• 제목/요약/키워드: Ryu Controller

검색결과 255건 처리시간 0.031초

Performance Evaluation of SDN Controllers: RYU and POX for WBAN-based Healthcare Applications

  • Lama Alfaify;Nujud Alnajem;Haya Alanzi;Rawan Almutiri;Areej Alotaibi;Nourah Alhazri;Awatif Alqahtani
    • International Journal of Computer Science & Network Security
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    • 제23권7호
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    • pp.219-230
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    • 2023
  • Wireless Body Area Networks (WBANs) have made it easier for healthcare workers and patients to monitor patients' status continuously in real time. WBANs have complex and diverse network structures; thus, management and control can be challenging. Therefore, considering emerging Software-defined networks (SDN) with WBANs is a promising technology since SDN implements a new network management and design approach. The SDN concept is used in this study to create more adaptable and dynamic network architectures for WBANs. The study focuses on comparing the performance of two SDN controllers, POX and Ryu, using Mininet, an open-source simulation tool, to construct network topologies. The performance of the controllers is evaluated based on bandwidth, throughput, and round-trip time metrics for networks using an OpenFlow switch with sixteen nodes and a controller for each topology. The study finds that the choice of network controller can significantly impact network performance and suggests that monitoring network performance indicators is crucial for optimizing network performance. The project provides valuable insights into the performance of SDN-based WBANs using POX and Ryu controllers and highlights the importance of selecting the appropriate network controller for a given network architecture.

신경망을 이용한 비선형 동적 시스템의 최적 제어에 관한 연구 (An Neural Network Direct Controller For Nonlinear Systems)

  • 전정채;이형충;유인호;김희숙
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 D
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    • pp.2498-2500
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    • 2004
  • In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller. The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system.

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An Implementation of Mutual Tuning Controller for Position Control of Multiple Hydraulic Cylinders

  • Kim, Jin-Gyu;Park, Jang-Ho;Ryu, Gi-Seok;Park, Hyo-Sik;Lim, Jong-Ok;Kim, Jong-Hwa
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.67.4-67
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    • 2001
  • In order to push or pull a heavy weight structure, the positions of multiple hydraulic cylinders participated on must be tuned sumultaneously. To do this, it is necessary to control the position of each hydraulic cylinder through mutual tuning controller. In this paper, a tuning control of multiple hydraulic cylinders is introduced under the assumption that each position controller for each cylinder is used.

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Simple Speed Control Algorithm for DC Motors

  • Nguyen, Ba-Hai;Ngo, Hai-Bac;Ryu, Jee-Hwan
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2009년도 추계학술대회
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    • pp.510-513
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    • 2009
  • In this paper, a novel speed control algorithm of DC motors is presented. The key contribution here is a simple speed controller only with speed feedback and without an inner current control loop. This is possible by adjusting the reference speed based on a certain rule. Therefore, the proposed speed controller here becomes simpler while maintaining the control performance. Moreover, with the proposed controller, the system response can be tuned with less complexity. This proposed control method is investigated both mathematically and experimentally.

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신경망-관리 제어기를 이용한 PID 제어 시스템의 강인제어 (Robust control of PID control system using Neural network-Supervisory controller)

  • 지봉철;최석호;박왈서;유인호;조현섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 B
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    • pp.791-793
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    • 1999
  • In this paper, neural network-supervisory control method is proposed to minimize the effect of system uncertainty by load change and disturbance in the PID control system. In the proposed method, PID controller performs main control action by performing control within constraint error. And neural network-supervisory controller performs control action when error reaches the boundary of constraint error. Combining neural network-supervisory controller to guarantee the stability into PID control system, the resulting PID control system is expected to show better performance in the system with load change and disturbance. Simulation applying PID controller and neural network-supervisory controller showed excellence of proposed method.

