• Bulletin of the Korean Space Science Society
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• 2007.10a
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• pp.135-138
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• 2007

The present work is to estimate the stability region of the State-Dependent Riccati Equation (SDRE) controlled system, which is used for a decentralized coordinated attitude control in satellite formation flying. In this research, currently emerging methods which estimate region of attraction for the SDRE controllers are introduced and the methods are applied to attitude control systems. The results guarantee the stability of the given decentralized coordinated attitude control system in satellite formation flying.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1037-1043
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• 2011

Two-wheeled balancing mobile robots are currently controlled in terms of linear control methods without considering the nonlinear dynamical characteristics. However, in the high maneuvering situations such as fast turn and abrupt start and stop, such neglected terms become dominant and greatly influence the overall driving performance. This paper addresses the SDRE nonlinear optimal control method to take advantage of the exact nonlinear dynamics of the balancing robot. Simulation results indicate that the SDRE control outperforms LQR in the respect of transient performance and required wheel torques. A design example is suggested for the state matrix that provides design flexibility in the SDRE control. It is shown that a well-planned state matrix by reflecting the physics of a balancing robot greatly contributes to the driving performance and stability.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2311-2313
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• 2000

In this paper, we consider $H^{\infty}$ optimal Kalman filter problems for linear weakly coupled stochastic systems. We introduce a decomposition for the systems of the Hamiltonian form, which plays an important role of exclusion of ill-condition by ${\varepsilon}$-effect and the parallel computation possibility. It is shown that the algebraic Riccati equation of the weakly coupled $H^{\infty}$ optimal Kalman filter problem is decoupled into completely independent reduced-order, well-defined, two suboptimal Kalman filters.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.157-162
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• 1998

This paper provides some properties of positive real systems in time domain. It is well-known that a positive real system and a bounded real system are closely related by bilinear transform in a frequency domain. By using supply rate and storage function, we show that a positive real system can be transformed into a bounded real system, and that a positive real system can be transformed into another positive real system with in a time domain. Also, we show that an ESPR(extended strictly positive real) system can be decomposed into a feedback system of lossless positive real system and another ESPR system. These results may be used to design an output feedback controller for mixed H$H_2$ESPR problem.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.135-141
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• 2008

A new approach to $H_{\infty}$ multi-step prediction is developed by applying the innovation analysis theory. Although the predictor is derived by resorting to state augmentation, nevertheless, it is completely different from the previous works with state augmentation. The augmented state here is considered just as a theoretical mathematic tool for deriving the estimator. A distributed algorithm for the Riccati equation of the augmented system is presented. By using the reorganized innovation analysis, calculation of the estimator does not require any augmentation. A numerical example demonstrates the effect in reducing computing burden.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.622-628
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• 1999

This paper presented to design a robust turbo-generator control system using {{{{ { H}_{$\infty$ } }}}} control synthesis for improving small-signal stability. Application study of{{{{ { H}_{$\infty$ } }}}} control synthesis is more appropriate in this system since a turbo-generator system is usually operated under circumstance of unmeasurable modelling uncertainty and external disturbance. The{{{{ { H}_{$\infty$ } }}}} control theory was briefly reviewed for good understanding and the reasonable approach. The design results are simulated for a case study and to check the system performance in comparison with currently operating Lead/Lag filtered PSS performance.

• Journal of Power Electronics
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• v.4 no.4
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• pp.228-236
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• 2004

This paper describes the optimal current-control of a permanent magnet synchronous motor by the use of robust and simple current controllers, based upon the analytical procedure known as the inverse LQ (ILQ) design method. The ILQ design method is a strategy for finding the optimal gains based on pole assignment without solving the Riccati equation. It is very important to keep the motor in robust servo-lock. By experiments and simulations, we will show that the ILQ optimal servo-system with servo-lock is more insensitive at low speeds to variations in armature inductance than the standard PI servo-system. Variations in armature inductance have the greatest influence on the responses of a servo-system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.965-971
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• 1999

This paper presented to design the power system stabilizer(PSS) for a turbo-generator system using LQG/LTR control synthesis for improving small-signal stability. Application study of LGG/LTR control synthesis is more appropriate in this system since a turbo-generator system is usually operated under circumstance of unmeasurable uncertainties and external disturbance. The LQG/LTR control theory was briefly reviewed for good understanding and the reasonable design approach. The design results are simulated for a case study and to check the system performance in comparison with currently operating lead-lag filtered PSS performance.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1089-1091
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• 1996

This paper presents a design method of Kalman Filter on continuous nonlinear stochastic system via BPF(Block Pulse Function). When we design Kalman Filter on nonlinear stochastic system, we must linearize this systems. In this paper, we uses the adaptive approach scheme and BPF for linearizing of nonlinear system and solving the Riccati differential equation which is usually guite difficult. This method proposed in this paper is simple and have computational advantages. Furthermore this method is very applicable to analysis and design of Kalman Filter on nonlinear stochastic systems.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.328-330
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• 1993

In this paper, we present a robust $H^{\infty}$ controller for a state delayed system with uncertainties. The unstructured and norm bounded uncertainties enter into both the state and the input matrix, where the matching condition of the uncertainties is not assumed. A robust stabilization condition and also a robust $H^{\infty}$ stabilization condition are suggested. The robust $H^{\infty}$ controller is obtained by solving a Riccati equation which is derived from the suggested robust $H^{\infty}$ stabilization condition.