• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.62.2-62
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• 2001

In this paper, we present a new time-varying sliding mode system that guarantees stable error convergence. The previous papers have dealt with stability of the time-varying sliding mode system by point-wisely investigating the stability of time-invariant system every time. However, it may be unstable even though it guarantees time-invariant stability every time, We designed the time-varying sliding surface so that the resultant time-varying system on sliding mode may be Stable. The initial sliding surface is obtained so that shifting distance of the surface may be minimized with respect to an initial error, and the intercept is produced so that the surface may pass the initial error.

• ETRI Journal
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• v.37 no.1
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• pp.11-20
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• 2015

This paper deals with optimal power allocation for channel estimation of orthogonal frequency-division multiplexing uplinks in time-varying channels. In the existing literature, the estimation of time-varying channel response in an uplink environment can be accomplished by estimating the corresponding channel parameters. Accordingly, the optimal power allocation studied in the literature has been in terms of minimizing the mean square error of the channel estimation. However, the final goal for channel estimation is to enable the application of coherent detection, which usually means high spectral efficiency. Therefore, it is more meaningful to optimize the power allocation in terms of capacity. In this paper, we investigate capacity with imperfect channel estimation. By exploiting the derived capacity expression, an optimal power allocation strategy is developed. With this developed power allocation strategy, improved performance can be observed, as demonstrated by the numerical results.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.379-381
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• 2004

In this paper, a robust $H_{\infty}$ stabilization problem to a uncertain fuzzy systems with time-varying delay via static output feedback is investigated. The Takagi-Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear systems with time-varying delayed state. Using a single Lyapunov function, the globally asymptotic stability and disturbance 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.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.255-261
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• 2000

This paper presents the results of the robust H(sub)$\infty$ FIR filtering for a class of nonlinear continuous time-varying systems subject to real norm-bounded parameter uncertainty and know Lipschitz nonlinearity under sampled measurements. We address the problem of designing filters, using sampled measurements, which guarantee a prescribed H(sub)$\infty$ performance in continuous time-varying context, irrespective of the parameter uncertainty and unknown initial states. The infinite horizon causal H(sub)$\infty$FIR filter are investigated using the finite moving horizon in terms of two Riccati equations with finite discrete jumps.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.307-316
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• 2007

In real system application, the interacting multiple model (IMM) based algorithm operates with the following problems: it requires less computing resources as well as a good performance with respect to the various target maneuvering, it requires a robust performance with respect to the time-varying measurement noise, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an adaptive fuzzy interacting multiple model (AFIMM) algorithm, which is based on the basis sub-models defined by considering the maneuvering property and the time-varying mode transition probabilities designed by using the mode probabilities as the inputs of the fuzzy decision maker whose widths are adjusted, is proposed. To verify the performance of the proposed algorithm, a radar target tracking is performed. Simulation results show that the proposed AFIMM algorithm solves all problems in the real system application of the IMM based algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.754-759
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• 1993

An adaptive model predictive control (AMPC) strategy using auto-regression moving-average (ARMA) models is presented. The characteristic features of this methodology are the small computer memory requirement, high computational speed, robustness, and easy handling of nonlinear and time varying MIMO systems. Since the process dynamic behaviors are expressed by ARMA models, the model parameter adaptation is simple and fast to converge. The recursive least square (RLS) method with exponential forgetting is used to trace the process model parameters assuming the process is slowly time varying. The control performance of the AMPC is verified by both comparative simulation and experimental studies on distillation column control.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.6-129
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• 2001

In this paper, we consider a class of time-varying systems with time-varying state delay. Generally, this system is affected by many uncertainties and we assume that the information of the upper bound(time-delay, uncertainty) is known. In this work, we propose a robust control for system with state delay. The stability based on Lyapunov function is presented. Finally, a numberical example is given to demonstrate the validity of the result.

• Journal of the Korean Mathematical Society
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• v.37 no.4
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• pp.593-611
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• 2000

For linear time-varying control systems with constrained control described by both differential and discrete-time equations in Banach spaces was give necessary and sufficient conditions for exact global null-controllability. We then show that for such systems, complete stabilizability implies exact null-controllability.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.460-465
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• 1994

A high precision position control techinque of Brushless DC(BLDC) motor system with time varying parameters is expressed using the self tuning control method. The time varying parameters is estimated on real time by detecting voltage references from controller and mechanical motor speeds from tacho-generator. The effectiveness of the method is evaluated through the positon control experimental results of a BLDC motor system for reference change and arbitrary disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.231-235
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• 1995

In this paper, the frozen time approach is used to analyze the nonlinear system with time varying parameter. Using the extended linearization, we propose two analytical methods that compute an upper bound of the Euclidean norm of the difference between state variable and equilibrium point of the given system. The propertise of the two methods are discussed with simple examples.