• Transactions of the Korean Society of Automotive Engineers
• /
• v.23 no.4
• /
• pp.361-370
• /
• 2015

There will inevitably be errors and uncertainties in tire yaw mark related critical speed formula, which is derived merely from the relationship between the centrifugal force and the friction force acting on the point-mass vehicle. Constructing and measuring yaw marks through appropriate simulation works have made it possible to perform uncertainty analysis in calculation of critical speeds under variation of variety of conditions and parameters while existing yaw mark experimental tests have not performed properly. This paper does not present only the critical speed analysis results for parametric sensitivity and uncertainty of chord and middle ordinate, coefficient of friction and road grade, but also modeling uncertainty such as variation of braking level during turning and vehicle size. The yaw mark analysis methods and results may be now applied in practice of traffic accident investigation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.2
• /
• pp.93-102
• /
• 2005

The Nyquist robust stability margin is proposed as a measure of robust stability for systems with Affine TFM(Transfer Function Matrix) parametric uncertainty. The parametric uncertainty is modeled through a Affine TFM MIMO (Multi-Input Multi-Output) description with dead-time, and the unstructured uncertainty through a bounded perturbation of Affine polynomials. Gershgorin's theorem and concepts of diagonal dominance and GB(Gershgorin Bands) are extended to include model uncertainty. Multiloop PI/PID controllers can be tuned by using a modified version of the Ziegler-Nichols (ZN) relations. Consequently, this paper provides sufficient conditions for the robustness of Affine TFM MIMO uncertain systems with dead-time based on Rosenbrock's DNA. Simulation examples show the performance and efficiency of the proposed multiloop design method for Affine uncertain systems with dead-time.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.8
• /
• pp.140-147
• /
• 2015

In this paper, we propose a state feedback robust controller of 2-axis gimbal system which have bounded parametric uncertainty. The proposed controller is robust against dynamics variations of gimbal system and contains a dynamic compensator in order to improve a steady state error and a transient response. The stability of the closed-loop system is proved by Lyapunov approach. The performance of the proposed method is demonstrated by simulation on a 2-axis gimbal system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.7
• /
• pp.547-555
• /
• 2003

This paper presents an adaptive control against uncertainties in tail-controlled STT (Skid-to-Turn) missiles. We derive an analytic uncertainty model from a parametric affine missile model developed by the authors. Based on this analytic model, an adaptive feedback linearizing control law accompanied by a sliding mode control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme are demonstrated by simulation.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.8
• /
• pp.462-470
• /
• 2003

This paper presents an algorithm of identifying parametric uncertainty by way of an interval model. For a given set of frequency response data from an uncertain linear SISO system of which the upper and the lower bounds of both magnitude and phase responses are represented, the proposed algorithm consists of two main parts: first, the nominal model is identified by using Least Square Estimation (LSE), and then an interval model is constructed by expanding the extremal properties of interval systems, so that tightly enclose the given envelopes within those of interval model. Two numerical examples are given to demonstrate and verify the developed algorithm. The identified interval model can be used for evaluating the worst case performance and stability margins against parametric uncertainty by using some extremal properties on interval systems.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.54 no.1
• /
• pp.17-25
• /
• 2005

This paper provides sufficient conditions for the robustness of Affine linear TFM(Transfer Function Matrix) MIMO (Multi-Input Multi-Output) uncertain systems based on Rosenbrock's DNA (Direct Nyquist Array). The parametric uncertainty is modeled through a Affine TFM MIMO description, and the unstructured uncertainty through a bounded perturbation of Affine polynomials. Gershgorin's theorem and concepts of diagonal dominance and GB(Gershgorin Bands) are extended to include model uncertainty. For this type of parametric robust performance we show robustness of the Affine TFM systems using Nyquist diagram and GB, DNA(Direct Nyquist Array). Multiloop PI/PB controllers can be tuned by using a modified version of the Ziegler-Nickels (ZN) relations. Simulation examples show the performance and efficiency of the proposed multiloop design method.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.504-506
• /
• 1999

In this paper, we propose a method which control parametric uncertainty systems using PID controller by fuzzy auto tuning. We get the error and the error change rate of plant output correspond to the initial value of parameter using the Ziegler-Nickols tuning and determine the new proportional gain$(K_p)$ and the integral time $(T_i)$ from fuzzy tuner by the error and error change rate of plant output as a membership function of fuzzy theory. The Fuzzy Auto-tuning algorithm for PID controller operate to adapt variable parameter of plant in parametric uncertainty systems. It is shown this method considerably improve the transient response at computer simulation.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.3 s.96
• /
• pp.180-188
• /
• 1999

${\mu}$-synthesis is applied to design a robust controller for a seeker scan loop system which has model uncertainty and is subject to a external disturbance due to abrupt missile maneuver. The issue of modelling a real-valued parametric uncertainty of a physical seeker scan loop system is discussed. The two-degree-of-frame control structure is employed to obtain better performance. It is shown that ${\mu}$-synthesis provides a superior framework for the robust control design of a seeker scan loop system which exhibits robust performance. The proposed robust control system satisfies design requirements, and especially shows good scanning performances for conical and rosette scan patterns despite parametric uncertainty in real system model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.04a
• /
• pp.133-136
• /
• 2004

This paper proposes a stability condition in affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties and then, introduces the design method of a fuzzy-model-based controller which guarantees the stability. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of linear matrix inequalities (LMIs).

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.4
• /
• pp.825-833
• /
• 2013

An estimation of confidence intervals is essential to calculate uncertainty for greenhouse gases inventory. It is generally assumed that the population has a normal distribution for the confidence interval of parameters. However, in case data distribution is asymmetric, like nonnormal distribution or positively skewness distribution, the traditional estimation method of confidence intervals is not adequate. This study compares two estimation methods of confidence interval; parametric and non-parametric method for exponential distribution as an asymmetric distribution. In simulation study, coverage probability, confidence interval length, and relative bias for the evaluation of the computed confidence intervals. As a result, the chi-square method and the standardized t-bootstrap method are better methods in parametric methods and non-parametric methods respectively.