• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.411-418
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• 2006

There are mainly two types of bang-bang controllers for nominal linear time-invariant (LTI) system. Optimal bang-bang controller is designed based on optimal control theory and suboptimal bang-bang controller is obtained by using Lyapunov stability condition. In this paper, the suboptimal bang-bang control method is extended to LTI system involving both control input saturation and structured real parameter uncertainties by using Lyapunov robust stability condition. Two robust optimal bang-bang controllers are derived by minimizing the time derivative of Lyapunov function subjected to the limit of control input. The one is developed based on the classical quadratic stability(QS), and the other is developed based on the affine quadratic stability(AQS). And characteristics of the two controllers are compared. Especially, bounds of parameter uncertainties which theoretically guarantee robust stability of the two controllers are compared quantitatively for 1DOF vibrating system. Moreover, the validity of robust optimal bang-bang controller based on the AQS is shown through numerical simulations for this system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.176-181
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• 2002

In this paper, we consider the optimal control of detection threshold to minimize the conditional expectation of mean-square state estimation error for a probabilistic data association (PDA) filter. Earlier works on this problem involved the cumbersome graphical optimization algorithm or time-consuming numerical optimization algorithm. Using the numerical approximation of information reduction factor, we obtained the suboptimal detection threshold in a closed-form. This results are very useful for real- time implementation.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1872-1873
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• 2011

This paper presents a discrete-time approximate linear model of the continuous-time pulse-width-modulated linear system, and then, by employing the resultant model, a simple LQ suboptimal control scheme is proposed for a DC-DC step-down buck converter. The proposed scheme effectively regulates the output voltage to the desired level, which is also verified by the numerical simulation.

• 월간산업보건
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• s.277
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• pp.48-53
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• 2011

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.549-556
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• 2020

This paper proposes several suboptimal methods of designing a controller for a networked control system with state feedback where delay due to transmission error and transmission delay is modeled as a Markov process. A stability condition for a control system with Markov delay is found through an equivalent relationship that corresponding delay-dependent Lyapunov-Krasovskii functional has the same form of the Lyapunov function of an augmented control system. Several suboptimal methods of designing a controller from the stability condition are proposed to reduce complexity. A simple numerical experiment shows that a restricted subspace method which limits the search space of a matrix variable to a block diagonal form provides the best tradeoff between the complexity and performance.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.540-545
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• 1993

When modeling an underwater vehicle uncertainty arises in the presence of unsteady flow. It is difficult to include the uncertainty in the model and is therefore desirable to investigate robust controller design methods for the underwater vehicle. In the paper two robust control methods are applied for the underwater system. One is standard H$_{\infty}$ control and the other is time-varying sliding mode control with modified saturation function. Suboptimal design parameters for H$_{\infty}$ control and design parameters for time-varying switching surfaces are provided. Simulations and comparison are carried out.t.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.13-13
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• 2000

This paper considers delay-dependent guaranteed cost control for uncertain time-delay systems with norm-bounded parametric uncertainties. A new delay-dependent condition for the existence of the guaranteed cost control law is presented in terms of linear matrix inequalities (LMI). An algorithm involving convex optimization is proposed to design a controller which guarantees the suboptimal minimum of the guaranteed cost of the closed-loop system for all admissible uncertainties.

• Journal of computational fluids engineering
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• v.13 no.4
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• pp.96-106
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• 2008

We review a series of studies on turbulent skin friction drag reduction in wall-turbulence recently conducted in Japan. First, an identity equation relating the skin friction drag and the Reynolds shearstress (the FIK identity) is introduced. Based on the implication of the FIK identity, a new analytical suboptimal feedback control law requiring the streamwise wall-shear stress only is introduced and direct numerical simulation (DNS) results of turbulent pipe flow with that control is reported. We also introduce DNS of an anisotropic compliant surface and parameter optimization using an evolutionary optimization technique.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.454-456
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• 1998

Traditional adaptive control algorithms are not robust to dynamic uncertainties. The adaptive control algorithms developed previously to deal with dynamic uncertainties do not facilitate quantitative design. We proposed a new robust adaptive control algorithms consists of an $H^{\infty}$ suboptimal control law and a robust parameter estimator. Numerical examples showing the effectiveness of the $H^{\infty}$ adaptive scheme are provided.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2045-2050
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• 2004

An optimal combination of arbitrary number correlated estimates is derived. In particular, for two estimates this combination represents the well-known Millman and Bar-Shalom-Campo formulae for uncorrelated and correlated estimation errors, respectively. This new result is applied to the various estimation problems as least-squares estimation, Kalman filtering, and adaptive filtering. The new approximate adaptive filter with a parallel structure is proposed. It is shown that this filter is very effective for multisensor systems containing different types of sensors. Examples demonstrating the accuracy of the proposed filter are given.