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.

INTELLIGENT CONTROL SYSTEM OF PULSED MAG WELDING INVERTER BASED ON DIGITAL SIGNAL PROCESSOR

A fuzzy logic intelligent control system of pulsed MAG welding inverter based on digital signal processor （DSP） is proposed to obtain the consistency of arc length in pulsed MAG welding. The proposed control system combines the merits of intelligent control with DSP digital control. The fuzzy logic intelligent control system designed is a typical two-input-single-output structure, and regards the error and the change in error of peak arc voltage as two inputs and the background time as single output. The fuzzy logic intelligent control system is realized in a look-up table （LUT） method by using MATLAB based fuzzy logic toolbox, and the implement of LUT method based on DSP is also discussed. The pulsed MAG welding experimental results demonstrate that the developed fuzzy logic intelligent control system based on DSP has strong arc length controlling ability to accomplish the stable pulsed MAG welding process and controls pulsed MAG welding inverter digitally and intelligently.

Real-Time Discrete Adaptive Control of Robot Arm Based on Digital Signal Processing

A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.

Direct Digital Frequency Control Based on the Phase Step Change Characteristic between Signals

We present a new digital phase lock technology to achieve the frequency control and transformation through high precision multi-cycle group synchronization between signals without the frequency transformation circuit. In the case of digital sampling, the passing zero point of the phase of the controlled signal has the phase step characteristic, the phase step of the passing zero point is monotonic continuous with high resolution in the phase lock process, and using the border effect of digital fuzzy area, the gate can synchronize with the two signals, the quantization error is reduced. This technique is quite different from the existing methods of frequency transformation and frequency synthesis, the phase change characteristic between the periodic signals with different nominal is used. The phase change has the periodic phenomenon, and it has the high resolution step value. With the application of the physical law, the noise is reduced because of simplifying frequency transformation circuits, and the phase is locked with high precision. The regular phase change between frequency signals is only used for frequency measurement, and the change has evident randomness, but this randomness is greatly reduced in frequency control, and the certainty of the process result is clear. The experiment shows that the short term frequency stability can reach 10-12/s orders of magnitude.

Digital control of pulsed gas metal arc welding inverter using TMS320LF2407A

A digital control of pulsed gas metal arc welding inverter was proposed. A control system consisting of analogue parts was replaced with a new digital control implemented in a TMS320LF2407A DSP chip. The design and constructional features of the whole digital control were presented. The resources of the DSP chip were efficiently utilized and the circuits are very concise, which can enhance the stability and reliability of welding inverter. Experimental results demonstrate that the developed digital control has the ability to accomplish the excellent pulsed gas metal arc welding process and the merits of the developed digital control are stable welding process, little spatter and perfect weld appearance.

Pure Digital Control for the Outer Axis of a Three-Axis Flight Simulation Table

In this paper, a pure digital control method for the outer axis of a three-axis flight simulation table is worked out and a state observer is used to obtain the acceleration signal. The method is simple and easy to be emplayed, and especially suitable for the electrohydraulic (?)ervo-system with fast response. The simulation results show that the system given in this paper has optimal three-order system performance.

Adaptive Learning with Large Variability of Teaching Signals for Neural Networks and Its Application to Motion Control of an Industrial Robot

Recently, various control methods represented by proportional-integral-derivative （PID） control are used for robotic control. To cope with the requirements for high response and precision, advanced feedforward controllers such as gravity compensator, Coriolis/centrifugal force compensator and friction compensators have been built in the controller. Generally, it causes heavy computational load when calculating the compensating value within a short sampling period. In this paper, integrated recurrent neural networks are applied as a feedforward controller for PUMA560 manipulator. The feedforward controller works instead of gravity and Coriolis/centrifugal force compensators. In the learning process of the neural network by using back propagation algorithm, the learning coefficient and gain of sigmoid function are tuned intuitively and empirically according to teaching signals. The tuning is complicated because it is being conducted by trial and error. Especially, when the scale of teaching signal is large, the problem becomes crucial. To cope with the problem which concerns the learning performance, a simple and adaptive learning technique for large scale teaching signals is proposed. The learning techniques and control effectiveness are evaluated through simulations using the dynamic model of PUMA560 manipulator.

Intelligent Vehicle Driving Controller Design and Implementation Evaluation

An intelligent vehicle control system is designed and embedded in a Digital Signal Processing （DSP） platform （eZdspTM F2812）. A golf cart is used as an installation platform for the overall system, including steering wheel Alternating Current （AC） serve motor, brake actuator, throttle driving circuit and sensors. Digital image processing technology is also used to enable the autonomous driving system to achieve multi-mode lane-keeping, lane-change and obstacle-avoidance. The overall system is tested and evaluated on a university campus.

