• Title/Summary/Keyword: Micro Controller Unit

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Collaborative Streamlined On-Chip Software Architecture on Heterogenous Multi-Cores for Low-Power Reactive Control in Automotive Embedded Processors (차량용 임베디드 프로세서에서 저전력 반응적 제어를 위한 이기종 멀티코어 협력적 스트리밍 온-칩 소프트웨어 구조)

  • Jisu, Kwon;Daejin, Park
    • IEMEK Journal of Embedded Systems and Applications
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    • v.17 no.6
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    • pp.375-382
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    • 2022
  • This paper proposes a multi-core cooperative computing structure considering the heterogeneous features of automotive embedded on-chip software. The automotive embedded software has the heterogeneous execution flow properties for various hardware drives. Software developed with a homogeneous execution flow without considering these properties will incur inefficient overhead due to core latency and load. The proposed method was evaluated on an target board on which a automotive MCU (micro-controller unit) with built-in multi-cores was mounted. We demonstrate an overhead reduction when software including common embedded system tasks, such as ADC sampling, DSP operations, and communication interfaces, are implemented in a heterogeneous execution flow. When we used the proposed method, embedded software was able to take advantage of idle states that occur between heterogeneous tasks to make efficient use of the resources on the board. As a result of the experiments, the power consumption of the board decreased by 42.11% compared to the baseline. Furthermore, the time required to process the same amount of sampling data was reduced by 27.09%. Experimental results validate the efficiency of the proposed multi-core cooperative heterogeneous embedded software execution technique.

Hardware Implementation of a Neural Network Controller with an MCU and an FPGA for Nonlinear Systems

  • Kim Sung-Su;Jung Seul
    • International Journal of Control, Automation, and Systems
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    • v.4 no.5
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    • pp.567-574
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    • 2006
  • This paper presents the hardware implementation of a neural network controller for a nonlinear system with a micro-controller unit (MCU) and a field programmable gate array (FPGA) chip. As an on-line learning algorithm of a neural network, the reference compensation technique has been implemented on an MCU, while PID controllers with other functions such as counters and PWM generators are implemented on an FPGA chip. Interface between an MCU and a field programmable gate array (FPGA) chip has been developed to complete hardware implementation of a neural controller. The developed neural control hardware has been tested for balancing the inverted pendulum while controlling a desired trajectory of a cart as a nonlinear system.

Design Scheme of A Micro Real-Time Control System with CAN and RTOS (CAN과 RTOS를 내장한 소형 실시간 시스템 설계 기법)

  • Lim, Young-Gyu;Kim, Dong-Seoung
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.5
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    • pp.207-215
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    • 2014
  • In this paper, we propose a Micro Real-Time Control System (MRTCS) for decreasing the delay during interrupts processing and data transfer on sensor nodes. The MRTCS consists of a control, sensor nodes based on Controller Area Network (CAN) device. The control node was designed with Real Time Operating System (RTOS) on top of the small Micro Control Unit (sMCU). Sensor nodes have the CAN device without sMCU, which have multiple Digital Inputs, Outputs (DI/DO) and the CAN controller. We have evaluated with OCTAVE v3.6.4 from open source for system performance. Simulation results show that the system performance was increased through the delay reducing for interrupt processing and internal data transfer. We verify that a proposed MRTCS approach will be adapted to various real-time control system.

A Development and Performance Test of Voltage Measurement Accuracy Assessment System for Distribution Equipment (배전기기 전압계측 정밀도 평가시스템 개발 및 성능시험)

  • Cho, Jin-Tae;Kim, Ju-Yong;Lee, Hak-Ju;Kim, Jae-Han
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.27 no.9
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    • pp.83-89
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    • 2013
  • Power distribution system has been changed from radial system to closed loop or mesh system due to connection of distributed generation growth. Data from distribution equipments which are installed at distribution line is required to be accurate for the performance of DMS(Distribution Management System). This paper analyzes the voltage measurement data from distribution equipment. However, the results of the analysis are confirmed to have some errors in voltage measurement data from distribution equipment. These errors come from aging of voltage sensor in distribution equipment and inaccurate data transfer to FRTU(feeder remote terminal unit) through the controller. The main problem is that the voltage measurement data of distribution equipment can not be assessed after it's first installation at the distribution line. The voltage measurement accuracy assessment system is to assess the voltage measurement data from distribution equipment on hot-line. This study had a field test to verify the performance of system.

Method of In-Vehicle Gateway to Reduce the Reprogramming Time (리프로그래밍 시간 단축을 위한 차량 게이트웨이 개선 방안)

  • Kim, Jin-Ho;Ha, Kyung-Jae
    • Journal of Convergence for Information Technology
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    • v.9 no.7
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    • pp.25-32
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    • 2019
  • This paper proposes the method of an in-vehicle gateway to reduce the reprogramming time for the ECU (Electronic Control Unit). In order to reduce the reprogramming time, the gateway must prohibit transmitting messages, that are not related to reprogramming, to the destination CAN network, and no ECU should diagnose the DTC(Diagnostic Trouble Code) that indicates CAN communication error caused by prohibiting CAN messages by the gateway. Moreover, STmin, which are the minimum time between two consecutive CAN messages, should be minimized. In order to do this, this paper proposes the method that uses the link control command specified in UDS(Unified Diagnostic Services) and hardware based gateway functionality that are supported by the latest MCU(Micro Controller Unit). The proposed method is developed using TC275 based embedded system, and its results are presented.