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도립 진자의 궤적 제어를 위한 적응 제어기의 설계 (Design of Adaptive Fuzzy Controller to Inverted Pendulum Tracking)

  • 민현기;유창완;심재철;임화영
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 B
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    • pp.519-521
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    • 1999
  • An adaptive fuzzy controller is constructed from a set of fuzzy IF-THEN rules whose parameters are adjusted on-line according to some adaptation law for the purpose of controlling the plant to track a given trajectory. Adaptive fuzzy controller of this paper is designed based on the Lyapunov synthesis approach The adaptive fuzzy controller is designed through the following steps: first, construct an initial controller based on linguistic descriptions(in the form of fuzzy IF-THEN rules) about the unknown plant from human experts; then, develop an adaptation law to adjust the parameters of the fuzzy controller on-line, the adaptive fuzzy controllers are used to control the inverted pendulum to track a given trajectory.

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수중운동체 입수 초기의 불안정 거동에 대한 제어기 설계 및 성능평가 (Design and Performance Evaluation of Controller for Unstable Motion of Underwater Vehicle after Water Entry)

  • 박영일;류동기;김삼수;이만형
    • 한국정밀공학회지
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    • 제16권6호
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    • pp.166-175
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    • 1999
  • This paper describes a design and performance evaluation of robust controller which overrides unstable motion and pulls out quickly after water entry of underwater vehicle dropped from aircraft or surface ship. We use 6-DOF equation for model of motions and assume parameter uncertainty to reflect the difference of real motion from modelled motion equation. we represent a nonlinear system with uncertainty as Takagi and Sugeno's(T-S) fuzzy models and design controller stabilizing them. The fuzzy controller utilizes the concept of so-called parallel distributed compensation (PDC). Finally, we confirm stability and performance of the controller through computer simulation and hardware in the loop simulation (HILS).

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DEVELOPMENT OF A NETWORK-BASED TRACTION CONTROL SYSTEM, VALIDATION OF ITS TRACTION CONTROL ALGORITHM AND EVALUATION OF ITS PERFORMANCE USING NET-HILS

  • Ryu, J.;Yoon, M.;SunWoo, M.
    • International Journal of Automotive Technology
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    • 제7권6호
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    • pp.687-695
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    • 2006
  • This paper presents a network-based traction control system(TCS), where several electric control units(ECUs) are connected by a controller area network(CAN) communication system. The control system consists of four ECUs: the electric throttle controller, the transmission controller, the engine controller and the traction controller. In order to validate the traction control algorithm of the network-based TCS and evaluate its performance, a Hardware-In-the-Loop Simulation(HILS) environment was developed. Herein we propose a new concept of the HILS environment called the network-based HILS(Net-HILS) for the development and validation of network-based control systems which include smart sensors or actuators. In this study, we report that we have designed a network-based TCS, validated its algorithm and evaluated its performance using Net-HILS.

뉴럴 네트워크 방식의 벡터제어에 의한 유도전동기의 속도 제어 (The Speed Control of Vector controlled Induction Motor Based on Neural Networks)

  • 이동빈;유창완;홍대승;임화영
    • 한국지능시스템학회논문지
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    • 제9권5호
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    • pp.463-471
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    • 1999
  • This paper presents a vector controlled induction motor is implemented by neural networks system compared with PI controller for the speed control. The design employed the training strategy with Neural Network Controller(NNC) and Neural Network Emulator(NNE) for speed. In order to update the weights of the controller First of all Emulator updates its parameters by identifying the motor input and output next it supplies the error path to the output stage of the controller using backpropagation algorithm, As Controller produces an adequate output to the system due to neural networks learning capability Vector controlled induction motor characteristics actual motor speed with based on neural network system follows the reference speed better than that of linear PI speed controller.

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모터 파라미터 변화에 강인한 안정도 최대화 PI 제어기 설계 (Design of Robust Stability Maximizing PI Controller in Motor Parameter Variation)

  • 조내수;류지열;박철우;권우혁
    • 제어로봇시스템학회논문지
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    • 제15권6호
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    • pp.590-597
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    • 2009
  • This paper propose a PI controller that maximizes the degree of stability using a stability in a simplified motor model the applies decoupling control. The PI controller gains are directly from the motor parameters, thereby reducing the element of trial and error, and, the Kharitonov equation was used to evaluate the robustness of the gains to changes in the motor parameters. In addition, the system poles are located in the same position, the proposed method can provide a fast response. The effectiveness of the proposed controller is verified by simulation results.