• Title/Summary/Keyword: Lyapunov stability Analysis

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The Adaptive-Neuro Control of Robot Manipulator Using DSPs (디지털 시그널 프로세서를 이용한 로봇 매니퓰레이터의 적응-신경제어)

  • Cha, Bo-Ram;Kim, Seong-Il;Lee, Jin;Lee, Chi-U;Han, Seong-Hyeon
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2001.10a
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    • pp.122-127
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    • 2001
  • In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

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Study on the analysis Adaptive Observers to Control SRM Control Meathod (SRM 제어방법들에 대한 적응관측기들의 분석)

  • Shin, Jae-Hwa
    • Proceedings of the KIEE Conference
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    • 2007.11c
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    • pp.160-164
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    • 2007
  • MRAS observer, which is based on adaptive control theory, estimates speed and position by using optimal observer gains on the basis of Lyapunov stability theory. However, in case of MRAS theory, position estimation error is in existence because of non-linearity for inductance variation and limit cycles for position estimation. The adaptive sliding observer based on the variable structure control theory estimates the speed and position for zero of estimation error by using the sliding surface equal to the error between speed and position estimation. The binary observer estimates the rotor speed and rotor flux with alleviation of the high-frequency chattering, and retains the benefits achieved in the conventional sliding observer, such as robustness to parameter and disturbance variations. The speed and position sensorless control of SRM under the load and inductance variation is verified by the experimental results.

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Stable Wavelet Based Fuzzy Neural Network for the Identification of Nonlinear Systems (비선형 시스템의 동정을 위한 안정한 웨이블릿 기반 퍼지 뉴럴 네트워크)

  • Oh, Joon-Seop;Park, Jin-Bae;Choi, Yoon-Ho
    • Proceedings of the KIEE Conference
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    • 2005.07d
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    • pp.2681-2683
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    • 2005
  • In this paper, we present the structure of fuzzy neural network(FNN) based on wavelet function, and apply this network structure to the identification of nonlinear systems. For adjusting the shape of membership function and the connection weights, the parameter learning method based on the gradient descent scheme is adopted. And an approach that uses adaptive learning rates is driven via a Lyapunov stability analysis to guarantee the fast convergence. Finally, to verify the efficiency of our network structure. we compare the Identification performance of proposed wavelet based fuzzy neural network(WFNN) with those of the FNN, the wavelet fuzzy model(WFM) and the wavelet neural network(WNN) through the computer simulation.

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Robust Flight Control System Using Neural Networks: Dynamic Surface Design Approach (신경 회로망을 이용한 강인 비행 제어 시스템: 동적 표면 설계 접근)

  • Yoon, Sung-Jin;Choi, Yoon-Ho;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2006.07d
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    • pp.1848-1849
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    • 2006
  • The new robust controller design method is proposed for the flight control systems with model uncertainties. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides us with the ability to overcome the "explosion of complexity" problem of the backstepping controller. The SRWNNs are used to observe the arbitrary model uncertainties of flight systems and all their weights are trained on-line. From the Lyapunov stability analysis, their adaptation laws are induced and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a high performance aircraft (F-16) are utilized to validate the good tracking performance and robustness of the proposed control system.

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Design of a Real Time Adaptive Controller for SCARA Robot Using Digitl Signal Process (디지탈 신호처리기를 사용한 스카라 로보트의 실시간 적응제어기 설계)

  • 김용태;서운학;한성현;이만형;김성권
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.04a
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    • pp.472-477
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    • 1996
  • This paper presents a new approachtothe design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The prpposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

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Robust Flight Control System Using Neural Networks: Dynamic Surface Design Approach (신경 회로망을 이용한 강인 비행 제어 시스템: 동적 표면 설계 접근)

  • Yoo, Sung-Jin;Choi, Yoon-Ho;Park, Jin-Bae
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.55 no.12
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    • pp.518-525
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    • 2006
  • This paper presents the adaptive robust control method for the flight control systems with model uncertainties. The proposed control system can be composed simply by a combination of the adaptive dynamic surface control (DSC) technique and the self recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides us with the ability to overcome the 'explosion of complexity' problem of the backstepping controller. The SRWNNs are used to observe the arbitrary model uncertainties of flight systems, and all their weights are trained on-line. From the Lyapunov stability analysis, their adaptation laws are induced and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a high performance aircraft (F-16) are utilized to validate the good tracking performance and robustness of the proposed control system.

