• Title/Summary/Keyword: Model-Based Control

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A study on the adaptive predictive control of steam-reforming plant using bilinear model (쌍일차 모델을 이용한 스팀개질 플랜트의 적응예측제어에 관한 연구)

  • 오세천;여영구
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.156-159
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    • 1996
  • An adaptive predictive control for steam-reforming plant which consist of a steam-gas reformer and a waste heat steam-boiler was studied by using MIMO bilinear model. The simulation experiments of the process identification were performed by using linear and bilinear models. From the simulation results it was found that the bilinear model represented the dynamic behavior of a steam-reforming plant very well. ARMA model was used in the process identification and the adaptive predictive control. To verify the performance and effectiveness of the adaptive predictive controller proposed in this study the simulation results of steam-reforming plant control based on bilinear model were compared to those of linear model. The simulation results showed that the adaptive predictive controller based on bilinear model provides better performance than those of linear model.

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FEASIBILITY STUDY OF SOUND POWER BASED ACTIVE NOISE CONTROL STRATEGIES FOR GLOBAL NOISE REDUCTION

  • Kang, Seong-Woo;Kim, Yang-Hann
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06a
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    • pp.785-790
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    • 1994
  • The active noise control which regards the acoustic power as a target function to be minimized, is analyzed to test its feasibility of which simplifies the measurement system compared with the global acoustic energy based active noise control system. In fact, it is found that the acoustic power based active noise control strategy is equally likely as good as the global acoustic energy based active noise control method if the acoustic field of interest is diffusive or very low model density one. In the intermediate model density field, we also demonstrate that the power based control gives the similar results as the energy based control in terms of global sound energy reduction for the lightly damped enclosure which might be most important system in practical application. From all the theoretical and power based control strategy is dependent on the characteristics of the acoustic field to be controlled; i.e., the model density distribution, the degree of reverberation, and on the strength of modal interaction of the control source with the primary source; i.e., the location of control source.

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Enhanced Role-Based Access Control Administration Tool

  • Yenmunkong, Burin;Sathitwiriyawong, Chanboon
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1360-1364
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    • 2004
  • This paper propose an extended model for role-permission assignment based on locations called "Enhanced Role-Based Access Control (ERBAC03)". The proposed model is built upon the well-known RBAC model. Assigning permissions to role is considered too complex activity to accomplish directly. Instead we advocate breaking down this process into a number of steps. The concept of jobs and tasks is specifically introduced to facilitate role-permission assignment into a series of smaller steps. This model is suitable for any large organization that has many branches. Each branch consists of many users who work in difference roles. An administration tool has been developed to assist administrators with the administration of separation of duty requirements. It demonstrates how the specification of static requirements can be done based on "conflicting entities" paradigm. Static separation of duty requirements must be enforced in the administration environment. Finally, we illustrate how the ERBAC03 prototype is used to administer the separation of duty requirements.

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Integrated SolidWorks & Simscape Platform for the Model-Based Control Algorithms of Robot Manipulators

  • Ahn, Doo-Sung
    • Journal of Power System Engineering
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    • v.18 no.4
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    • pp.91-96
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    • 2014
  • The application of the recent model-based control schemes for robot manipulators require the solution of problems concerning various aspects, from the mechanical design to the necessity of determining a robot model suitable for control, and of experimentally testing the control performances. For one solution, integration of SolidWorks with Simscape for designing and controlling robot manipulators is presented in this paper. The integration provides a platform for rapid control prototyping of robot manipulators without the need for building real prototypes. Mechanical drawings of a robot are first created using Solidworks and imported into the Simscape, where a robot is represented by connected block diagrams based on the principle of physical modeling. Simulation examples for 7-DOF SAM ARM made by Berrett Technology Inc. are testified to show effectiveness of the presented platform.

