• Title/Summary/Keyword: Adaptive System

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Adaptive Phase-Locked Loop for Process Control System

  • Park, Jin-Bae;Shohei, Niwa
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.108.2-108
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    • 2001
  • This paper presents the application of adaptive phase-locked loop (adaptive PLL) technique to control the process variable of the process control system. The adaptive algorithm is related to the error. When the error of the system is changed, the adaptive gain will be directly changed according to the error. If the value of the adaptive gain is large, the value of the error will be large. In this experiment, the reference input is 50% step input. The experimental result in controlling the first order lag process by the adaptive PLL shows that the response of the controlled system has no overshoot, short rise time, and zero steady-state error. The experimental result also shows that when the output disturbance enters to the process control system, the adaptive PLL can maintain the stability of the system and the effect of the output disturbance can also be fast rejected. The adaptive PLL has better performance ...

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Adaptive Fuzzy Control of Helicopter (헬리콥터의 적응 퍼지제어)

  • 김종화;장용줄;이원창;강근택
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.05a
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    • pp.144-147
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    • 2001
  • This paper presents adaptive fuzzy controller which is uncertainty or unknown variation in different parameters with nonlinear system of helicopter. The proposed adaptive fuzzy controller applied TSK(Takagi-Sugeno-Kang) fuzzy system which is not only low number of fuzzy rule, and a linear input-output equation with a constant term, but also can represent a large class of nonlinear system with good accuracy. The adaptive law was designed by using Lyapunov stability theory. The adaptive fuzzy controller is a model reference adaptive controller which can adjust the parameter $\theta$ so that the plant output tracks the reference model output. First of all, system of helicopter was considered as stopping state, and design of controller was simulated from dynamics equation with stopping state. Results show that it is controlled more successfully with a model reference adaptive controller than with a non-adaptive fuzzy controller when there is a modelling error between system and model or a continuous added noise in such unstable system.

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A Design of Discrete-Time Model Reference Adaptive Control System by Direct Method (직접법에 의한 이산시간 기준모델 적응제어 시스템 설계에 관한 연구)

  • 김성덕
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.10 no.5
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    • pp.258-265
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    • 1985
  • A design method for a single-input single-output discrete time model reference adaptive system is described in this paper. By using the state-variable filters into inputs and outputs in reference model and unknown system, a simple adaptive structure which use all accessible signals can be constructed. Some papers for the adaptive shstem is which thw relative degree of unknown system have one or two have been reported, but the resulting adaptive system are intricate in structures and the design theories for the model reference adaptive system are not generalized. In this paper, for having two or more relative degrees, it has been verified that an adaptive scheme can be obtained by introducing a simple linear filter.

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Implementation of the Mass Flow Controller using Adaptive PID (적응 PID를 이용한 질량 유량 제어기 구현)

  • Baek, Kwang-Ryul;Cho, Bong-Su
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.1
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    • pp.19-25
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    • 2007
  • The MFC(Mass Flow Controller) is an equipment that measures and controls mass flow rates of fluid. Most of the HFC system is still using the PID algorithm. The PID algorithm shows superior performance on the MFC system. But the PID algorithm in the MFC system has a few problems as followed. The characteristic of the MFC system is changed according to the operating environment. And, when the piezo valve that uses the control valve is assembled in the MFC system, a coupling error is generated. Therefore, it is very difficult to find out the exact parameters of MFC system. In this paper, we propose adaptive PID algorithm in order to compensate these problems of a traditional PID algorithm. The adaptive PID algorithm estimates the parameters of MFC system using LMS(Least Mean Square) algorithm and calculates the coefficients of PID controller. Besides, adaptive PID algorithm shows better transient response because adaptive PID algorithm includes a feedforward. And we implement MFC system using proposed adaptive PID algorithm with self-tuning and Ziegler and Nickels's method. Finally, comparative analysis of the proposed adaptive PID and the traditional PID is shown.

Design of adaptive controllers for the boiler system (보일러를 위한 적응 제어기 설계)

  • 박태건;류지수;이기상
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.337-340
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    • 1997
  • In this paper we propose direct and indirect adaptive controllers for a nonlinear multivariable steam generating unit(200MW). In the direct adaptive scheme the estimation of the controller parameter are achieved from tracking error, while in the indirect approach the unknown parameter of the boiler system is estimated by the Hopfield network-based identifier. The performance of two proposed adaptive controllers is shown through simulations.

