• Title/Summary/Keyword: Uncertain parameters

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Performance Prediction of Landing Gear Considering Uncertain Operating Parameters (운용 파라미터의 불확실성을 고려한 착륙장치 완충성능 해석)

  • Kim, Tae Uk
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.37 no.7
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    • pp.921-927
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    • 2013
  • The performance estimation of a landing gear with uncertain parameters is presented. In actual use, many parameters can have certain degrees of variations that affect the energy absorbing performance. For example, the shock strut gas pressure, oil volume, tire pressure, and temperature can deviate from their nominal values. The objective function in this study is the ground reaction during touchdown, which is a function of the abovementioned parameters and time. To consider the uncertain properties, convex modeling and interval analysis are used to calculatethe objective function. The numerical results show that the ground reaction characteristics are quite different from those of the deterministic method. The peak load, which affects the efficiency and structural integrity, is increases considerably when the uncertainties are considered. Therefore, it is important to consider the uncertainties, and the proposed methodology can serve as an efficient method to estimate the effect of such uncertainties.

Analysis of Consolidation considering Uncertainties of Geotechnical Parameters and Reliability method (지반특성의 불확실성과 신뢰성 기법을 고려한 압밀해석)

  • Lee, Kyu-Hwan
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.11 no.4
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    • pp.138-146
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    • 2007
  • Geotechnical performance at the soft ground is strongly dependent on the properties of the soil beneath and adjacent to the structure of interest. These soil properties can be described using deterministic and/or probabilistic models. Deterministic models typically use a single discrete descriptor for the parameter of interest. Probabilistic models describe parameters by using discrete statistical descriptors or probability distribution density functions. The consolidation process depends on several uncertain parameters including the coefficients of consolidation and coefficients of permeability in vertical and horizontal directions. The implication of this uncertain parameter in the design of prefabricated vertical drains for soil improvement is discussed. A sensitivity analysis of the degree of consolidation and calculation of settlements to these uncertain parameters is presented for clayey deposits.

Robust stabilization of nonlinear uncertain systems without matching conditions (정합조건을 만족하지 않는 불확정 비선형 시스템의 강인 안정화)

  • 주진만;최윤호;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.159-162
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    • 1997
  • This paper describes robust stabilization of nonlinear single-input uncertain systems without matching conditions. We consider nonlinear systems with a vector of unknown constant parameters perturbed about a known value. The approach utilizes the generalized controller canonical form to lump the unmatched uncertainties recursively into the matched ones. This can be achieved via nonlinear coordinate transformations which depend not only on the states of the nonlinear system but also on the control input. Then the dynamic robust control law is derived and the stability result is also presented.

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Redundant Sensor Systems for the Measurement under Uncertain Conditions (불확실한 조건에서의 계측을 위한 잉여센서시스템)

  • 도용태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.436-439
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    • 2000
  • To interact with surroundings robots and other automated machines employ sensors. However, the sensors measurements are uncertain in some amount and this may limit the potential applications of machines. Varying surrounding conditions and noises of sensor signals are major sources of the uncertainty. In this paper the uncertainty is tried to be reduced by using redundant sensor systems, where the redundancy is accomplished by varying the parameters of logically defined sensors. The target value redundantly measured is estimated adaptively. An experiment was done for measuring the stereoscopic 3D position measurement in an inconsistent light condition.

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Adaptive Control of Uncertain Systems without Knowing Perfect Uncertainty Bounds (불확실한 시스템의 적응제어)

  • Kim, Hong-Seok;Choi, Chong-Ho
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.57-61
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    • 1989
  • An adaptive control scheme is presented for uncertain systems whose uncertaintiy bounds are expressed as a linear combination of unknown functions of special form. Both the states and the parameter estimate errors of the closed-loop system are proven to be bounded. The regulation errors can be made sufficiently small by adjusting the design parameters. An application of the proposed method to the position control of a simple pendulum is given.

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Output-Feedback Control of Uncertain Nonlinear Systems Using Adaptive Fuzzy Observer with Minimal Dynamic Order

  • Park, Jang-Hyun;Huh, Sung-Hoe;Park, Gwi-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.39.2-39
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    • 2001
  • This paper describes the design of an output-feedback controller based on an adaptive fuzzy observer for uncertain single-input single-output nonlinear dynamical systems. Especially, we have focused on the realization of minimal dynamic order of the adaptive fuzzy observer. For the purpose, we propose a new method in which no strictly positive real(SPR) condition is needed and combine dynamic rule activation scheme with on-line estimation of fuzzy parameters. By using proposed scheme, we can reduce computation time, storage space, and dynamic order of the adaptive fuzzy observer ...

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AN EASILY CHECKING CONDITION FOR THE STAVILITY TEST OF A FAMILY OF POLYNOMIALS WITH NONLIMEARLY PERTURBED COEFFICIENTS

  • Kim, Young-Chol;Hong, Woon-Seon
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.5-9
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    • 1995
  • In many cases of robust stability problems, the characteristic polynomial has real coefficients which or nonlinear functions of uncertain parameters. For this set of polynomials, a new stability easily checking algorithm for reducing the conservatism of the stability bound are given. It is the new stability theorem to determine the stability region just in parameter space. Illustrative example show that the presented method has larger stability bound in uncertain parameter space than others.

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DNN-Based Adaptive Optimal Learning Controller for Uncertain Robot Systems (동적 신경망에 기초한 불확실한 로봇 시스템의 적응 최적 학습제어기)

  • 정재욱;국태용;이택종
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.6
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    • pp.1-10
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    • 1997
  • This paper presents an adaptive optimal learning controller for uncertian robot systems which makes use fo simple DNN(dynamic neural network) units to estimate uncertain parameters and learn the unknown desired optimal input. With the aid of a lyapunov function, it is shown that all that error signals in the system are bounded and the robot trajectory converges to the desired one globally exponentially. The effectiveness of the proposed controller is hsown by applying the controller to a 2-DOF robot manipulator.

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Input-Output Feedback Linearizing Control With Parameter Estimation Based On A Reduced Design Model

  • Noh, Kap-Kyun;Dongil Shin;Yoon, En-Sup
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.87.2-87
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    • 2001
  • By the state transformation including independent outputs functions, a nonlinear process model can be decomposed into two subsystems; the one(design model) is described in output variables as new states and used for control system synthesis and the other(disturbance model) is described in the original unavailable states and its couplings with the design model are treated as uncertain time-varying parameters in the design model. Its existence with respect to the design model is ignored. So, the design model is an uncertain time-variant system. Control synthesis based on a reduced design model is a combined ...

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A PID learning controller for DC motors (DC 전동기를 위한 PID 학습제어기)

  • Baek, Seung-Min;Kuc, Tae-Yong
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.6
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    • pp.555-562
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    • 1997
  • With only the classical PID controller applied to control of a DC motor, good (target) performance characteristic of the controller can be obtained if all the model parameters of DC motor and operating conditions such as external load torque, disturbance, etc. are known exactly. However, in case when some of system parameters or operating conditions are uncertain or unknown, the fixed PID controller does not guarantee good performance, which is assumed with precisely known system parameters and operating conditions. In view of this and the robustness enhancement of DC motor control system, we propose a PID learning controller which consists of a set of learning rules for PID gain tuning and learning of an auxiliary input. The proposed PID learning controller is shown to drive the state of uncertain DC motor system with unknown system parameters and external load torque to the desired one world wide asymptotically. Computer simulation and experimental results are given to demonstrate the effectiveness of the proposed PID learning controller, thereby showing its superiority to the conventional fixed PID controller.

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