A Real-Time Power Controller for Grid-Connected Inverters in LV Smart Microgrids

This paper presents a real-time power flow controller for VSIs （voltage source inverters） interfaced to low voltage microgrids. The proposed controller is modular, flexible, intelligent, inexpensive, portable, adaptive and designed to positively contribute in low voltage microgrids in which the lines R/X ratio is greater than the transmission lines. Therefore, the proposed control strategy is developed for operation in distribution lines. The controller strategy is different from the conventional grid-connected inverters which are designed based on transmission line characteristics. This controller, using a Texas Instrument general purpose DSP （digital signal processor）, is programmed and tuned using MATLAB/SIMULINK in order to enhance self-healing, reliability and stability of the grid. This general purpose controller makes proper decisions using its local measurements as the primary source of data. The controller has the capability of communicating with the adjacent controllers and sharing the information if/when needed. The power flow output of the inverter is tested for both islanded and grid-connected modes of operation. The inverter positively contributes to active and reactive power supply while operating in grid-connected mode. The proposed control method has been implemented on a Texas Instrument DSC （digital signal controller） chip and tested on a hardware test bench at the Alternative Energy Laboratory at WVU1T （West Virginia University Institute of Technology）. The system＇s experimental results veri~ the validity and efficiency of the proposed controller.

基于STM32的辨音识别系统的设计与应用

声音识别技术能够用于多种环境参数检测,本文采用STM32的DSP技术,对全向拾音器采集到环境声音进行快速傅里叶变换(FFT),获取待测声音的主频率和次频率,通过液晶屏显示采集信号的强度和主要频率分量。该设备能够有效对环境声音的主要参赛进行检测,在噪声检测和一般设备运行故障检测具有较高的适用性。

快速刀具伺服系统位置域重复控制设计及其数字实现

在非圆零件车削过程中,快速刀具伺服(Fast tool servo,FTS)的运动精度直接影响零件的加工质量.主轴变速加工使得FTS的参考目标信号周期时变而不确定,这对实现其渐近跟踪提出了极大的挑战.本文利用FTS的位置域周期特性,提出一种基于位置域重复控制和时域速度反馈镇定的FTS系统复合控制设计方法,并给出位置域改进型重复控制器(Spatial modified repetitive controller,SMRC)的数字实现算法,实现对时变周期参考目标信号的高精度跟踪.首先,建立包含位置相关时变周期参考目标信号内模的SMRC,并引入位置域相位超前装置对镇定补偿器引起的相位滞后进行补偿,在此基础上构建复合控制律.然后应用小增益定理和算子理论,推导出控制系统的稳定性条件,在保持系统采样频率不变的条件下,应用插值法建立SMRC的数字实现算法,确保位置域重复控制和时域镇定控制器的同步执行.最后,通过仿真验证所设计的FTS控制系统具有满意的时变周期跟踪性能和鲁棒性,并通过与其他位置域重复控制方法的比较,说明所提方法同时具有更好的暂态和稳态性能.

高性能双轴振镜控制系统设计

针对高速高精度的激光微加工应用,提出一种基于并行处理架构的全数字控制双轴振镜驱动系统设计方案,在高频数字控制下实现了双轴振镜的高动态实时控制。通过建立振镜系统数学模型,以串级闭环控制为基础,采用模型跟踪控制策略提升了位置跟踪性能。实验结果表明所设计的双轴振镜控制系统能够有效提升动态响应速度、降低跟踪误差,满足期望工作性能指标.

基于大创项目的应用技术开发实践——以数字电源教具设计为例

针对教学环节中的难点和重点内容,基于dsPIC33CK256MP505数字信号控制器芯片,为开发新型的数字电源教具,在降压转换器的电路拓扑结构基础上,利用MplabPowerSmart开发软件,完成了电压控制型数字环路补偿器的设计,实现3P3Z数字补偿器的实时算法功能。

基于指数趋近率的液压机泵控伺服系统滑模控制

滑模控制方法具备较强鲁棒性,控制器结构也较简单,被广泛应用于泵控电液伺服液压系统上。在分析泵控系统原理的基础上,为克服传统PID控制很难抵抗较强外部干扰力的缺点,泵控伺服系统建立指数趋近律滑模控制器,建立泵控伺服系统MATLAB/Simulink仿真。研究结果表明:正弦信号跟踪下,滑模控制最大稳态跟踪误差与PID相比降低83.4%,同时控制器IMSE指标相对PID控制器发生了显著降低。该研究有助于提高液压机运行效率,对提高产品质量具有一定的指导意义。