Hardware development for Electrical Vehicle Control Unit (전기차량용 차량제어기 하드웨어 개발)

  • Kim, Ucksoo;Kang, Sundoo
    • 한국신재생에너지학회:학술대회논문집
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    • 2010.11a
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    • pp.96.1-96.1
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    • 2010
  • 전기차량용 차량제어기는 차량 전체의 구동 전략과 브레이크 시의 회생제동, 고전압 배터리의 SOC management 등을 제어하는 역할을 한다. 엑셀 페달 및 브레이크 페달의 신호를 입력 받아 운전자의 주행의지를 받아 들이고, 차량의 각종 제어기들과 CAN 통신을 통하여 필요한 정보들을 송수신한다. 이러한 입/출력 동작을 통하여 차량 전체의 구동전략을 세우고 각종 제어기들에게 주행에 필요한 정보를 전달한다. MCU(Main Control Unit)로는 32bit micro-controller 이 적용되었으며, 열충격과 고온동작 내구 등의 환경시험 및 전자기파 적합성 시험등을 통해 외부환경 변화에도 요구 성능을 만족함을 확인하였다. 이러한 성공적인 개발을 통해 2011년 초 시범양산되는 현대기아자동차의 BLUE ON 에 양산적용될 예정이라는 데에 의의가 있다.

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PC Based Distributed Control System of AGV with Multi-Thread Method (다중 쓰레드 기법을 미용한 AGV의 PC기반 분산제어 시스템)

  • Jun, Sung-Jae;Cho, Yon-Sang;Park, Heung-Sik
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.9 s.174
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    • pp.107-114
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    • 2005
  • With the recent progress in flexible manufacturing systems (FMS) in industry, increasing attention has been given to Automatic Guided Vehicle (AGV) systems. An AGV is a self-powered unit for transporting materials between stations without needing to be controlled by an operator. Such a system has several sensors to recognize the external state, and it is designed to travel between stations automatically without external assistance. To manage each device automatically in real time it requires a distributed controller with a main computer as the host, as well as a number of micro-controllers. In this study, an AGV system with dual motor drive was constructed. A Pentium 4 personal computer was set up as the main host for the distributed control, and this communicated with other micro-controllers in the management of the motor. The speed of each motor was also controlled by a micro-controller.

Design of Lightweight Artificial Intelligence System for Multimodal Signal Processing (멀티모달 신호처리를 위한 경량 인공지능 시스템 설계)

  • Kim, Byung-Soo;Lee, Jea-Hack;Hwang, Tae-Ho;Kim, Dong-Sun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.5
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    • pp.1037-1042
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    • 2018
  • The neuromorphic technology has been researched for decades, which learns and processes the information by imitating the human brain. The hardware implementations of neuromorphic systems are configured with highly parallel processing structures and a number of simple computational units. It can achieve high processing speed, low power consumption, and low hardware complexity. Recently, the interests of the neuromorphic technology for low power and small embedded systems have been increasing rapidly. To implement low-complexity hardware, it is necessary to reduce input data dimension without accuracy loss. This paper proposed a low-complexity artificial intelligent engine which consists of parallel neuron engines and a feature extractor. A artificial intelligent engine has a number of neuron engines and its controller to process multimodal sensor data. We verified the performance of the proposed neuron engine including the designed artificial intelligent engines, the feature extractor, and a Micro Controller Unit(MCU).

Development of Steering Control System based on CAN for Autonomous Tractor System (자율 주행 트랙터 시스템의 성능 향상을 위한 CAN 기반의 조향제어시스템 개발)

  • Seo, Dong-Hyun;Seo, Il-Hwan;Chung, Sun-Ok;Kim, Ki-Dae
    • Korean Journal of Agricultural Science
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    • v.37 no.1
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    • pp.123-130
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    • 2010
  • A steering control system based on CAN(Controller Area Network) for autonomous tractor was developed to reduce duty of a central processing computer and to improve performance of steering control in terms of reduced control interval and error. The steering control system consisted of a SCU (Steering Control Unit), an EHPS system, and a potentiometer. The SCU consisted of an MCU (Micro Controller unit), an A/D converter, and a DC-DC converter, and a PID controller was used to control steering angle. The steering control system was communicated with the computer by CAN-bus. Each actuator and implement was connected to a multi-function board interfacing with the computer through a USB cable. Without CAN, control interval of the autonomous tractor was 1.5 seconds. When the CAN-based steering control system was combined with the autonomous tractor, however, control interval of the integrated system was reduced to those less than 0.05 seconds. When the autonomous tractor was operated with 1.5-s and 0.05-s control cycles at a 0.63-m/s travelling speed, the trajectories were close to straight lines for both of the control cycles. For a 1.34-m/s traveling speed, tractor trajectory was close to sine wave with a 1.5-s control cycle, but was straight line with a 0.05-s control cycle.

Dynamic Modeling based Flight Control of Hexa-Rotor Helicopter System (헥사로터형 헬리콥터의 동역학 모델기반 비행제어)

  • Han, Jae-Gyun;Jin, Taeseok
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.4
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    • pp.398-404
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    • 2015
  • In this paper, we describe the design and performance of a prototype multi-rotor unmaned aerial vehicle( UAV) platform featuring an inertial measurement unit(IMU) based autonomous-flying for use in bluetooth communication environments. Although there has been a fair amount of study of free-flying UAV with multi-rotors, the more recent trend has been to outfit hexarotor helicopter with gimbal to support various services. This paper introduces the hardware and software systems toward very compact and autonomous hexarotors, where they can perform search, rescue, and surveillance missions without external assistance systems like ground station computers, high-performance remote control devices or vision system. The proposed system comprises the construction of the test hexarotor platform, the implementation of an IMU, mathematical modeling and simulation in the helicopter. Furthermore, the hexarotor helicopter with implemented IMU is connected with a micro controller unit(MCU)(ARM-cortex) board. The micro-controller is able to command the rotational speed of the rotors and to get the measurements of the IMU as input signals. The control simulation and experiment on the real system are implemented in the test platform, evaluated and compared against each other.