• Title/Summary/Keyword: Hybrid control model

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TSK Fuzzy Model Based Hybrid Adaptive Control of Nonlinear Systems (비선형 시스템의 TSK 퍼지모델 기반 하이브리드 적응제어)

  • Kim, You-Keun;Kim, Jae-Hun;Hyun, Chang-Ho;Kim, Eun-Tai;Park, Mi-Gnon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.211-216
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    • 2004
  • In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

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Novel Control Method for a Hybrid Active Power Filter with Injection Circuit Using a Hybrid Fuzzy Controller

  • Chau, MinhThuyen;Luo, An;Shuai, Zhikang;Ma, Fujun;Xie, Ning;Chau, VanBao
    • Journal of Power Electronics
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    • v.12 no.5
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    • pp.800-812
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    • 2012
  • This paper analyses the mathematical model and control strategies of a Hybrid Active Power Filter with Injection Circuit (IHAPF). The control strategy based on the load harmonic current detection is selected. A novel control method for a IHAPF, which is based on the analyzed control mathematical model, is proposed. It consists of two closed-control loops. The upper closed-control loop consists of a single fuzzy logic controller and the IHAPF model, while the lower closed-control loop is composed of an Adaptive Network based Fuzzy Inference System (ANFIS) controller, a Neural Generalized Predictive (NGP) regulator and the IHAPF model. The purpose of the lower closed-control loop is to improve the performance of the upper closed-control loop. When compared to other control methods, the simulation and experimental results show that the proposed control method has the advantages of a shorter response time, good online control and very effective harmonics reduction.

Hybrid Control Model of MR Damper for Seismic Response Control of Adjacent Buildings (인접건축물의 지진응답 제어를 위한 MR 감쇠기의 복합제어 모델)

  • Kim, Gee-Cheol;Kang, Joo-Won;Chae, Seoung-Hun
    • Journal of Korean Association for Spatial Structures
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    • v.11 no.2
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    • pp.101-110
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    • 2011
  • Many researchers have attempted to apply semi-active control systems in the civil engineering structures. Recently, magneto-rheological(MR) fluid dampers have been developed. This MR damper is one of semi-active dampers as a new class of smart dampers. This paper discusses the application of MR damper for seismic response control of adjacent buildings subjected to earthquake. Here, a controllable damping force of MR damper that is installed between adjacent buildings is applied to seismic response control. A hybrid model combines skyhook and groundhook control algorithm so that the benefits of each can be combined together. In this paper, hybrid control model are applied to the multi degree of freedom system representative of buildings in order to reduce seismic response of adjacent buildings. And the performance of hybrid control model is compared with that of others. It was demonstrated that hybrid control model or adjacent buildings with MR damper was effective for seismic response control of two adjacent buildings reciprocally.

Control Strategy for Buck DC/DC Converter Based on Two-dimensional Hybrid Cloud Model

  • Wang, Qing-Yu;Gong, Ren-Xi;Qin, Li-Wen;Feng, Zhao-He
    • Journal of Electrical Engineering and Technology
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    • v.11 no.6
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    • pp.1684-1692
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    • 2016
  • In order to adapt the fast dynamic performances of Buck DC/DC converter, and reduce the influence on converter performance owing to uncertain factors such as the disturbances of parameters and load, a control strategy based on two-dimensional hybrid cloud model is proposed. Firstly, two cloud models corresponding to the specific control inputs are determined by maximum determination approach, respectively, and then a control rule decided by the two cloud models is selected by a rule selector, finally, according to the reasoning structure of the rule, the control increment is calculated out by a two-dimensional hybrid cloud decision module. Both the simulation and experiment results show that the strategy can dramatically improve the dynamic performances of the converter, and enhance the adaptive ability to resist the random disturbances, and its control effect is superior to that of the current-mode control.