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Performance of an Adaptive-MCM System with Combining AMC and MIMO Schemes (AMC와 MIMO 기법이 결합된 Adaptive-MCM 시스템의 성능 분석)

  • Seo, Chang-Woo;Joe, In-Sik;Yoon, Gil-Sang;Lee, Jung-Hwan;Hwang, In-Tae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.2
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    • pp.501-506
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    • 2010
  • The proposal set out in this paper, is the Adaptive-MCM(Modulation, Coding and MIMO) system, which results from the combination of adaptive modulation and coding (AMC) and multiple input multiple output (MIMO) schemes. The performance of this system is analyzed through computer simulation. By using the MIMO scheme adaptively as well, the proposed Adaptive-MCM system, presents a better improvement of data rate and error performance compared to the AMC system. The throughput performance of the Adaptive-MCM system is analyzed and compared with the throughput performance of Non-Adaptive-MCM Systems. As a result of the simulation, we can infer that, at a fixed MCM level, there is an improvement of the trade-off between secure Signal to Noise Ratio (SNR) and a high data rate. Consequently, this trade-off improvement results in a better average data rate.

ADAPTIVE SLICING ODE CONTROL USING FUZZY LOGIC SYSTEM

  • Yoo, Byungkook;Jeoung, Sacheul;Ham, Woonchul
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.26-30
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    • 1995
  • In this study, the fuzzy approximator and sliding mode control (SMC) scheme are considered. An adaptive sliding mode control is proposed based on the SMC theory. This proposed control scheme is that a adaptive law is utilized to approximate the unknown function f by fuzzy logic system in designing the sliding mode controller for the nonlinear system. In order to reduce the approximation errors, the differences of nonlinear function and fuzzy approximator, an adaptive law is also intoduced and the stability of proposed control scheme are proven with simple adaptive law and roburst adaptive law. This proposed control scheme is applied to a single link robot arm.

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A Design of Stable Adaptive Composite Control Systems (안정한 적응 이중 제어시스템의 설계)

  • Zhang, Jeong-Il;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • 1994.11a
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    • pp.370-372
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    • 1994
  • In this paper, a stable adaptive composite control system consisting of a PID and a fuzzy controllers is designed to control nonlinear systems. In the fuzzy controller, parameters of membership functions characterizing the linguistic terms change according to some adaptive law. Also, parameters of PID controller change according to some adaptive law. These adaptive laws are based on the Lyapunov synthesis approach. Then, it is proved that the closed-loop system using such an adaptive composite control system is globally stable in the sense that all signals involved are bounded and the tracking error converges to zero. We apply this adaptive composite control system to control a nonlinear system.

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A Study on the Adaptive Observer/Adaptive Identifier in the Presence of Noise (잡음하에서의 적응관측자 및 적응식별기에 관한 연구)

  • 최종호;남석우
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.1
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    • pp.83-91
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    • 1990
  • An adaptive observer which is applicable to discrete linear time invariant systems of ARMA type in the presence of noise is proposed. It first estimates the system parameters of the MA type by applying only the system input to the observer. Then it estimates the output which corresponds to the output of the system without any noise. This is a special case of Suzuki's adaptive observer. This estimated output is applied to Suzuki's adaptive observer to estimate the system parameters of ARMA type and the states. The proposed method can make the estimate errors of the system parameters sufficiently small even in the presence of noise in the system. It can also make the estimate errors of the states of the system sufficiently small when there is no process noise. These properties of the proposed adaptive observer is certified by computer simulation.

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A Study on the Structure and Adaptive Methods for Robust Adaptive Control and its Simulation (견실한 적응제어를 위한 구조 및 적응 방법에 관한 인구와 시뮬레이션)

  • 윤태웅;최종호
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.36 no.7
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    • pp.484-491
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    • 1987
  • A sufficent condition for the robust control of the adaptive control system is presented under the convergence of the parameters of the adaptive system. The plant in the adaptive control system is a stable system which includes the unmodelled dynamics and can be approximated by a minimum phase system. It is shown that modified structure which Kosut and Friedlander suggested satisfies the sufficient condition more easily than the original structure without modification. It is also shown by computer simulation that the modified structure and/ or the adaptation method using the normalized input and output data or filtered input and output data can improve the robustness of the adaptive control system.

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