obtained are compared to those obtained by the popular search techniques, i.e., the genetic algorithm (GA), the particle swarm optimization (PSO), and the adaptive tabu search (ATS). As results, the CS outperforms other algorithms and provides superior results. The CS is also applied to a constrained design of the optimum PID controller for the dc motor speed control system. From experimental results, the CS has been successfully applied to the speed control of the dc motor.

Revisiting the LQR Problem of Singular Systems

In the development of linear quadratic regulator(LQR) algorithms, the Riccati equation approach offers two important characteristics——it is recursive and readily meets the existence condition. However, these attributes are applicable only to transformed singular systems, and the efficiency of the regulator may be undermined if constraints are violated in nonsingular versions. To address this gap, we introduce a direct approach to the LQR problem for linear singular systems, avoiding the need for any transformations and eliminating the need for regularity assumptions. To achieve this goal, we begin by formulating a quadratic cost function to derive the LQR algorithm through a penalized and weighted regression framework and then connect it to a constrained minimization problem using the Bellman's criterion. Then, we employ a dynamic programming strategy in a backward approach within a finite horizon to develop an LQR algorithm for the original system. To accomplish this, we address the stability and convergence analysis under the reachability and observability assumptions of a hypothetical system constructed by the pencil of augmented matrices and connected using the Hamiltonian diagonalization technique.

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.

DC Motor Speed Regulator via Active Damping Injection and Angular Acceleration Estimation Techniques

This paper suggests a novel model-based nonlinear DC motor speed regulator without the use of a current sensor.The current dynamics,machine parameters and mismatched load variations are considered.The proposed controller is designed to include an active damping term that regulates the motor speed in accordance with the first-order low-pass filter dynamics through the pole-zero cancellation.Meanwhile,the angular acceleration and its reference are obtained from simple first-order estimators using only the speed information.The effectiveness is experimentally verified using hardware comprising the QUBEServo2,myRIO-1900,and LabVIEW.

The research of power saving frequency conversion speed regulation experiment system

A power saving frequency difference controlling method was introduced by the double inverter and motor experiment system.The characters of the system under differ- ent loads were investigated.The theoretical analysis and experiment results show the frequency difference method is a ideal power saving speed regulation method for the dou- ble inverter and motor system.The experiment system is simply structured,convenient to operate and provides a new way of character testing for frequency conversion speed regulation.

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.

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.

Speed Regulation Method Using Genetic Algorithm for Dual Three-phase Permanent Magnet Synchronous Motors

Dual three-phase Permanent Magnet Synchronous Motor(DTP-PMSM)is a nonlinear,strongly coupled,high-order multivariable system.In today’s application scenarios,it is difficult for traditional PI controllers to meet the requirements of fast response,high accuracy and good robustness.In order to improve the performance of DTP-PMSM speed regulation system,a control strategy of PI controller based on genetic algorithm is proposed.Firstly,the basic mathematical model of DTP-PMSM is established,and the PI parameters of DTP-PMSM speed regulation system are optimized by genetic algorithm,and the modeling and simulation experiments of DTP-PMSM control system are carried out by MATLAB/SIMULINK.The simulation results show that,compared with the traditional PI control,the proposed algorithm significantly improves the performance of the control system,and the speed output overshoot of the GA-PI speed control system is smaller.The anti-interference ability is stronger,and the torque and double three-phase current output fluctuations are smaller.

Increasing the Efficiency of Grid Tied Micro Wind Turbines in Low Wind Speed Regimes

Major problem with grid tied micro wind turbine is synchronization and wind variability. Due to this problem the stability of available grid gets reduced. The stability can be achieved by output power control of the turbine. Major part of many countries like India, the annual mean wind speed is not high. The rated wind speed of turbine remain around 11 m/s and cut in is around 3.5 m/s. Due to this problem we aimed to develop a sustainable wind energy system that can provide stable power supply even at the locations of low wind speed of 2 - 4 m/s. To address this issue, a momentary impulse or external torque to the rotor by external motor is one of the good options to maintain the momentum of blades and thus provide stability for sufficient time. Various theoretical calculations and experiments are conducted on the above method. This would increase the output power and also the efficiency of wind turbine. We show that Return-On-Investment will be high as compared with other grid connected turbines. Our proposed concept in the present study, if implemented properly, can help the installation of number of wind turbines even at domestic level. It also makes the consumers energy independent and promotes the use of wind as a source of energy and may enter as a rooftop energy supply system similar to solar.

