• 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 Institute of Electronics Engineers of Korea CI
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• v.38 no.6
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• pp.38-45
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• 2001

In this paper, numerical stability analysis methodology for the singleton-type linguistic fuzzy control systems is proposed. The proposed stability analysis is not the analytical method but the numerical method using the convex optimization of Quadratic Programming (QP) and Linear Matrix Inequalities (LMI). Finally, the applicability of the suggested methodology is highlighted via simulation results.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.4
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• pp.1-10
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• 2001

In this paper, we propose the stability analysis and design methodology for the discrete-time affine Type III fuzzy system via the convex optimization technique. First, the stability condition is derived under which the discrete-time affine Type III fuzzy system is quadratically stable in the large. Next, the derived condition is reformulated into the convex optimization problem called Linear Matrix Inequalities (LMI) and numerically addressed. Finally, the effectiveness and the feasibility of the proposed analysis and design methodology is highlighted via an example and its computer simulation result.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.411-416
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• 2016

This paper presents the design methodology of an unknown input observer for Lipschitz nonlinear systems with unknown inputs in the framework of convex optimization. We use an unknown input observer (UIO) to consider both nonlinearity and disturbance. By deriving a sufficient condition for exponential stability in the linear matrix inequality (LMI) form, existence of a stabilizing observer gain matrix of UIO will be assured by checking whether the quadratic stability margin of the error dynamics is greater than the Lipschitz constant or not. If quadratic stability margin is less than a Lipschitz constant, the coordinate transformation may be used to reduce the Lipschitz constant in the new coordinates. Furthermore, to reduce the maximum singular value of the observer gain matrix elements, an object function to minimize it will be optimally designed by modifying its magnitude so that amplification of sensor measurement noise is minimized via multi-objective optimization algorithm. The performance of UIO is compared to a nonlinear observer (Luenberger-like) with an application to a flexible joint robot system considering a change of load and disturbance. Finally, it is validated via simulations that the estimated angular position and velocity provide true values even in the presence of unknown inputs.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.1
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• pp.35-41
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• 2010

In developing modern aircraft, the reconfiguration control that can improve the safety and the survivability against the unexpected failure by partitioning control surfaces into several parts has been actively studied. This paper deals with the reconfiguration control using model predictive control method considering the saturation of control surfaces under the control surface failure. Linearized aircraft model at trim condition is used as the internal model of model predictive control. We propose the controller that performs optimization using LMI (linear matrix inequalities) based semi-definite programming in case that control surface saturation occurs, otherwise, uses analytic solution of the model predictive control. The performance of the proposed control method is evaluated by nonlinear simulation under the flight scenario of control surface failure.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.59-66
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• 2007

In this paper, we consider the non-fragile robust guaranteed cost state feedback controllers design method for descriptor systems with parameter uncertainties and static state feedback controller with multiplicative uncertainty. The sufficient condition of controller existence, the design method of non-fragile robust guaranteed cost controller, the measure of non-fragility in controller, the upper bound of guaranteed cost performance measure to minimize the guaranteed cost are presented via LMI(linear matrix inequality) technique. Also, the sufficient condition can be rewritten as LMI form in terms of transformed variables through singular value decomposition, some changes of variables, and Schur complements. Therefore, the obtained non-fragile robust guaranteed cost controller satisfies the asymptotic stability and minimizes the guaranteed cost for the closed loop descriptor systems with parameter uncertainties and controller fragility. Finally, a numerical example is given to illustrate the design method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.9-14
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• 2005

In this paper, we consider the synthesis of non-fragile $H_{\infty}$ state feedback controllers for singular systems and static state feedback controller with multiplicative uncertainty. The sufficient condition of controller existence, the design method of non-fragile $H_{\infty}$ controller, and the measure of non-fragility in controller are presented via LMI(linear matrix inequality) technique. Also, the sufficient condition can be rewritten as LMI form in terms of transformed variables through singular value decomposition, some changes of variables, and Schur complements. Therefore, the obtained non-fragile $H_{\infty}$ controller guarantees the asymptotic stability and disturbance attenuation of the closed loop singular systems within a prescribed degree. Moreover, the controller design method can be extended to the problem of robust and non-fragile $H_{\infty}$ controller design method for singular systems with parameter uncertainties. Finally, a numerical example is given to illustrate the design method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1162-1167
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• 2004

This paper presents the design methodology of digital fuzzy controller(DFC) for the systems with time-delay. We propose the fuzzy feedback controller whose output is delayed with unit sampling period and predicted. The analysis and the design problem considering time-delay become easy because the proposed controller is syncronized with the sampling time. The stabilization problem of the digital fuzzy system with time-delay is solved by linear matrix inequality(LMI) theory. Convex optimization techniques are utilized to solve the stable feedback gains and a common Lyapunov function for designed fuzzy control system. To show the effectiveness the proposed control scheme, the network control example is presented.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.69-75
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• 2003

This paper presents a fuzzy logic based approach to tracking control of a sampled nonlinear system. It is assumed that the plant to be controlled is under both the internal uncertainty and the external disturbances. Discrete-time adaptive fuzzy control method is proposed and its parameters are determined by the recently-spolighted convex optimization technique called LMI. Finally, the computer simulation is tarried out to verify the effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.72-77
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• 2017

This paper proposes the explicit tuning rule of multi-loop PID controller for brushless direct current motors to predict the system behaviors in time and frequency domains, using properties of the convex combination method. The convex set of the proposed controllers formulates the envelope to satisfy the performances in time and frequency domains. The final control parameters are determined by solving the convex optimization problem subject to the constraints which are represented as convex set of time domain performances. The effectiveness of the proposed control method is shown in the numerical simulation, in which controller tuning algorithm and dynamics of brushless DC motor are well taken into account.