• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.517-523
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• 2006

This paper is focused on a robust saturation controller for the stable linear time-invariant (LTI) system involving both actuator's saturation and structured real parameter uncertainties. Based on affine quadratic stability and multi-convexity concept, a robust saturation controller is newly proposed and the linear matrix inequality (LMI)-based sufficient existence conditions for this controller are presented. The controller suggested in this paper can analytically prescribe the lower and upper bounds of parameter uncertainties, and guarantee the closed-loop robust stability of the system in the presence of actuator's saturation. Through numerical simulations, it is confirmed that the proposed robust saturation controller is robustly stable with respect to parameter uncertainties over the prescribed range defined by the lower and upper bounds.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.2
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• pp.73-81
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• 2001

This paper describes the procedure to develop a robust estimator design method for a target tracker that accounts for both structured real parameter uncertainties and unknown inputs. Two robust design approaches are combined: the Mini-p-Norm. design method to consider real parameter uncertainties and the $H_{\infty}$ design technique for unknown disturbances and unknown inputs. Constant estimator gains are computed that guarantee the robust performance of the estimator in the presence of parameter variations in the target model and unknown inputs to the target. The new estimator has two design parameters. One design parameter allows the trade off between small estimator error variance and low sensitivity to unknown parameter variations. Another design parameter allows the trade off between the robustness to real parameter variations and the robustness to unknown inputs. This robust estimator design method was applied to the longitudinal motion tracking problem of a T-38 aircraft.

• Nuclear Engineering and Technology
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• v.35 no.1
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• pp.64-79
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• 2003

In the risk and reliability analysis of complex technological systems, the primary concern of formal uncertainty analysis is to understand why uncertainties arise, and to evaluate how they impact the results of the analysis. In recent times, many of the uncertainty analyses have focused on parameters of the risk and reliability analysis models, whose values are uncertain in an aleatory or an epistemic way. As the field of parametric uncertainty analysis matures, however, more attention is being paid to the explicit treatment of uncertainties that are addressed in the predictive model itself as well as the accuracy of the predictive model. The essential steps for evaluating impacts of these model uncertainties in the presence of parameter uncertainties are to determine rigorously various sources of uncertainties to be addressed in an underlying model itself and in turn model parameters, based on our state-of-knowledge and relevant evidence. Answering clearly the question of how to characterize and treat explicitly the forgoing different sources of uncertainty is particularly important for practical aspects such as risk and reliability optimization of systems as well as more transparent risk information and decision-making under various uncertainties. The main purpose of this paper is to provide practical guidance for quantitatively treating various model uncertainties that would often be encountered in the risk and reliability modeling process of complex technological systems.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.200-214
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• 2016

This paper investigates the problem of stability analysis and robust H_∞ controller for time-delayed systems with parameter uncertainties and stochastic disturbances. It is assumed parameter uncertainties are norm bounded and mean and variance for disturbances of them are known. Firstly, by constructing a newly augmented Lyapunov-Krasovskii functional, a stability criterion for nominal systems with time-varying delays is derived in terms of linear matrix inequalities (LMIs). Secondly, based on the result of stability analysis, a new controller design method is proposed for the nominal form of the systems. Finally, the proposed method is extended to the problem of robust H_∞ controller design for a time-delayed system with parameter uncertainties and stochastic disturbances. To show the validity and effectiveness of the presented criteria, three examples are included.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.67-69
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• 2009

This paper deals with the consensus problem for multi-agent linear dynamic systems with parameter uncertainties. All the agents are identical high-order linear systems with parameter uncertainties and their state information is exchanged through a communication network. It is shown that a consensus is achieved if there exists a feasible solution to a set of linear matrix inequalities obtained for a simultaneous stabilization problem for multiple systems. A numerical example is presented to show the effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2125-2133
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• 2018

To achieve high performance speed regulation, a robust adaptive speed controller is proposed for the permanent magnet synchronous motor (PMSM) subject to parameter uncertainties and input saturations in this paper. A nonlinear adaptive control is introduced to compensate the PMSM speed tracking errors due to uncertainties, disturbances and control input saturation constraints. By combining the adaptive control and the nonlinear robust control based on the interconnection and damping assignment (IDA) strategy, a new robust adaptive control is designed for speed regulation of PMSM. Stability and robustness of the closed-loop control system involved with the constrained control inputs rather than unconstrained control inputs are validated. Simulations for PMSM control in the presence of uncertainties and saturations nonlinearities show that the proposed approach is effective to regulate speed, and the average tracking error using the proposed approach is at least 32% smaller than the compared methods.

• Computational Structural Engineering : An International Journal
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• v.1 no.2
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• pp.81-87
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• 2001

A framework for reliability analysis of structural components and systems under conditions of statistical and model uncertainty is presented. The Bayesian parameter estimation method is used to derive the posterior distribution of model parameters reflecting epistemic uncertainties. Point, predictive and bound estimates of reliability accounting for parameter uncertainties are derived. The bounds estimates explicitly reflect the effect of epistemic uncertainties on the reliability measure. These developments are enhance-ments of second-moment uncertainty analysis methods developed by A. H-S. Ang and others three decades ago.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.362-365
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• 1994

This paper deals with the disturbance attenuation problem for linear systems with real parametric uncertainties. When there are time invariant parameter uncertainties whose sizes are bounded, a less conservative output feedback controller is constructed such that the closed loop system is asymptotically stable and achieves the prescribed disturbance attenuation level for all allowable parameter uncertainties. In order to demonstrate efficacy of the design method a numerical example is presented.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.161-166
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• 1990

In this paper, Proposed the robust controller for robot manipulator plus actuator with dynamic parameter uncertainties. In general, errors and uncertainties system parameters exist more or less between the actual system and mathematical model. To reduce these trems, used Lyapunov stability theorem. The performance of the controller is evaluated for the three degree of freedom robot manipulator plus actuator model with uncertainties of parameters and model errors.

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