Hybrid System Modeling and Control for Path Planning and Autonomous Navigation of Wheeled Mobile Robots (차륜형 이동로봇의 경로 계획과 자율 주행을 위한 하이브리드 시스템 모델과 제어)

  • Im, Mi-Seop;Im, Jun-Hong
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.1
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    • pp.33-40
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    • 2000
  • In this paper, an integrated method for the path planning and motion control of wheeled mobile robots using a hybrid system model and control is presented. The hybrid model including the continuous dynamics and discrete dynamics with the continuous and discrete state vector is derived for a two wheel driven mobile robot. The architecture of the hybrid control system for real time path planning and following is designed which has the 3-layered hierarchical structure : the discrete event system using the digital automata as the higher process, the continuous state system for the wheel velocity controls as the lower process, and the interface system as the interaction process between the continuous system as the low level and the discrete event system as the high level. The reference motion commands for autonomous navigation are generated by the abstracted motion in the discrete event system. The motion control tasks including the feasible path planning and autonomous motion control with various initial conditions are investigated as the applications by the simulation studies.

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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.

Hybrid position/force control of uncertain robotic systems using neural networks (신경회로망을 이용한 불확실한 로봇 시스템의 하이브리드 위치/힘 제어)

  • Kim, Seong-U;Lee, Ju-Jang
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.3
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    • pp.252-258
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    • 1997
  • This paper presents neural networks for hybrid position/force control which is a type of position and force control for robot manipulators. The performance of conventional hybrid position/force control is excellent in the case of the exactly-known dynamic model of the robot, but degrades seriously as the uncertainty of the model increases. Hence, the neural network control scheme is presented here to overcome such shortcoming. The introduced neural term is designed to learn the uncertainty of the robot, and to control the robot through uncertainty compensation. Further more, the learning rule of the neural network is derived and is shown to be effective in the sense that it requires neither desired output of the network nor error back propagation through the plant. The proposed scheme is verified through the simulation of hybrid position/force control of a 6-dof robot manipulator.

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Model updating with constrained unscented Kalman filter for hybrid testing

  • Wu, Bin;Wang, Tao
    • Smart Structures and Systems
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    • v.14 no.6
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    • pp.1105-1129
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    • 2014
  • The unscented Kalman filter (UKF) has been developed for nonlinear model parametric identification, and it assumes that the model parameters are symmetrically distributed about their mean values without any constrains. However, the parameters in many applications are confined within certain ranges to make sense physically. In this paper, a constrained unscented Kalman filter (CUKF) algorithm is proposed to improve accuracy of numerical substructure modeling in hybrid testing. During hybrid testing, the numerical models of numerical substructures which are assumed identical to the physical substructures are updated online with the CUKF approach based on the measurement data from physical substructures. The CUKF method adopts sigma points (i.e., sample points) projecting strategy, with which the positions and weights of sigma points violating constraints are modified. The effectiveness of the proposed hybrid testing method is verified by pure numerical simulation and real-time as well as slower hybrid tests with nonlinear specimens. The results show that the new method has better accuracy compared to conventional hybrid testing with fixed numerical model and hybrid testing based on model updating with UKF.

Active Vibration Control of a Beam Structure Using Hybrid Mount (하이브리드마운트를 이용한 빔 구조물의 능동진동제어)

  • 김승환;홍성룡;최승복
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.13 no.7
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    • pp.524-531
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    • 2003
  • This paper presents an active vibration control of a flexible beam structure using a hybrid mount which consists of elastic rubber and Piezoelectric material. After identifying stiffness and damping properties of the rubber and piezoelectric elements, a mechanical model of the hybrid mount is established. The mount model is then Incorporated into the beam structure, and the governing equation of motion is obtained in a state space. A sliding mode controller is designed in order to actively attenuate the vibration of the beam structure subjected to high frequency and small magnitude excitations. The controller is experimentally realized and control responses such as acceleration of the beam structure and force transmission through the hybrid mount are evaluated. In addition. a comparative work is done between the passive and hybrid mount systems.