• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.799-808
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• 2004

In this paper, a new collision avoidance algorithm based on the dynamic model of a mobile robot is proposed. In order to avoid obstacles on the path of a mobile robot, intelligent force control is used to regulate accurate distance between a robot and an obstacle. Since uncertainties from robot and environment dynamics degrade the performance of a collision avoidance task, neural network is used to compensate for uncertainties so that the collision avoidance can be performed intelligently. Simulation studies are conducted to confirm the proposed collision avoidance tracking control algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.907-912
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• 2005

In this paper, we consider the problem of designing sliding surfaces fur a class of dynamic systems with mismatched uncertainties in the state space model. In terms of LMIs, we give necessary and sufficient conditions fir the existence of a linear sliding surface such that the reduced order sliding mode dynamics is asymptotically stable and completely independent of uncertainties. We parameterize all such linear sliding surfaces by using the solution to the given LMI conditions. And, we consider the problem of designing linear sliding surfaces guaranteeing pole placement constraints or $H_2/H_infty$ performances. Finally, we give a design example in order to show the effectiveness of our method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.16-21
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• 2005

This paper considers the problem of state estimation in linear continuous-time systems with multi-sensor environment and observation uncertainties. We propose two suboptimal filtering algorithms for these types of systems. The filtering algorithms consist of two steps: The local optimal Kalman estimates are computed at the first step. And, these local estimates are lineally fused at the second step. The implementation of the two-step filtering algorithms needs a lower memory demand than the optimal Kalman and adaptive Lainiotis-Kalman filters. In consequence of parallel structure of the proposed filters, the parallel computers can be used for their design. The examples exhibit the effect of common noise on the performance of fusion of the local Kalman estimates based on observations from different sensors and in the presence of uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.156.4-156
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• 2001

The uncertainties of an atmospheric re-entry flight with respect to stability and controllability are aerodynamic error, measurement error of the angle of attack, variation of dynamic pressure, wind, and trim position of the control surfaces, etc. During hypersonic flight, a future angle of attack is biased from a nominal schedule. In order words, because the angle of attack is estimated from the navigation data, estimation error occurs due to wind, atmospheric density variation, etc. Error models used in this study, include a standard deviation of +-3 sigma, and are the normal distribution of statistics. This paper shows the appraisement of tracking performance onto the reference trajectory, satisfaction of the initial condition of TAEM about the re-entry system.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.261-269
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• 2014

This paper provides an overview of the basics and recent studies of Lyapunov-based nonlinear adaptive control, the aim of which is to improve or maintain the performance and stability of the closed-loop system by cancelling out the presumable uncertainties in the nonlinear system dynamics. The design principles are essentially based on Lyapunov's direct method. In this survey, we provide a comprehensive overview of Lyapunov-based nonlinear adaptive control techniques with simplified effective design examples, which are to be elaborated as related recent results are gradually shown. The scope of the survey contains research on singularity problems in adaptive control, the techniques to deal with linearly and nonlinearly parameterized uncertainties, robust neuro-adaptive control, and adaptive control methodologies combined with various nonlinear control techniques such as sliding-mode control, back-stepping, dynamic surface control, and optimal/$H_{\infty}$ control.

• Journal of The Korean Astronomical Society
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• v.21 no.2
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• pp.155-171
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• 1988

We have examined how sensitively the extinction value determined by the method of star-count depends on such factors as the plate limit, the size of counting reseau, the non-linearity in the number distribution of stars with magnitude, and the angular resolution demanded by the given problem. We let the Poisson distribution portray the statistical nature of the countings, and chose the region containing the globule Barnard 361 as an example field. Uncertainties due to various combinations of the factors are presented in graphic forms: (1) Dynamic range in the extinction measurements is evaluated as a function of reseau size for varying plate limits. (2) Statistical errors involved in the star-count are analized in terms of the signal-to-noise ratio, the plate limit and the reseau size. (3) Systematic error due to the non-linearity in the number distribution are thoroughly analized. (4) Finally, a methodology is presented for correcting the systematic error in the observed radial density gradient. These graphs are meant to be used in selecting proper size of the reseau and in estimating errors inherent to the star-count analysis.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.140-148
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• 2000

This paper presents iterative schemes and continuation schemes for designing robust controllers which stabilize dynamic systems having bounded parametric uncertainties. Utilizing results of the cheap control problem, some existence conditions of the robust controller are obtained, which are different from the matching conditions. continuation schemes are used to overcome the divergence problem of iterative schemes. The roust controller design method is extended to nonlinear system ans easily implementable series solution is also obtained. Results are illustrated with simple examples.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1761-1762
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• 2008

In this paper, we propose an adaptive neural control method to solve this problem. It is assumed that the model uncertainties of the robots dynamics, joint flexibility, and motor dynamics are unknown. The dynamic surface design method is applied, and all uncertainties in the robot and motor dynamics are compensated by using the adaptive function approximation technique. Simulation results for three-link electrically driven flexible-joint (EDFJ) manipulators are provided to validate the effectiveness of the proposed control system.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1775-1776
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• 2008

This paper presents a adaptive fuzzy control suitable for motion control of multi-link robot manipulators with uncertainties. When joint velocities are available, full state adaptive fuzzy feedback control is designed to ensure the stability of the closed loop dynamic. If the joint velocities are not measurable, an observer is introduced and an adaptive output feedback control is designed based on the estimated velocities. To reduce the number of fuzzy rules of the fuzzy controller, we consider the properties of robot dynamics and the decomposition of the unknown input gain matrix. The proposed controller is robust against uncertainties and external disturbances. The validity of the control scheme is demonstrated by computer simulations on a two-link robot manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.218-228
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• 2001

The switched reluctance motor(SRM) has been increasingly used in high-performance servo applications such as electric vehicles, aircraft, and direct-drive robots. The dynamic equations of SRMs are, however, highly nonlinear and this makes it difficult to control SRMs with high performance. In this paper, we propose a new robust current tracking controller for SAMs which can compensate the nonlinear characteristics of SRM(i.e., back-emf and inductance) completely and hence shows perfect tracking performance even with an arbitrary small current control loop gain. Furthermore, even in case that there exist some model uncertainties, our current controller guarantees that the stator currents can track the reference current commands with sufficiently small tracking errors. In order to justify our work, we present the tracking performance analysis and some simulation results.