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

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.12
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• pp.575-583
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• 2001

It is hard to obtain good robust performance and robust stability for uncertain and time-varying system. The robust 2-DOF controller is frequently used to obtain the desired response and the good robustness. Two controllers can be independently designed. Generally, one controller reduces sensitivity to parameter variations, nonlinear effects, and other disturbances. On the other hand, the other controller reduces the error between the desired command and output. In this paper, the various robust perfect MFCs(model-following controllers) combined with TDC(Time Delay Control) are designed, and the imperfect stable MFC combined with TDC and SMC(Sliding Mode Control) is proposed. These controllers are based on the method of designing robust 2-DOF controllers for dynamic system with uncertainty. The performance of the proposed imperfect sable MFC has been evaluated through computer simulations. The simulation results indicate that the proposed controller shows the excellent performance characteristics for an overhead crane with uncertain and time-varying parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.907-912
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• 2005

In this paper, we consider the problem of designing sliding surfaces fur a class of dynamic systems with mismatched uncertainties in the state space model. In terms of LMIs, we give necessary and sufficient conditions fir the existence of a linear sliding surface such that the reduced order sliding mode dynamics is asymptotically stable and completely independent of uncertainties. We parameterize all such linear sliding surfaces by using the solution to the given LMI conditions. And, we consider the problem of designing linear sliding surfaces guaranteeing pole placement constraints or $H_2/H_infty$ performances. Finally, we give a design example in order to show the effectiveness of our method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.594-597
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• 2005

In this paper, I-PDA controller based on Coefficient Diagram Method incorporating feedforward controller is applied by robotic manipulators. Robotic manipulator models contain uncertain elements, which are not known exactly. Therefore, the dynamics of robotic manipulators are generally classified as uncertain dynamic system. The controller considered for the robotic manipulators need to move payloads of different masses from one point to another with good balance of the stability and response, consequently we propose I-PDA controller based on Coefficient Diagram Method incorporating FFC. The effectiveness of the controller for different system type of robotic manipulators is demonstrated by the simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.27.3-27
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• 2001

In this paper, a robust receding horizon controller for uncertain linear time-varying systems is presented in the dynamic output-feedback form. The existing output-feedback receding horizon controller in the literature is composed of a state observer and a static controller associated with the observer states (similar to LQC control), where the fundamental assumption is that the state observer will supply the exact states as time goes up. The performance of those controllers may be much degraded and even the closed-loop stability may not be guaranteed when the system suffers from disturbances and uncertainties or is time-varying. The proposed controller, which is not necessary to have the state-observer, overcomes such difficulties. Using matrix inequality conditions on the terminal weighting matrix, the closed-loop system stability is guaranteed. Numerical examples are ...

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2320-2322
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• 2001

This paper describes the design of a robust adaptive neural-net(NN) observer for uncertain nonlinear dynamical system. The Lyapunov synthesis approach is used to guarantee a uniform ultimate boundedness property of the state estimation error, as well as of all other signals in the closed-loop system. Especially, for reducing the dynamic oder of the observer, we propose a new method in which no strictly positive real(SPR) condition is needed with on-line estimation of weights of the NNs. No a priori knowledge of an upper bounds on the uncertain terms is required. The theoretical results are illustrated through a simulation example.

• Korean Management Science Review
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• v.29 no.1
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• pp.1-14
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• 2012

The goal of the multi-reservoir operation planning is to provide an optimal release plan that maximize the reservoir storage and hydropower generation while minimizing the spillages. However, the reservoir operation is difficult due to the uncertainty associated with inflows. In order to consider the uncertain inflows in the reservoir operating problem, we present a Stochastic Dynamic Programming (SDP) model based on the markov decision process (MDP). The objective of the model is to maximize the expected value of the system performance that is the weighted sum of all expected objective values. With the SDP model, multi-reservoir operating rule can be derived, and it also generates the steady state probabilities of reservoir storage and inflow as output. We applied the model to the Geum-river basin in Korea and could generate a multi-reservoir monthly operating plan that can consider the uncertainty of inflow.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.199-199
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• 2000

Most of linear time-varying(LTV) systems except special cases have no general solution for the dynamic equations. Thus, it is difficult to design time-varying controllers in analytic ways, and other control design approaches such as robust control have been applied to control design for uncertain LTI systems which are the approximation of LTV systems have been generally used instead. A robust control method such as quantitative feedback theory(QFT) has an advantage of guaranteeing the stability and the performance specification against plant parameter uncertainties in frozen time sense. However, if these methods are applied to the approximated linear time-invariant(LTI) plants which have large uncertainty, the designed control will be constructed in complicated forms and usually not suitable for fast dynamic performance. In this paper, as a method to enhance the fast dynamic performance, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks for LTV systems with bounded time-varying parameters.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.59-66
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• 2010

This paper is proposed an adaptive fuzzy bilinear synchronization design for uncertain $L\ddot{u}$ chaos system. It is assumed that the $L\ddot{u}$ chaos system has unknown parameters. First, The $L\ddot{u}$ chaos system can be reconstructed via TS fuzzy bilinear modeling. We design an adaptive fuzzy bilinear synchronization control scheme based on TS fuzzy bilinear $L\ddot{u}$ chaos system with uncertain parameters. Lyapunov theory is employed to guarantee the stability of error dynamic system between TS fuzzy bilinear $L\ddot{u}$ chaos system and the proposed slave system and to derive the adaptive laws for estimating unknown parameters. Simulation results is given to demonstrate the validity of our proposed synchronization scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.929-938
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• 2009

This paper presents a novel control methodology for communication network based nonlinear systems with time delay nature. We construct a nominal nonlinear control law for representing a linear model and a reset control system which is aimed for corrective control strategy to compensate system error due to uncertain time delay through wireless communication network. Next, online neural control approach is proposed for overcoming nonstationary statistical nature in the network topology. Additionally, DBN (Dynamic Bayesian Network) technique is accomplished for modeling of its dynamics in terms of casuality, which is then utilized for estimating prediction of system output. We evaluate superiority and reliability of the proposed control approach through numerical simulation example in which a nonlinear inverted pendulum model is employed as a networked control system.