• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.847-849
• /
• 1999

본 논문에서는 도립 진자 시스템에 대하여 모델의 불확실성에도 불구하고 수레의 위치가 기준 입력을 추종하는 강건한 2-자유도(two degree of freedom) 제어기를 설계한다. 도립 진자 시스템의 모델 불확실성은 기약 분해 불확실성으로 고려하고, 기준 입력 추종 성능은 도립 진자 시스템의 수레 위치가 원하는 기준 위치로 추종하는 문제를 고려한다. 이러한 강건 안정화와 기준입력 추종사이의 절충 문제를 해결하기 위해서 2-자유도 제어기를 설계한다. 2-자유도 제어기는 프리필터와 피드백 제어기로 구성된다. 설계 절차에 따라 얻어진 제어기는 모의 실험을 통해 그 성능을 확인한다.

• Journal of Advanced Marine Engineering and Technology
• /
• v.32 no.5
• /
• pp.785-790
• /
• 2008

A technique for determining the feedback gain of the states feedback controller using a real-coded genetic algorithm(RCGA) is presented. It is concerned with the states error to the performance index of a RCGA. As for assessing the performance of the controller three performance criteria (ISE. IAE and ITAE) are adopted. And designing the controller involves a constrained optimization problem. Therefore a real-coded genetic algorithm incorporating the penalty strategy is used. The performance of the proposed method is demonstrated through a set of simulation about an inverted pendulum system.

• Journal of the Korean Society of Industry Convergence
• /
• v.6 no.4
• /
• pp.393-399
• /
• 2003

In this paper, a self-organizing fuzzy logic controller with hybrid structure is proposed. The structure of the proposed method is composed of a basic fuzzy logic controller and the FARMA SOC(Fuzzy Autoregressive Moving Average Self-organizing Controller). The self-organizing cntroller with hybrid structure has advantage over the FARMA controller as follows. The proposed controller improves poor performance due to the lack of I/O data to calculate predictive output. I executed some computer simulations on the regulation problem of an inverted pendulum system and compared the results of the proposed method with those of the FARMA SOC method.

• Journal of the Korean Society of Industry Convergence
• /
• v.19 no.3
• /
• pp.101-108
• /
• 2016

I propose a hybrid fuzzy controller with a look-up table to improve the performance of the FARMA(Fuzzy Auto-regressive Moving Average) fuzzy controller. The hybrid structure of the proposed method is composed of a fuzzy controller with a look-up table of the PD type and the FARMA fuzzy controller. The proposed method improves poor performance due to the lack of I/O data to calculate predictive output and shows robust performance over the FARMA fuzzy controller when a incorrect Dmax value is selected by trial and error. I executed some computer simulations on the regulation problem of an inverted pendulum system and compared the results with those of the FARMA fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.388-388
• /
• 2000

The complexity of nonlinear systems makes it difficult to ascertain their behavior using classical methods of analysis. Many efforts have been focused on the advanced algorithms and techniques that hold the promise of improving real-time optimal control while at the same time providing higher accuracy. In this paper, a fuzzy cell mapping method of real-time optimal control far nonlinear dynamical systems is proposed. This approach combines fuzzy logic with cell mapping techniques in order to find the optimal input level and optimal time interval in the finite set which change the state of a system to achieve a desired obiective. In order to illustrate this method, we analyze the behavior of an inverted pendulum using fuzzy cell mapping.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.3
• /
• pp.362-373
• /
• 2004

In this study, we introduce a noble neurogenetic approach to the design of the fuzzy controller. The design procedure dwells on the use of Computational Intelligence (CI), namely genetic algorithms and neurofuzzy networks (NFN). The crux of the design methodology is based on the selection and determination of optimal values of the scaling factors of the fuzzy controllers, which are essential to the entire optimization process. First, tuning of the scaling factors of the fuzzy controller is carried out, and then the development of a nonlinear mapping for the scaling factors is realized by using GA based NFN. The developed approach is applied to an inverted pendulum nonlinear system where we show the results of comprehensive numerical studies and carry out a detailed comparative analysis.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2283-2286
• /
• 2000

Sliding control is a powerful approach to controlling nonlinear and uncertain systems. Conventional sliding mode control suffer' from high control gain and chattering problem. also it needs mathematic! modeling equations for control systems. A Fuzzy controller is endowed with control rules and membership function that are constructed on the knowledge of expert, as like intuition and experience. but It is very difficult to obtain the exact values which are the membership function and consequent parameters. In this paper, without mathematical modeling equations, the plant parameters in sliding mode are estimated by the indirect adaptive fuzzy method. the proposed algorithm could analyze the system's stability and convergence behavior using Lyapunov theory. so sliding modes are reconstructed and decreased tracking error. moreover convergence time took a short. An example of inverted pendulum is given for demonstration of the robustness of proposed methodology.

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

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.9
• /
• pp.1802-1808
• /
• 2009

A fault detection observer with finite time convergence characteristics(FT_FDO) is proposed and applied to a fault detection isolation system for a dynamic control system. The FT_FDO is a kind of dual state-observer scheme that provides with the state estimates insensitive to a specified fault and the corresponding fault estimate. The state estimates are processed to get the residual that will be logically compared with other residuals to detect and isolate the fault of interest, and the fault estimate may be used for fault compensation. The FDIS employing the FT_FDOs can be considered to be a multiple observer schemes(MOS) in which FT_FDOs are parallelly driven to generate a set of residuals to be compared each other. Due to the finite time convergence characteristics of the FT_FDO, the predetermined detection delay can be considered in the design stage of FDIS so that any fault of interest can be detected and identified in that time. It evidently resolves a well known difficulty of threshold selection owing to the transient responses of the fault detection observers(FDO) employed in FDIS. An FDIS is constructed for instruments(2-sensor, 1-actuator) in an inverted pendulum control system, and simulations are performed to show the performance of the FDIS and fault tolerant control system.

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