Derivation of an Energy Function Reflecting Damping Effects in Multi-Machine Power Systems (다모선 전력계통에서 댐핑효과를 고려한 에너지 함수의 유도)

  • Kwon, Yong-Jun;Ryu, Heon-Su;Choi, Byoung-Kon;Moon, Young-Hyun
    • Proceedings of the KIEE Conference
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    • 2001.05a
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    • pp.172-175
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    • 2001
  • This paper presents a new energy function reflecting the damping effect in multi-machine power systems. The Lyapunov direct method provides precise and rigorous theoretical backgrounds for stability analysis of nonlinear systems. Incorporating damping effects into accurate estimates of the domain of attraction, which is a minor but crucial point, has been attempted with long history to yield partial success for single machine systems. In this paper, the damping-reflected energy function presented in the previous work has been generalized for application to multi-machine systems. The generalized energy function is tested for the WSCC 9-bus system to show the semi-negativeness of its time derivative.

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Voltage Stability Analysis Based on Energy Function considering Tap of Transformer (변압기 탭영향을 고려한 에너지함수를 이용한 전압안정도 해석)

  • Kim Beom Shik;Kwon Yong Jun;Lee Ki Je;Moon Young Hyun
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.242-244
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    • 2004
  • 본 논문에서는 전력계통에서 에너지 함수를 이용하여 탭의 영향이 고려된 전압안정도 해석방법을 제시하였다. 전력계통의 전압안정도 해석은 부하단 변압기 탭의 특성과 밀접하게 연관되어 있으며 역학적 등가모델(EMM)을 이용하여 탭의 영향을 고려한 새로운 에너지함수를 유도하였다. 이 에너지 함수는 Lyapunov 함수의 조건을 만족시키며, 유도된 에너지함수로부터 안정평형점과 불안정평형점을 구하여 두 점에서의 에너지의 차이로서 전압붕괴를 예측할 수 있음을 1기 무한대 모선에 대하여 검증해 보았다.

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Speed and Flux Estimation for an Induction Motor

  • Lee, Gil-Su;Lee, Dong-Hyun;Yoon, Tae-Woong;Lee, Kyo-Beum;Ick Choy;Song, Joong-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.45.3-45
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    • 2002
  • $\textbullet$ In this paper, a new method of estimating the rotor speed and flux is proposed. $\textbullet$ The stator currents and voltages are measurable and all the system parameters are known. $\textbullet$ There are a number of common terms in the error dynamics. $\textbullet$ This is utilized to find a simpler error model involving some auxiliary variables. $\textbullet$ Using this error model, the state estimation problem is converted into a parameter estimation prob. $\textbullet$ Some stability properties are given on the basis of Lyapunov analysis. $\textbullet$ The effectiveness of the proposed scheme is demonstrated through simulations and experiments.

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A Global Regulation Method of Nonlinear Systems with Unbounded Parameters Under State Feedback Frame (비억제 파라미터를 갖는 비선형 시스템의 전역 안정화)

  • Koo, Min-Sung;Choi, Ho-Lim
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.3
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    • pp.171-176
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    • 2016
  • In this paper, we consider a regulation problem of nonlinear systems under two triangular conditions where there possibly exist unbounded parameters in the systems. We propose a state feedback controller with dynamic gains in order to deal with unbounded parameters based on the condition of the time-varying rate of the growing parameter. The analysis of our control scheme is carried out by Lyapunov stability method. Our control method is verified by simulation results.