• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.18-21
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• 2014

We propose a nonlinear observer design method for traffic control systems based on T-S fuzzy approach. We parameterize the observer gains in terms of the solution matrices of LMIs. We also give a simple algorithm to compute the observer gain matrices. Finally we give simulation results to show the effectiveness of the proposed fuzzy observer design method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.126-131
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• 2015

Studies on the control of inverted pendulum type systems have been widely reported. This is because this type of system is a typical complex nonlinear system and may be a good model to verify the performance of a proposed control system. In this paper, we propose the design of two fuzzy logic control systems for the control of a Segway mobile robot which is an inverted pendulum type system. We first introduce a dynamic model of the Segway mobile robot and then analyze the system. We then propose the design of the fuzzy logic control system, which shows good performance for the control of any nonlinear system. In this paper, we here design two fuzzy logic control systems for the position and balance control of the Segway mobile robot. We demonstrate their usefulness through simulation examples. We also note the possibility of simplifying the design process and reducing the computational complexity. This possibility is the result of the skew symmetric property of the fuzzy rule tables of the system.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.146-154
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• 2006

In this paper, we propose direct and indirect adaptive fuzzy sliding mode control approaches for a class of nonaffine nonlinear systems. In the direct case, we use the implicit function theory to prove the existence of an ideal implicit feedback linearization controller, and hence approximate it to attain the desired performances. In the indirect case, we exploit the linear structure of a Takagi-Sugeno fuzzy system with constant conclusion to establish an affine-in-control model, and therefore design an indirect adaptive fuzzy controller. In both cases, the adaptation laws of the adjustable parameters are deduced from the stability analysis, in the sense of Lyapunov, to get a more accurate approximation level. In addition to their robustness, the design of the proposed approaches does not require the upper bounds of both external disturbances and approximation errors. To show the efficiency of the proposed controllers, a simulation example is presented.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.697-700
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• 2005

An adaptive fuzzy sliding-mode controller (SMC) for uncertain or ill-defined single-input single-output (SISO) nonaffine nonlinear systems is proposed. By using the universal approximation property of the fuzzy logic system (FLS), it is tuned on-line to cancel the unknown system nonlinearity. We adopt a self-structuring FLS to guarantee global stability of the closed-loop system rather than semi=global boundedness. The control and adaptive laws are derived so that the estimated fuzzy parameters are bounded and the sliding condition is satisfied.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.10a
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• pp.315-318
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• 2008

In this paper proposed the solar tracking system to use a fuzzy control order to increase an output of the PV(Photovoltaic) array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. Recently, artificial intelligent control of the fuzzy control, neural-network and genetic algorithm etc. have been studied. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up, nonlinear altitude and azimuth. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.42-49
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• 2000

This paper presents the application of a FARMA controller to stabilization of nonlinear Two-Generator Five-Bus power Systems. The control rules and the membership functions of the FARMA controller are generated automatically without using any plant model high complexity and severe nonlinearity of power systems are introduced and two-Machine Five -Bus Power system stabilization problem is formulated. The simulation results demonstrate the effectiveness and application possibility of the FARMA controller to the control problem of high order and nonlinear plants.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.499-503
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• 2003

This paper we study the exact controllability for the nonlinear fuzzy control system in $E_N^n$by using the concept of fuzzy number of dimension n whose values are normal, convex, upper semicontinuous and compactly supported surface in $E_N^n$

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.724-732
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• 2016

In this paper, a sampled-data observer-based decentralized fuzzy control technique is proposed for a class of nonlinear large-scale systems, which can be represented to a Takagi-Sugeno fuzzy system. The premise variable is assumed to be measurable for the design of the observer-based fuzzy controller, and the closed-loop system is obtained. Based on an exact discretized model of the closed-loop system, the stability condition is derived for the closed-loop system. Also, the stability condition is converted into the linear matrix inequality (LMI) format. Finally, an example is provided to verify the effectiveness of the proposed techniques.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.112-117
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• 2004

This paper suggests the design and analysis of the fuzzy sliding mode control for a nonlinear system using Takagi-Sugeno(T-S) fuzzy model. In this control scheme, identifying procedure that the input gain matrices in a T-S fuzzy model are manipulated into the same one is needed. The input disturbances generated in the identifying procedure are resolved by incorporating the disturbance treatment method of the conventional sliding mode control. The proposed control strategy can also treat the input disturbances that can not be linearized in the linearization procedure of T-S fuzzy modeling. Design example for the nonlinear system, an inverted pendulum on a cart, demonstrates the utility and validity of the proposed control scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.578-583
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• 2002

This paper presents a method for designing fuzzy $H_2/H_{\infty}$ controllers of nonlinear systems with time varying delay. Takagi-Sugeno fuzzy model is employed to represent nonlinear systems with time varying delay. Using a single quadratic Lyapunov function, the globally exponential stability and $H_2/H_{\infty}$ performance problem are discussed. A sufficient condition for the existence of fuzzy $H_2/H_{\infty}$ controllers is then presented in terms of linear matrix inequalities(LMls). The proposed fuzzy $H_2/H_{\infty}$ controllers minimizes the upper bound on the linear quadratic performance measure.