Contribution of the FPGAs for Complex Control Algorithms: Sensorless DTFC with an EKF of an Induction Motor

Krim, Saber; Gdaim, Soufien; Mtibaa, Abdellatif; Mimouni, Mohamed Faouzi

doi:10.1007/s11633-016-1017-z

Cited by 14 publications

(13 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…With 8 bits, the speedup in Msps for the TS-FIMM-OS, TS-FIMM-P, Fuzzy-PI-OS and Fuzzy-PI-P are 11 [18,20] shows a hardware can achieve about 1 Msps. The work presented in [18] uses two inputs, 25 rules, one output and 8 bits and the designer presented in [20] was projected with three inputs, 42 rules and one output. The speedup in Msps for the TS-FIMM-OS, TS-FIMM-P, Fuzzy-PI-OS and Fuzzy-PI-P are equal to previously calculated values used in [5].…”

Section: Validation Results -Fuzzy-pi Controller Hardwarementioning

confidence: 99%

“…Intelligent systems based on production rules that use Fuzzy Logic in the inference process are called in the literature of Fuzzy Systems (FS) [4]. Among the existing inference strategies, the most used, the Mamdani and the Takagi-Sugeno, are differentiated by the final stage of the inference process [5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20].…”

Section: Introductionmentioning

confidence: 99%

“…The works presented in [30,31,32,33,34,35,36,37] propose implementations of FS on reconfigurable hardware (Field Programmable Gate Array -FPGA), showing the possibilities associated with the acceleration of fuzzy inference processes having a high degree of parallelization. Other works propose specific implementations of Fuzzy Control Systems (FCS) using the Fuzzy Mamdani Inference Machine (M-FIM) and the Takagi-Sugeno Fuzzy Inference Machine (TS-FIM) [5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]. The works presented in [38,39,40] propose the Takagi-Sugeno hardware acceleration for other types of application fields.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Proposal of Takagi–Sugeno Fuzzy-PI Controller Hardware

Silva

Lopes

Valderrama

et al. 2020

Sensors

View full text Add to dashboard Cite

This work proposes dedicated hardware for an intelligent control system on Field Programmable Gate Array (FPGA). The intelligent system is represented as Takagi-Sugeno Fuzzy-PI controller. The implementation uses a fully parallel strategy associated with a hybrid bit format scheme (fixed-point and other floatingpoint). Two hardware designs are proposed; the first one uses a single clock cycle processing architecture, and the other uses a pipeline scheme. The bit accuracy was tested by simulation with a non linear control system of robotic manipulator. The area, throughput, and dynamic power consumption of the implemented hardware are used to validate and compare the results of this proposal. The results achieved allow that the proposal hardware can use in several applications with high-throughput, low-power and ultra-low-latency restrictions such as teleportation of robot manipulators, tactile internet, industrial automation in industry 4.0, and others. such as the tactile Internet [21,22], the Internet of Things (IoT) and Industry 4.0, where the problems associated with processing, power, latency and miniaturization are fundamental. Robotic manipulators used on tactile internet need a high-throughput and ultra-low-latency control system, and this can be achieved with dedicated hardware [21].The development of dedicated hardware, in addition to speeding up parallel processing, makes it possible to operate with clocks adapted to low-power consumption [23,24,25,26,27,28,29]. The works presented in [30,31,32,33,34,35,36,37] propose implementations of FS on reconfigurable hardware (Field Programmable Gate Array -FPGA), showing the possibilities associated with the acceleration of fuzzy inference processes having a high degree of parallelization. Other works propose specific implementations of Fuzzy Control Systems (FCS) using the Fuzzy Mamdani Inference Machine (M-FIM) and the Takagi-Sugeno Fuzzy Inference propose the Takagi-Sugeno hardware acceleration for other types of application fields. This work aims to develop a new hardware proposal for a Fuzzy-PI controller with TS-FIM. Unlike most of the works presented, this project offers a fully parallel scheme associated with a hybrid platform using fixed-point and floating-point representations. Two TS-FIM hardware modules have been proposed, the first (here called TS-FIM module one-shot) takes one sample time to execute the TS-FIM, and the second (here called as TS-FIM module pipeline) uses registers inside the TS-FIM. Two Fuzzy-PI controller hardware have been proposed, one for the TS-FIM one-shot module and another for the TS-FIM module pipeline. The proposed hardware have been implemented, tested and validated on a Xilinx Virtex 6 FPGA. The synthesis results, in terms of size, resources and throughput, are presented according to the number of bits and the type of numerical precision. Already, the physical area on the target FPGA reaches less than 7%. The implementation achieved a throughput between 10 and 18Msps (Mega samples per second), and between 490and 882 Mfl...

show abstract

Section: Validation Results -Fuzzy-pi Controller Hardwarementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Proposal of Takagi–Sugeno Fuzzy-PI Controller Hardware

Silva

Lopes

Valderrama

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Looking at multiple grooves existing in the single-wire winding motor that needs to be wound (Wang et al, 2010), domestic scholars proposed a threading winding and automation winding machine suitable for small-size motor stators. Aiming at the automation problem of single-wire winding, Krim et al (2019) produced an NOL nozzle winding machine, which adopts an automation transmission unit and can be freely arranged in the production line. Stephen J. Dodds of the University of East London proposed a robust tension control system for a sort of winding machine, aiming at the problem of the length and stability of velocity variation.…”

