• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.335-340
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• 2008

In this paper, a decentralized fuzzy output feedback controller for nonlinear interconnected systems with time delay is proposed. The nonlinear interconnected system is represented to fuzzy system using Takagi-Sugeno (T-S) fuzzy model. The decentralized output feedback controller is designed(or stability of subsystems of the fuzzy interconnected system. The stable condition of the closed-loop subsystem is represented to the linear matrix inequality (LMI) form and control gain is obtained by LMI. An example is given to show the verification discussed throughout the paper.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.5
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• pp.385-392
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• 2002

This paper introduces a new approach to analysis of error convergence for a class of iterative teaming control systems. Firstly, a nonlinear plant is represented using a Takagi-Sugeno(T-S) fuzzy model. Then each iterative learning controller is designed for each linear plant in the T-S fuzzy model. From the view point of two-dimensional(2-D) system theory, we transform the proposed learning systems to a 2-D error equation, which is also established if the form of T-S fuzzy model. We analyze the error convergence in the sense of induced L$_2$-norm, where the effects of disturbances and initial conditions on 2-D error are considered. The iterative teaming controller design problem to guarantee the error convergence can be reduced to the linear matrix inequality problem. This method provides a systematic design procedure for iterative teaming controller. A simulation example is given to illustrate the validity of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.559-562
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• 2004

In this paper, a new dual-rate digital control technique for the Takagi-Sugeno (T-S) fuzzy system is suggested. The proposed method takes account of the stabilizablity of the discrete-time T-S fuzzy system at the fast-rate sampling points. Our main idea is to utilize the lifted control input. The proposed approach is to obtain the dual-rate discrete-time T-S fuzzy system by discretizing the overall dynamics of the T-S fuzzy system with the lifted control, and then to derive the sufficient conditions for the stabilization in the sense of the Lyapunov asymptotic stability for this system.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.301-307
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• 2004

This paper suggests a fuzzy variable structure control scheme for Takagi-Sugeno(T-S) fuzzy model and presents the attitude control of the wheel-driven inverted pendulum(WDIP) based on the proposed control algorithm. The proposed controller is designed based on the T-S fuzzy modeling of nonlinear system and the unification of gain matrices in linear subsystems that constitute the overall fuzzy model. The uncertainties generated in the gain matrix unifying procedure can be interpreted as the input disturbances of the conventional variable structure control. These unifying disturbances can be resolved by using the robustness property of the conventional variable structure system. Design example for wheel-driven inverted pendulum demonstrates the utility and validity of the proposed control scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.615-623
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• 2008

This paper proposes an $H_{\infty}$ controller design method for Takagi-Sugeno (T-S) fuzzy systems using a fuzzy basis-function-dependent Lyapunov function. Sufficient conditions for the guaranteed $H_{\infty}$ performance of the T-S fuzzy control system are given in terms of linear matrix inequalities (LMIs). These LMI conditions are further used for a convex optimization problem in which the $H_{\infty}-norm$ of the closed-loop system is to be minimized. To facilitate the basis-function-dependent Lyapunov function approach and thus improve the closed-loop system performance, additional decision variables are introduced in the optimization problem, which provide an additional degree-of-freedom and thus can enlarge the solution space of the problem. Numerical examples show the effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.65-71
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• 2013

In this paper, we address fault detection observer design problem of T-S fuzzy systems with sensor fault. To detect fault, T-S fuzzy model-based observer is used. By introducing $\mathfrak{H}$_ performance index, an observer is designed as sensitive to fault as possible. The fault is then detected by a fault decision logic. The design conditions are derived in terms of linear matrix inequalities. An illustrative example is provided to verify the effectiveness of the proposed fault detection technique.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.44-49
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• 1999

This paper presents a new T-S(Tae-Sugeno) fuzzy controller design method satisfying the output energy bound. Maximum output energy via a quadratic Lyapunov function to obtain the bound on output energy is derived. LMI(Linear Matrix Inequality) problems which satisfy an output energy bound for both of the continuous-time and discrete-time T-S fuzzy control system are also derived. Solving these LMIs simultaneously, we find a common symmetric positive definite matrix P which guarantees the global asymptotic stability of the system and stable feedback gains K's satisfying the output energy bound. A simple example demonstrates validity of the proposed design method.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.508-512
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• 2016

This paper discusses a Takagi-Sugeno (T-S) fuzzy controller design problem for a phugoid model-based multi-agent system. The error between the state of a phugoid model and a reference is defined to construct a multi-agent system model. A T-S fuzzy model of the multi-agent system is built by introducing a nonlinear controller. A fuzzy controller is then designed to stabilize the T-S fuzzy model, where the synthesis condition is represented in terms of linear matrix inequalities.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.68-75
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• 2004

In this paper, an estimator with an appropriate adaptive law for updating parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the parameterized plant model. Using the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for indirect adaptive fuzzy control.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.95-105
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• 2001

In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model(SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied for the control of an uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control(CMFC).