• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.37 no.6
• /
• pp.15-24
• /
• 2000

This paper presents an output feedback robust H$\infty$ control problem for a class of uncertain nonlinear systems, which can be represented by an fuzzy dynamic model. The nonlinear system is represented by Takagi-Sugeno fuzzy model, and the control design is carried out on the basis of the fuzzy model. Using a single quadratic Lyapunov function, the globally exponential stability and disturance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust H$\infty$ controllers are given in terms of linear matrix inequalities(LMIs). Constructive algorithm for design of robust H$\infty$ controller is also developed. The resulting controller is nonlinear and automatically tuned based on fuzzy operation.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.5
• /
• pp.520-525
• /
• 2003

This paper concerns a design methodology of observer-based output-feedback digital controller for Takagi-Sugeno(TS) fuzzy systems using intelligent digital redesign (IDR). The term of IDR involves converting an analog fuzzy-mode-based controller into an equivalent digital one in the sense of state-matching. The considered IDR problem is viewed as convex minimization problems of the norm distances between linear operators to be matched. The stability condition is easily embedded and the separations principle is explicitly shown.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.2
• /
• pp.159-164
• /
• 2010

This paper focuses on the stability analysis and stabilization for networked control system with neutral type of time-delay. By utilizing the delay partitioning idea, new stability criteria are proposed in terms of linear matrix inequalities(LMIs). These conditions are developed based on the Lyapunov-Krasovskii functionals. Based on the derived criteria, a sufficient condition for te solvability of this problem is obtained in terms of linear matrix inequality without decomposing the original system matrices. Also, it is shown that the proposed controller design method is general for networked control systems. Finally, illustrative examples are presented to show the applicability of the proposed method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.11
• /
• pp.941-947
• /
• 2002

Two methods of constructing T-S fuzzy model which is equivalent to a given nonlinear system are presented. The first method is to obtain an equivalent T-S fuzzy model by using the sum of linearly independent scalar functions with constant real matrix coefficients. The sum of products of linearly independent scalar functions is used in the second method. The former method is to formulate the procedures of T-S fuzzy modeling dealt in many examples of previous publications; the latter is a new method. By comparing the number of linearly independent functions used in the two methods, we can easily find out which method makes fewer rules than the other. The nonlinear dynamics of an inverted Pendulum on a cart is used as an equivalent T-5 fuzzy modeling example.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.5
• /
• pp.692-699
• /
• 2008

This paper describes optimal operation method using recognition of walker's will for a robotic walker. Recently, walking aid system has been required according to the increase of elder and handicapped person. However, most of walking aid system don't have actuator for its movement. Unfortunately, standard frames have weakness for the movement to upward/download direction of slope. So, active type walking aids are interested, but it is not easy to control. In this paper, we adapt user's will system that can recognize walking direction and speed. First, FSR(Force Sensing Register) is applied to measure user's will to walk. And then, fuzzy algorithm is used for determining optimal wheel velocity and direction of the walking aid. From the result, walking aid can move smoothly and safely following the user's will. The walking aid can help user to walk more optimally. Here, all the processes are verified experimentally in the real world.

• Journal of the Korean Society for Precision Engineering
• /
• v.28 no.4
• /
• pp.391-397
• /
• 2011

Control of interior permanent magnet (IPMSM) is difficult because its nonlinearity and parameter uncertainty. In this paper, a fuzzy c-regression models clustering algorithm which is based on T-S fuzzy is used to model IPMSM with a series linear model and weight them by memberships. Lagrangian of constrained function is built for calculating clustering centers where training output data are considered. Based on these clustering centers, least square method is applied for T-S fuzzy linear model parameters. As a result, IPMSM can be modeled as T-S fuzzy model for T-S fuzzy control of them.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.04a
• /
• pp.510-514
• /
• 2004

In this paper, we introduce Fuzzy Beppo Levi's Theorem in which we use the supremum instead of addition in the expression of Beppo Levi's Theorem. That holds under the conditions which are continuity of t-seminorm ┬and the fuzzy additivity of a fuzzy measure g.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2005.11a
• /
• pp.419-422
• /
• 2005

In this note, the Takagi-Sugeno (T-S) fuzzy-model-based state estimator using standard Kalman filter theory is investigated. In that case, the dynamic system model is represented the T-S fuzzy model with the fuzzy state estimation. The steady state solutions can be found for proposed modeling method and dynamic system for maneuvering targets can be approximated as locally linear system. And then, modeled filter is corrected by the fuzzy gain which is a fuzzy system using the relation between the filter residual and its variation. This paper studies the T-S fuzzy model-based state estimator which the dynamic system can be approximated as linear system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.11
• /
• pp.916-921
• /
• 2002

We presents a new method of constructing an equivalent T-S fuzzy model by using the sum of products of linearly independent scalar functions from nonlinear dynamics. This method exactly expresses nonlinear systems and automatically determines the number of rules. We design a stabilizing controller f3r ul inverted pendulum system by using the concep of parallel distributed compensation (PDC) and linear matrix inequalities (LMIs) based on the proposed T-S fuzzy modeling method. We show effectiveness of a systematically designed fuzzy controller based on the proposed T-S fuzzy modeling method through the simulation and experiment of an inverted pendulum system.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.2
• /
• pp.138-143
• /
• 2006

This paper presents intelligent digital redesign method for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an . example to guarantee the stability and effectiveness of the proposed method.