• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1464-1468
• /
• 1997

We propose a decentralized state estimation method in the multisensor state estimation problem. The proposed method bounds teh maximum energy gain from uknown external disturbances to the estimation errors in the suboptimal case. And we formulate aternative H/sip .inf./ filter gain equatiions with teh idea that the suboptimal H.$^{\infty}$ filter is the special form of Kalman filter filter whose state equations are defined in indefinite inner product spaces. Using alternative filter gain equations we design the decentralized $H^{\infty}$ state estimator which is composed of local filters and central fusion filter that are suboptimal in the $H^{\infty}$ sense. In addition, the proposed update equations between global and local data can reduce unnecessary calculation burden efficently.y.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1469-1472
• /
• 1997

For system state estimation, existing LMS type esimators widely used. For example Kalman filter is one of them. In this paper, a state estimator is derived for the H$_{\infty}$ norm of the estimation error spectrum matrix to be minimized. For the solution of this problem classical NP interpolation problem is used. Also, by deriving the duality between the filter problem and the well-known H$_{\infty}$ control problem, another solution is obtained. The computer simuation results show that H$_{\infty}$ estimator has less estimation error and so this is better than the existing Kalman filter estimator.or.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.426-429
• /
• 1997

This paper proposes a robust H$_{\infty}$ tracking filter to improve the unacceptable target tracking performance for systems with parameter uncertainties. Also, we use here the input estimation approach to account for the possibility of maneuver. Simulation results show that the robust H$_{\infty}$ tracking filter which is proposed here to solve the systems with all system parameter uncertainties, has a good tracking performance for a maneuvering target tracking problem.m.

• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.414-417
• /
• 1997

We propose a decentralized $H_{\infty}$ state estimation method in the multisensor state estimation problem. The proposed method bounds the maximum energy gain from unknown external disturbances to the estimation errors in the suboptimal case. And we formulate the decentralized state estimation method in the general case of different global and local models using alternative gain equation of the $H_{\infty}$ state estimator which can calculate global state estimates from the the linear combination of local state estimates. In addition, the proposed update equation between global and local Riccati solutions can reduce unnecessary calculation burden efficiently.

• Proceedings of the KIEE Conference
• /
• 1998.07b
• /
• pp.750-753
• /
• 1998

This paper gives a simple parameterization of all stable unbiased filters to solve the suboptimal mixed $H_2/H_{\infty}$ filtering problem. Using the central filter, mixed $H_2/H_{\infty}$ filter is designed which minimizes the upper bound for the $H_2$ norm of the transfer matrix from a white noise to the estimation error subject to an $H_{\infty}$ norm constraint on the transfer matrix from an energy-bounded noise to the estimation error. The problem of finding suitable estimator gain can be converted into a convex optimization problem involving linear matrix inequalities.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.535-535
• /
• 2000

This paper presents an adaptive receding horizon H$_{\infty}$ controller for the linear parameter varying systems in the deterministic environment, which combines a parameter range estimator and a robust receding horizon H$_{\infty}$ controller using the parameter bounds. Using parameter set inclusion and terminal inequality condition, the closed-loop system stability is guaranteed. It is shown that the stabilizing adaptive receding horizon H$_{\infty}$ controller guarantees the H$_{\infty}$ norm bound.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.2
• /
• pp.214-219
• /
• 2010

This paper deals with a nonlinear fuzzy $H_{\infty}$ filter design for SOC(state of charge) estimation in Lithium polymer battery. The dynamic equation of the battery cell is modeled as a T-S fuzzy system and the filter is designed via solutions of linear matrix inequalities. In order to illustrate the performance of the designed filter, a computer simulation is performed using the experimental data with the UDDS(urban dynamometer driving schedule) current profile.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.6
• /
• pp.735-746
• /
• 1999

We design the robust and inherently fault tolerant decetralized$$H^infty$$ filter for the multisensor state estimation problem when there are insufficient priori informations on the statistical properties of external disturbances. For developing the proposed algorithm, an alternative form of suboptimal$$H^infty$$ filter equations are formulated by applying an alternative form of Kalman filter equations to the indefinite inner product space state model of suboptimal$$H^infty$$ filtering problems. The decentralized$$H^infty$$ filter that consists of local and central fusion filters can be designed effciently using the proposed alternative$$H^infty$$ filiter gain equations. The proposed decentralized$$H^infty$$ filter is robust against un-known external disturbances since it bounds the maximum energy gain from the external disturbances to the estimation errors under the prescribed level$$r^2$$ in both local and central fusion filters and is also fault tolerant due to its inherent redundancy. In addition, the central fusion equations between the global and local data can reduce the unnecessary calculation burden effectively. Computer simulations are made to ceritfy the robustness and fault tolerance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.386-391
• /
• 2003

This paper focuses on robust $H_{\infty}$ control for bilinear systems with time-varying parameter uncertainties and exogenous disturbance via output feedback. $H_{\infty}$ control is achieved via separation into a $H_{\infty}$ state feedback control problem and a $H_{\infty}$ state estimation problem. The suitable robust stabilizing output feedback control law can be constructed in term of approximated solution to x-dependent Riccati equation using successive approximation technique. Also, the $H_{\infty}$ filter gain can be constructed in term of solution to algebraic Riccati equation. The output feedback control robustly stabilizes the plant and guarantees a robust $H_{\infty}$ performance for the closed-loop systems in the face of parameter uncertainties and exogenous disturbance.

• Journal of Electrical Engineering and Technology
• /
• v.2 no.4
• /
• pp.445-451
• /
• 2007

Voltage quality problems such as voltage sag, swell, flicker, undervoltage, and overvoltage have been of great concern for both utilities and customers over the last decade. In this paper, a new approach based on the $H_{\infty}$ algorithm to monitor voltage disturbances is presented. The key idea of this approach is to estimate the amplitude of the fundamental component of distorted and noisy voltage waveform instantaneously, and then the information can be extracted from the estimated envelope to identify and classify different voltage related power quality problems. The $H_{\infty}$ algorithm is characterized by a fast tracking, unlike that of existing techniques. The $H_{\infty}$ algorithm outperforms the Kalman Filter (KF) by its fast convergence and robust tracking performance against non-Gaussian noise. The paper investigates the effects of various types of noise on the performance of the $H_{\infty}$ algorithm. Digital simulation results confirm the validity and accuracy of the proposed method. The proposed $H_{\infty}$ algorithm is examined by tracking the flicker produced by a resistance welder simulated in the PSCAD/EMTDC package.