基于锁相环倍频的BLDCM速度控制系统设计

介绍一种基于锁相环六倍频速度采集的无刷直流电机(BLDCM)控制系统,以高性能处理器STM32为核心控制元件,采用锁相环倍频技术实现对电机转速的高精度控制。该系统包括处理器、驱动电路、逆变电路、倍频电路和电机,其中倍频电路对三路霍尔信号实现六倍频处理,输出作为系统的速度反馈。经仿真和实际测试,所设计的锁相环六倍频电路,能够准确有效地进行速度采集和处理,从而提高控制系统速度采集的精度。实验表明:该控制系统实用性强,具有较高的工程应用价值。

基于Ansoft的高速永磁无刷直流电机磁场有限元分析

基于Maxwell二维瞬态磁场分析理论,依据给定的技术指标,运用RMxprt快速确定电机电磁及结构设计方案,并导入Maxwell中建立二维有限元仿真模型,基于场路耦合有限元法对电机的机械特性和效率进行了仿真分析,仿真结果精确地反映了高速永磁无刷直流电机的启动过程,为电机的优化设计、减少转矩脉动、提高启动转矩提供了理论依据。

基于带抽头电感准Z源变换器的BLDCM控制系统研究

基于带抽头电感的准Z源网络,构建一种永磁无刷直流电机(BLDCM)的控制系统。利用该准Z源网络的高电压增益特性,实现两种工作模式的平滑切换,有效拓宽了无刷直流电机控制系统的调速范围,并弥补了电源端故障时电机转速和转矩特性变差的问题。仿真和实验证明了该方法的有效性、准确性和实时性。

基于PROFIBUS-DP通讯方式的PLC、触摸屏和直流调速器组成的调速系统的设计

由直流调速器构成的直流调速系统具有结构紧凑、可适应性强、维护简便的特点.根据不同的应用场合,可选择单象限或四象限的工作装置.该系统所有的控制、调节、监控及附加功能都由微处理器来实现,其控制功能十分强大.以西门子全数字直流调速器Simoreg dc master 6ra70为例,阐述了数字直流调速系统的设计方法.

高速ADC THS1207在电动车无刷直流电机中的应用

介绍了12bit同步高速模数转换器THS1207的基本原理及工作特性,重点对THS1207在电动车无刷直流电机中的应用做了具体研究,给出了相关硬件电路图和软件设计流程,为电动车无刷直流电机控制器的性能测试做了很好的准备。

基于Profibus-DP的港口起重机械电机调速系统研究"

文中研究设计了一种模拟港口起重机四大机构的交直流电机调速实验系统。系统以西门子PLC站作为控制中心,通过Profibus-DP总线与交直流调速装置通信,实现控制电机运行的目的,满足起重机械四大机构不同工作环境对电机运行的要求,并通过上位机监控电机运行状态,实现安全运行状态监控;同时系统具有能量回馈功能,可以达到能量的循环使用,从而实现节能的目的。

提高BLDCM驱动器调速精度及改善其可控性的方法研究

简要介绍了直流无刷电机调速系统的电路组成和工作原理、测速和测电压的设备连接方式和测量方法.利用原有试验测试平台的测试数据,通过MATLAB拟合分析,得到了电机的调速特性曲线的关系表达式.针对原测试平台的无刷直流电机存在输出转速调节精度较低的问题,提出了通过使用单片机、数据存储器和D/A转换器来改善电机驱动器的调速精度和调速可控的方法.研究表明,该方法能够提高原有电机输出转速的调节精度,能够实现无极调速和自动控制.

基于TMP88CK49的无位置传感器的BLDC控制

介绍了一种利用TMP88CK49微处理器控制无位置传感器的无刷直流电动机的新方法 ,能可靠地实现无刷直流电动机的起动和速度控制。