• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.768-773
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• 2012

Packet loss compensation techniques are increasingly important to stable remote control over wireless communication in WNCS (Wireless Networked Control Systems). Its time varying channels, limited bandwidth, interference, and poor signal not only leads to packet loss or latency, but also can negatively affect performance and system stability. This paper presents a compensation technique exploiting an EWMA (Exponentially Weighed Moving Average)-based value estimator to clarify the influence of packet loss on the overall WNCS behavior. As an example of actuator to be remotely controlled, a rotary-type inverted pendulum has been considered, and modeled. Performance evaluation results through Matlab/Simulink and Truetime co-simulation confirm the superiority of the proposed value estimation method over previous approaches.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.9
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• pp.76-87
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• 1992

A novel self-organizing fuzzy plus PD control algorithm is proposed, where the proposed controller consists of a typical fuzzy reasoning part and self organizing part in which both on-line and off-line algorithms are employed to modify the Look-Up Table(LUT) for the fuzzy control rules and to decide how much fuzzy rules are to be modifid after evaluating the control performance, respectively. And the fuzzy controller is replaced by a PD controller in a prespecified region nearby the set point for good settling actions, where gain parameters are determined by fuzzy rules based on the magnitude of error velocity at the instant when the output penetrates into the prespecified region. To show the effectiveness of the proposed controller, extensive computer simulation results as well as experimental results are illustrated for an inverted pendulum system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.174-179
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• 1995

본 논문데서는 부하외란이나 시스템 내부 파라미터의 변동시에 적응력이 저하되는 종래의 PI제어기와, 정상상태 잔류편차가 존재하는 퍼지 제어기의 단점을 극복하기 위한 적 응 퍼지 제어 기법을 제안하였고, 이를 도립 진자 시스템에 적용하였다. 운송차의 위치 및 진자 각도의 오차, 오차의 변화량에 따라 퍼지 추론을 행하여 PI 제어기의 가중치를 결정하 는 구조로, P제어기는 운송차 및 진자의 오차가 과도 상태에서의 영역에서 사용되어 속응성 과 고정도의 특성을 얻는다. 1제어기는 정상상태에서의 정도 향상에 이용되었다. 특히, 제안 하는 적응 퍼지 제어기는 운송차의 위치 오차에 대한 PI 동작과, 진자의 각도 오차에 대한 PI 동작을 각각 퍼지 추론에 의해 부드럽게 전환함으로서 고유 불안정의 시스템인 도립 진 자 시스템의 안정화 제어에 적용하였다.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.17-26
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• 2002

In this paper, a new design methodology of the fuzzy controller is presented. The performance of the fuzzy controller is sensitive to the variety of scaling factors. The design procedure is based on evolutionary computing (more specifically, a genetic algorithm) and estimation algorithm to adjust and estimate scaling factors respectively. The tuning of the soiling factors of the fuzzy controller is essential to the entire optimization process. And then we estimate scaling factors of the fuzzy controller by means of two types of estimation algorithms such as HCM (Hard C-Means) and Neuro-Fuzzy model[7]. The validity and effectiveness of the proposed estimation algorithm for the fuzzy controller are demonstrated by the inverted pendulum system.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.306-307
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• 2007

본 논문은 계층적 공정 경쟁 유전자 알고리즘(Hierarchical Fair Competition-based Genetic Algorithms : HFCGA)을 이용하여 회전형 역 진자 시스템의 최적 Fuzzy 제어기 설계를 제안한다. 탐색 공간이 크거나 복잡한 최적해 탐색문제에 대해 조기 수렴 문제를 내제하고 있는 기존의 유전자 알고리즘의 해결방안으로 병렬 유전자 알고리즘이 개발되었으며, HFCGA는 병렬 유전자 알고리즘의 한 구조이다. 본 논문에서는 회전형 역 진자 시스템에 대해 LQR 제어기와 유사한 형태의 Fuzzy 제어기를 구성하고, HFCGA를 이용하여 최적의 제어기 파라미터들을 구한다. 그리고 시뮬레이션 및 실제 공정에 적용하여 LQR 제어기와 설계된 제어기의 성능을 평가한다.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1811-1812
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• 2007