Section: Introductionmentioning

confidence: 99%

Design and motion analysis of a small motor stator multi-wire paralleled winding hybrid robot

et al. 2021

View full text Add to dashboard Cite

Abstract. The working space of small motor stators is narrow, and most of them are manual winding. It is difficult to guarantee the uniform arrangement of enameled wires by multi-wire winding. To solve these problems, a three-phase parallel equivalent multi-wire winding robot is proposed to achieve large output torque of the motor. Firstly, according to the equivalent model, the structure of the large arm, small arm and manipulator is designed to determine the motion model of the winding robot. Euler's kinematics theory is used to analyze the change of the working position of the arm, and the rotation matrix of the arm and the constraint equation of the motion vector of each branch chain are established. The motion model of the arm and the manipulator are established using inverse kinematics and analytical analysis. The motion pose of each joint of the winding robot is studied to ensure that the robot realizes a three-phase parallel multi-wire winding motion. ADAMS software was used for kinematic simulation analysis of the winding robot. The displacement of the branch chain on the xyz axis was represented by the torque of the virtual motor to verify the correctness of the inverse kinematics solution and the closure condition of the manipulator block. Finally, the ROS simulation platform is built to simulate the joint motion planning of the winding robot to verify the multi-line parallel principle and the feasibility of the multi-line parallel winding hybrid robot. The research results of this paper provide a theoretical reference for multi-wire parallel winding equipment control.

show abstract

“…GDMK yönteminde meydana gelen bu olumsuzlukların giderilmesine ve kontrol başarımının iyileştirilmesine yönelik, sabit anahtarlama frekanslı DMK (SAF-DMK) yöntemi [1], bulanık mantık temelli DMK yöntemi [3], algılaycısız kontrol temelli DMK yöntemi [4] ve model öngörülü kontrol temelli DMK yöntemi [5] literatürde önerilmiştir. Belirtilen çalışmalarda [1], [3]- [5] önerilen yöntemlerin GDMK yöntemine göre üstünlükleri detaylı olarak incelenmiştir.…”

Section: Introductionunclassified

Design of Adaptive Extended Kalman Filter-Based Speed-Sensorless Direct Torque Controlled Drive System with Constant Switching Frequency

İnan¹,

Zerdali²

2020

Pamukkale J Eng Sci

View full text Add to dashboard Cite

Bu çalışmada, hız-algılayıcısız asenkron motor (ASM) kontrolü için uyarlamalı genişletilmiş Kalman filtresi (UGKF) tabanlı sabit anahtarlama frekanslı doğrudan moment kontrollü (SAF-DMK'lı) sürücü sisteminin tasarımı gerçekleştirilmektedir. Stator akısı tabanlı ASM modelini kullanan UGKF ile GKF'lerin kestirim başarımını doğrudan etkileyen ve geleneksel GKF'lerde sabit olarak kabul edilen sistem gürültüsü kovaryans matrisi çalışma koşullarına göre çevrimiçi olarak güncellenmektedir. UGKF'nin geleneksel DMK'lı sürücü yerine, SAF-DMK'lı sürücüye dahil edilmesinin nedeni geleneksel DMK kontrolündeki moment dalgalanmalarının ve değişken anahtarlama frekansından kaynaklanan anahtarlama kayıplarının azaltılmasıdır. SAF-DMK'lı sürücünün ihtiyaç duyduğu stator akısının stator duran eksen takımı bileşenlerine ve rotor mekanik açısal hızına ek olarak, stator akımının stator duran eksen takımı bileşenleri ve yük momenti önerilen UGKF tabanlı gözlemleyici ile kestirilmektedir. Yük momenti kestirimi ile önerilen hız-algılayıcısız sürücü sisteminin bozucu yük momenti değişimlerine karşı dayanıklı olması sağlanmaktadır. Son olarak, önerilen UGKF-tabanlı hız-algılayıcısız SAF-DMK'lı sürücü sistemi benzetim çalışmaları altında doğrulanmaktadır. In this study, the design of the adaptive extended Kalman filter (AEKF) based direct torque controlled drive system with constant switching frequency (DTCD-CSF) is performed for speed-sensorless control of induction motor (IM). The system noise covariance matrix, which directly affects the estimation performance of EKFs and is assumed as constant in conventional EKFs, is updated online according to the operating conditions by the AEKF, which uses stator flux-based IM model. The reason why the proposed algorithm is included on a DTCD-CSF, instead of a conventional DTCD, is to reduce the torque ripples in the traditional direct torque control and the switching losses caused by the variable switching frequency. The load torque and the stator stationary axis components of stator currents in addition to the stator stationary axis components of stator fluxes and the rotor mechanical speed required for the DTCD-CSF are estimated by the proposed AEKF-based observer. By the load torque estimation, it is ensured that the proposed speed-sensorless drive system is robust to changes in load torque. Finally, the proposed AEKF-based speedsensorless DTCD-CSF is verified under simulation studies.

show abstract

Contribution of the FPGAs for Complex Control Algorithms: Sensorless DTFC with an EKF of an Induction Motor

Cited by 14 publications

References 28 publications

Proposal of Takagi–Sugeno Fuzzy-PI Controller Hardware

Proposal of Takagi–Sugeno Fuzzy-PI Controller Hardware

Design and motion analysis of a small motor stator multi-wire paralleled winding hybrid robot

Design of Adaptive Extended Kalman Filter-Based Speed-Sensorless Direct Torque Controlled Drive System with Constant Switching Frequency

Contact Info

Product

Resources

About