Fault-Tolerant Control for 5L-HNPC Inverter-Fed Induction Motor Drives with Finite Control Set Model Predictive Control Based on Hierarchical Optimization

  • Li, Chunjie;Wang, Guifeng;Li, Fei;Li, Hongmei;Xia, Zhenglong;Liu, Zhan
    • Journal of Power Electronics
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    • v.19 no.4
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    • pp.989-999
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    • 2019
  • This paper proposes a fault-tolerant control strategy with finite control set model predictive control (FCS-MPC) based on hierarchical optimization for five-level H-bridge neutral-point-clamped (5L-HNPC) inverter-fed induction motor drives. Fault-tolerant operation is analyzed, and the fault-tolerant control algorithm is improved. Adopting FCS-MPC based on hierarchical optimization, where the voltage is used as the controlled objective, called model predictive voltage control (MPVC), the postfault controller is simplified as a two layer control. The first layer is the voltage jump limit, and the second layer is the voltage following control, which adopts the optimal control strategy to ensure the current following performance and uniqueness of the optimal solution. Finally, simulation and experimental results verify that 5L-HNPC inverter-fed induction motor drives have strong fault tolerant capability and that the FCS-MPVC based on hierarchical optimization is feasible.

Feedforward actuator controller development using the backward-difference method for real-time hybrid simulation

  • Phillips, Brian M.;Takada, Shuta;Spencer, B.F. Jr.;Fujino, Yozo
    • Smart Structures and Systems
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    • v.14 no.6
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    • pp.1081-1103
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    • 2014
  • Real-time hybrid simulation (RTHS) has emerged as an important tool for testing large and complex structures with a focus on rate-dependent specimen behavior. Due to the real-time constraints, accurate dynamic control of servo-hydraulic actuators is required. These actuators are necessary to realize the desired displacements of the specimen, however they introduce unwanted dynamics into the RTHS loop. Model-based actuator control strategies are based on linearized models of the servo-hydraulic system, where the controller is taken as the model inverse to effectively cancel out the servo-hydraulic dynamics (i.e., model-based feedforward control). An accurate model of a servo-hydraulic system generally contains more poles than zeros, leading to an improper inverse (i.e., more zeros than poles). Rather than introduce additional poles to create a proper inverse controller, the higher order derivatives necessary for implementing the improper inverse can be calculated from available information. The backward-difference method is proposed as an alternative to discretize an improper continuous time model for use as a feedforward controller in RTHS. This method is flexible in that derivatives of any order can be explicitly calculated such that controllers can be developed for models of any order. Using model-based feedforward control with the backward-difference method, accurate actuator control and stable RTHS are demonstrated using a nine-story steel building model implemented with an MR damper.

T-S Model Based Robust Indirect Adaptive Fuzzy Control

  • Hyun, Chang-Ho;Park, Chang-Woo;Park, Mignon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.05a
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    • pp.211-214
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    • 2002
  • In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

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T-S Fuzzy Model Based Robust Indirect Adaptive State Feedback Control of Flexible Joint Manipulators

  • Hyun, Chang-Ho;Park, Chang-Woo;Park, Mignon
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1471-1474
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    • 2002
  • In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

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Robust Predictive Speed Control for SPMSM Drives Based on Extended State Observers

  • Xu, Yanping;Hou, Yongle;Li, Zehui
    • Journal of Power Electronics
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    • v.19 no.2
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    • pp.497-508
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    • 2019
  • The predictive speed control (PSC) strategy can realize the simultaneous control of speed and current by using one cost function. As a model-based control method, the performance of the PSC is vulnerable to model mismatches such as load torque disturbances and parameter uncertainties. To solve this problem, this paper presents a robust predictive speed control (RPSC) strategy for surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed RPSC uses extended state observers (ESOs) to estimate the lumped disturbances caused by load torque changes and parameter mismatches. The observer-based prediction model is then compensated by using the estimated disturbances. The introduction of ESOs can achieve robustness against predictive model uncertainties. In addition, a modified cost function is designed to further suppress load torque disturbances. The performance of the proposed RPSC scheme has been corroborated by experimental results under the condition of load torque changes and parameter mismatches.

A Design on Robust Model Following Servo System Using $\delta$--Operator ($\delta$-연산자를 이용한 강인한 모델 추종형 서보 제어 시스템의 구성에 관한연구)

  • Kim, Chung-Tek;Hwang, Hyun-Joon
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.2
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    • pp.121-126
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    • 2000
  • In the fast sampling limit the delta operator model tends to the analog system model. This fundamental property of the delta operator model unifies continuous and discrete time control system. In this paper we study robust linear optimal model following servo system in the presence of disturbances and parameter perturbations. A technique to directly design the generalized differential operator based unified control system that covers both differential operator based continuous time and delta operator based discrete time case is presented. The quadratic criterion function for a linear system is used to design the robust unified servo control system The characteristics of the proposed servo system are analysed and simulated to verify the robustness.

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