• Journal of Communications and Networks
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• v.18 no.1
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• pp.8-18
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• 2016

In this paper, we propose a number of blind equalization approaches for time-varying andmulti-path channels. The approaches employ cost reference particle filter (CRPF) as the symbol estimator, and additionally employ either least mean squares algorithm, recursive least squares algorithm, or $H{\infty}$ filter (HF) as a channel estimator such that they are jointly employed for the strategy of "Rao-Blackwellization," or equally called "mixture filtering." The novel feature of the proposed approaches is that the blind equalization is performed based on direct channel estimation with unknown noise statistics of the received signals and channel state system while the channel is not directly estimated in the conventional method, and the noise information if known in similar Kalman mixture filtering approach. Simulation results show that the proposed approaches estimate the transmitted symbols and time-varying channel very effectively, and outperform the previously proposed approach which requires the noise information in its application.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.292-294
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• 1996

In the Industrial motor drive system, a torsional vibration is often generated because of the elastic element in torque transmission. Such system is simply modelled as a two-mass system. In this paper, it is proposed control system which is based on the two-degree-of-freedom PI control and resonance ratio control with the $H^{\infty}$ filter which is robust in disturbance and noise. The control performance of the proposed control system are examined by the computer simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.7
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• pp.1214-1229
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• 2011

Power control is a key technique in spectrum underlay cognitive network to guarantee the interference temperature limit of the primary users (PUs) and the quality of service of the secondary users (SUs). In this paper, a robust power control scheme via link gain pricing with $H_{\infty}$ estimator is proposed. The scheme guarantees the interference temperature of the PUs through operating in the network-centric manner, and keeps the fairness between the SUs through link gain pricing. Furthermore, the $H_{\infty}$ filter is also used in the proposed scheme to estimate the channel variation, and thus the power control scheme is robust to the severe channel fading. Plenty of simulations are taken, and prove its superior robust performance against the channel fading, and its effectiveness in guaranteeing the interference temperature limit of the PUs.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.146-148
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• 1997

An LMI-based parameterization of all $\gamma$-suboptimal reduced-order unbiased $H_{\infty}$ filters is provided in terms of a free matrix, using the unbiasedness condition, bounded real lemma and the general solution of the basic LMI. Also, by sequentially solving the generalized eigenvalue minimization and basic LMI problem, the optimal filter coefficient matrix can be obtained with the best achievable performance.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1961-1963
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• 2001

In a target tracking problem, the radar glint noise has non-Gaussian heavy-tailed distribution and will seriously affect the target tracking performance. In this study, an extended robust $H_{\infty}$ was developed which can significantly improve the tracking performance when glint noise is present. Through the computer simulations, the proposed filter showed superior and robust tracking performance compared with other extended Kalman filters.

• ETRI Journal
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• v.31 no.4
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• pp.399-407
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• 2009

In this paper, we present a robust $H_{\infty}$ distributed power control scheme for wireless CDMA communication systems. The proposed scheme is obtained by optimizing an objective function consisting of the user's performance degradation and the network interference, and it enables a user to address various user-centric and network-centric objectives by updating power in either a greedy or energy efficient manner. The control law is fully distributed in the sense that only its own channel variation needs to be estimated for each user. The proposed scheme is robust to channel fading due to the immediate decision of the power allocation of the next time step based on the estimations from the $H_{\infty}$ filter. Simulation results demonstrate the robustness of the scheme to the uncertainties of the channel and the excellent performance and versatility of the scheme with users adapting transmit power either in a user-centric or a network-centric efficient manner.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1520-1529
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• 2013

In this paper, we propose and assess the performance of "H infinity filter ($H_{\infty}$, HIF)" and "cost reference particle filter (CRPF)" in the problem of tracking a target based on the measurements of the range and the bearing of the target. HIF and CRPF have the common advantageous feature that we do not need to know the noise statistics of the problem in their applications. The performance of the extended Kalman filter (EKF) is also compared with that of the proposed filters, but the noise information is perfectly known for the applications of the EKF. Simulation results show that CRPF outperforms HIF, and is more robust because the tracking of HIF diverges sometimes, particularly when the target track is highly nonlinear. Interestingly, when the tracking of HIF diverges, the tracking of the EKF also tends to deviate significantly from the true track for the same target track. Therefore, CRPF is very effective and appropriate approach to the problems of highly nonlinear model, especially when the noise statistics are unknown. Nonetheless, HIF also can be applied to the problem of timevarying state estimation as the EKF, particularly for the case when the noise statistcs are unknown. This paper provides a good example of how to apply CRPF and HIF to the estimation of dynamically varying and nonlinearly modeled states with unknown noise statistics.

• Smart Structures and Systems
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• v.21 no.2
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• pp.187-194
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• 2018

This paper focuses on the $H_{\infty}$ filter design problem for offshore steel jacket platforms. Its objective is to design a full-order state observer for offshore platforms in presence of unknown disturbances. To make the method more practical, it is assumed that the measured variables are available at discrete-time instants with time-varying sampling time intervals. By modelling the sampling intervals as a bounded time-varying delay, the estimation error system is expressed as a time-delay system. As a result, the addressed problem can be transformed to the problem of stability of dynamic error between the system and the state estimator. Then, based on the Lyapunov-Krasovskii Functional (LKF), a stability criterion is obtained in the form of Linear Matrix Inequalities (LMIs). According to the stability criterion, a sufficient condition on designing the state estimator gain is obtained. In the end, the proposed method is applied to an offshore platform to show its effectiveness.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.177-178
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• 2008

An LMI-based method for robust $L_2-L_{\infty}$ filter design is proposed for poly topic uncertain time-delay systems. By using the Projection Lemma and a suitable linearizing transformation, a strict LMI condition for $L_2-L_{\infty}$ filter design is obtained, which does not involve any iterations for design-parameter search, any couplings between the Lyapunov and system matrices, nor any system-dependent filter parameterization. Therefore, the proposed condition enables one to easily adopt, with help of efficient numerical solvers, a parameter-dependent Lyapunov function approach for reducing conservatism, and to design both robust and parameter-dependent filters for uncertain and parameter-dependent time-delay systems, respectively.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.99-105
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• 1999

This paper presents a fuzzy H$\infty$ filtering problem for a class of uncertain nonlinear systems with time-varying delayed states and unknown inital state on the basis of Takagi-Sugeno(T-S) fuzzy model. The nonlinear systems are represented by T-S fuzzy models, and the fuzzy control systems utilize the concept of the so-called parallel distributed compensation. Using a single quadraic Lyapunov function, the stability and L2 gain performance from the noise signals to the estimation error are discussed. Sufficient conditions for the existence of fuzzy H$\infty$ filters are given in terms of linear matrix inequalities (LMIs). The filtering gains can also be directly obtained from the solutions of LMIs.