• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2945-2965
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• 2023

The laser inertial measurement unit is a precision device widely used in rocket navigation system and other equipment, and its quality is directly related to navigation accuracy. In the quality evaluation of laser inertial measurement unit, there is inevitably uncertainty in the index input information. First, the input numerical information is in interval form. Second, the index input grade and the quality evaluation result grade are given according to different national standards. So, it is a key step to transform the interval information input by the index into the data form consistent with the evaluation result grade. In the case of uncertain input, this paper puts forward a method based on probability distribution to solve the problem of asymmetry between the reference grade given by the index and the evaluation result grade when evaluating the quality of laser inertial measurement unit. By mapping the numerical relationship between the designated reference level and the evaluation reference level of the index information under different distributions, the index evidence symmetrical with the evaluation reference level is given. After the uncertain input information is transformed into evidence of interval degree distribution by this method, the information fusion of interval degree distribution evidence is carried out by interval evidential reasoning algorithm, and the evaluation result is obtained by projection covariance matrix adaptive evolution strategy optimization. Taking a five-meter redundant laser inertial measurement unit as an example, the applicability and effectiveness of this method are verified.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1262-1266
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• 2003

Fuzzy sliding mode controller for a class of uncertain nonlinear dynamical systems is proposed and analyzed. The controller's construction and its analysis involve sliding modes. The proposed controller consists of two components. Sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum. The results show that both alleviation of chattering and performance are achieved.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.401-404
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• 1998

In this paper, we present robust reliable $H\infty$ controller design methods of continuous and discrete uncertain time delay systems through LMI(linear matrix inequality) approach, respectively. Also the existence conditions of state feedback control are proposed. Using some changes of varables and Schur complements, the obtained sufficient conditions are transformed into LMI form. We show the validity of the proposed method through numerical examples.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.25-32
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• 1996

This paper will propose the direct adaptive learning control scheme based on adaptive control technique and intelligent control theory for a nonlinear system. Using the proposed learning control scheme, we will apply to on-line control an uncertain but for model perfect matching, it's structure condition is known. The effectiveness of the proposed control schem will be illustrated by simulations of a robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.687-693
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• 1989

A robust deterministic control for a class of singularly perturbed uncertain systems, where uncertainties are characterized deterministically rather than stochastically, is developed based mainly on information available on an uncertain reduced-order system. The deterministic control scheme is applied to the motion control of a n degree of freedom robotic manipulator. The parasitic actuator and sensor dynamics of the manipulator are explicitly considered in the stability analysis of the deterministic controller using a singular perturbation model. Simulation and experimental studies for a two degree of freedom, direct drive SCARA manipulator are conducted to evaluate the effectiveness of the derived control scheme.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.22-30
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• 1993

In this paper, robust adaptive control algorithms which can be applied to unknown uncertain systems are suggested. Transform matrix for dividing states into "uncontrolled" states and "controlled" states and general searching procedure for the transform matrix which assign arbitrary n-1 eigen values for the uncontrolled subsystem of n-th orther single-input single-output systems of which state variables can be observable are also studied and utilized for the design of new-type controllers. We drived new-type control laws by using adaptive control theory and variable structure system and its stability is proved by using Lyapunov stability theory.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.956-960
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• 1987

This paper investigates the control problem which is specified by an uncertain linear system and a linear quadratic performance index. Only the size of parameter uncertainty is assumed to be given instead of its statistics. In addition, a mathing condition which constrains the system structure is assumed to be satisfied. The control law can be obtained by solving an LQ optimal control problem for a nominal system.

• 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.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.46-52
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• 1992

This paper considers uncertain systems with closed-loop poles in a polygonal region. A method is presented which is applicable to computing the perturbation of a pole-located region due to parameter uncertainties. A method is also proposed to calculate the bound on parameter uncertainties which allow the closed-loop poles to remain in a specified region. They provide useful robustness measures on the closed-loop poles of uncertain systems.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.33-38
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• 1996

In this paper, we present a robust H\ulcorner control design method for parameter uncertain systems that have delay in both state and control input. Through a certain algebraic Riccati inequality approach, a state feedback controller is obtained. The proposed state feedback controller stabilizes parameter uncertain delay systems and guarantees disturbance attenuation within a prescribed level. An illustrative example is given to demonstrate the results of the proposed method.