面向HKSEDSPC6713系列DSP的主动噪声控制系统设计

微处理器芯片的生态建设是高端装备与智能微系统自主、可控的关键,尽管国产数字信号处理(digital signal processing, DSP)器件及其相关开发应用技术近年来得到了一定的发展,但与需求仍存在较大差距。在主动噪声控制领域,前馈型多通道控制方案比单通道有较大的控制范围和较好的性能,但对系统的运算能力有较高的要求。文章以多通道FxLMS算法为基础,对多通道降噪系统的运算量进行了分析,依据国产DSP开发板的电路结构,设计了控制系统方案,并进行了实验研究。实验表明,所设计的噪声控制系统运算效率较ARM作为运算器提高了80%,对100~1 000 Hz内的周期性噪声信号衰减达到15~20 dB,证明了该方案的正确性。

非线性环路补偿的交错并联BUCK变换器数字控制策略研究

针对氢能燃料电池输出低电压、大电流,不能适用通讯基站电源的问题,设计了一种电力电子交错并联BUCK变换器,同时提出了一种非线性环路补偿的数字控制策略。文中采用两个BUCK电路并联,控制信号为180°两相交错脉冲宽度控制,采用小信号模型建立了电压环、电流环数学模型,控制策略采用电流内环、电压外环双闭环控制。为了控制快准稳,分别对两环路控制策略补偿校正设计,通过环路补偿数字控制策略搭建交错并联BUCK变换器simulink模型,仿真结果表明变换器在输入范围下实现了48 V直流稳定输出,验证了本研究的有效性。

DR设备利用信号传递特性得出准确剂量指示质量控制方法的研究

目的:探究数字X射线摄影(DR)设备利用信号传递特性(STP)得出准确探测器剂量指示(DDI)的质量控制方法。方法:通过STP绘制拟合回归曲线,得出剂量与DDI值或像素值的计算公式,计算得出影像接收器入射空气比释动能10μGy对应的基线值。结果:SYNTHESIS型DR摄影机的剂量与像素值对数相关公式为y=-1455ln(x)+7311.1,回归到剂量x=10μGy,得出像素值y=3961。Brivo XR515型DR摄影机的剂量与像素值线性响应公式为y=140.33x-2.3445,回归到剂量x=10μGy,得出准确的像素值y=1401。结论:此方法可以准确地完成DR设备验收检测和状态检测的DDI项目,并得到客观准确的评价。

“基于Speedgoat的主动降噪”信号处理实验设计

“基于Speedgoat的主动降噪”是“信号处理实验”课程新型实验,能够巩固学生的理论知识,培养实践能力,联系实际应用。该实验以Speedgoat为硬件实验平台,以主动降噪技术为理论应用载体,旨在加深学生对LMS、FxLMS算法的学习和理解。内容不仅贴近生活与科技应用需求,吸引学生的兴趣,而且能从实用性角度加深学生对于语音信号处理方法和自适应算法的认知。实验课程推行后受到了学生的肯定与欢迎,教学效果突出。

轻量化音频信号处理算法与FPGA实现

为了解决语音通信系统中音频信号处理的数据量大,杂散信号多,以及调频接收机在接收到的音频信号忽大忽小的问题,提出了一种轻量化音频信号处理算法,并基于此算法在现场可编程门阵列(FPGA)平台上实现了音频信号的接收与自动增益控制。该算法结合数字下变频技术、多级抽取滤波技术及自动增益控制技术(AGC),应用于音频信号处理系统中,将从上级天线接收的射频模拟信号通过模数转换以及数字下变频转换为基带音频信号,经四级抽取滤波将基带信号中的杂散信号滤除,降低了系统的复杂性和功耗,同时AGC对基带音频信号进行控制调整,输出较为稳定的音频信号。经过实验证明:该算法能够有效地将信息速率从102.4 MHz降至32 kHz、减少计算负担、提高信号质量、降低了FPGA的资源利用率;并且实现音频信号的自动增益控制调整,其调整时间仅为12.8μs,满足接收机的功率稳定时间。

一种工业巡检机器人的控制系统设计

介绍基于钢轨行走的工业巡检机器人控制系统的设计,阐述各部分的作用和相互之间的连接关系,针对应用多传感器不利于主控制模块控制算法运行的问题,将主控制模块和信号处理模块分开,通过串口进行数据交互,减少了主控制模块的压力。分析部件接口和供电,对主控制模块和信号处理模块进行硬件设计,设计控制系统的软件。编写调试界面,在实验室调试控制系统,验证了控制系统的实用性。