본 논문에서는 Fuzzy-PID Control을 이용한 2축 도립진자를 제어한다. X-Y 축을 움직이는 카트에는 도립진자가 세워져 있으며 카트가 2축의 평면상에 원하는 위치로 빠르고 정확하게 이동할 수 있게 하는 동시에 도립진자의 균형을 깨뜨리지 않고 움직이는 것을 제어의 목표로 한다. Fuzzy-PID Control은 도립진자의 균형에 대한 제어뿐만 아니라 로봇의 위치 제어까지 적용된다. 본 연구 논문에서는 이러한 Fuzzy-PID 적용 시스템에 대한 시뮬레이션을 실행함으로 그 우수성을 입증 하고자 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.527-532
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• 2005

In this paper, we proposed an adaptive fuzzy sliding control for unknown nonlinear systems using estimation of bounds for approximation errors. Unknown nonlinearity of a system is approximated by the fuzzy logic system with a set of IF-THEN rules whose consequence parameters are adjusted on-line according to adaptive algorithms for the purpose of controlling the output of the nonlinear system to track a desired output. Also, using assumption that the approximation errors satisfy certain bounding conditions, we proposed the estimation algorithms of approximation errors by Lyapunov synthesis methods. The overall control system guarantees that the tracking error asymptotically converges to zero and that all signals involved in controller are uniformly bounded. The good performance of the proposed adaptive fuzzy sliding mode controller is verified through computer simulations on an inverted pendulum system.

• Journal of IKEEE
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• v.9 no.1 s.16
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• pp.72-78
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• 2005

This paper describes the design of a robust output-feedback controller for a single-input single-output nonlinear dynamical system with a full relative degree. While all the previous research works on the output-feedback control are based on dynamic observers, a new state estimator which uses the past values of the measurable system output is proposed. We name it backward-difference state estimator since the derivatives of the output are estimated simply by backward difference of the present and past values of the output. The disturbance generated due to the error between the estimated and real state variables is compensated using an additional robustifying control law whose gain is tuned adaptively. Overall control system guarantees that the tracking error is asymptotically convergent and that all signals involved are uniformly bounded. Theoretical results are illustrated through a simulation example of inverted pendulum.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.532-538
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• 1998

In this paper, a new adaptive fuzzy inference method using neural network based fuzzy reasoning is proposed to make a fuzzy logic control system more adaptive and more effective. In most cases, the design of a fuzzy inference system rely on the method in which an expert or a skilled human operator would operate in that special domain. However, if he has not expert knowledge for any nonlinear environment, it is difficult to control in order to optimize. Thus, using the proposed adaptive structure for the fuzzy reasoning system can controled more adaptive and more effective in nonlinear environment for changing input membership functions and output membership functions. The proposed fuzzy inference algorithm is called adaptive neuro-fuzzy control(ANFC). ANFC can adapt a proper membership function for nonlinear plant, based upon a minimum number of rules and an initial approximate membership function. Nonlinear function approximation and rotary inverted pendulum control system ar employed to demonstrate the viability of the proposed ANFC.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.689-693
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• 2000

In this paper, we proposed a decoupled adaptive fuzzy sliding-mode control scheme in designing the SMC of a class of fourth-order nonlinear systems. These systems are decoupled the whole system into two second-order systems such that each subsystem has a separate control target expressed in terms of a sliding surface. Then, information from the secondary target conditions the main target, which, in turn, generates a control action to make both subsystem move toward their sliding surface. respectively, and Two sets of fuzzy rule bases are utilized to represent the equivalent control input with unknown system functions of the main target, The membership functions of the THEN-part. which is used to construct a suitable equivalent control of SMC. are changed according to adaptive law, Under this design scheme, we not only maintain the distribution of membership functions over state space but also reduce considerably computing time, we apply the decoupled adaptive sliding-mode control to control a nonlinear inverted pendulum system and confirms the validity of the proposed approach.