• Journal of Mechanical Science and Technology
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• v.18 no.11
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• pp.1916-1922
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• 2004

A robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, and etc. Therefore, uncertainties are often nonlinear and time-varying. The neural network structure presents the bound function and does not need the concave property of the bound function. The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulator.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2161-2163
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• 2004

This paper focuses on congestion control for ATM network with uncertain time-variant delays. The time-variant delays can be distinguished into two distinct components. The first one that is represented by time-variant queueing delays in the intermediate switches is occurred in the return paths of RM cells. The next one is a forward path delay. It is solved by the VBR Model which quantifies the data propagation from the sources to the switch. Robust $H_{\infty}$ control is studied for solving congestion problem with norm-bounded time-varying uncertain parameters. The suitable robust $H_{\infty}$ controller is obtained from the solution of a convex optimization problem including terms of LMIs.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.4
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• pp.312-316
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• 2004

In this paper, it is presented an adaptive robust control system to implement real-time control of a robot manipulator. There are Quantitative or qualitative differences between a real robot manipulator and a robot modeling. In order to compensate these differences, uncertain factors are added to a robot modeling. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, etc. Also, uncertainty is often nonlinear and time-varying. In the proceeding work, we proposed a class of robust control of a robot manipulator and provided the stability analysis. In the work, we propose a class of adaptive robust control of robot manipulator with bound estimation. Through experiments, the proposed adaptive robust control scheme is proved to be an efficient control technique for real-time control of a robot system using DSP.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.501-501
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• 2000

In this paper, the theoretical development to stabilize a class of uncertain time-delay systems via sliding mode control is presented. The system under consideration is described in state space model containing state delay, uncertain parameters and disturbance. The main idea is to reduce the state of delayed system, by employing the generalize linear transformation, into an equivalent one with no delay inside, which is easier to analyze its behavior and stability. Then, the sliding control approach is employed to find the stabilizing control law. Finally, a numerical simulation is illustrated to show the algorithm for applying the proposed theorems and the efffetiveness of the designed control law in stabilizing the controlled systems.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.620-623
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• 1997

This paper is concerned with the design of a suboptimal Kalman filter with robust state estimation performance for system models represented in the state space, which are subjected to parameter uncertainties in both the state and measurement matrices. Under the assumption that the uncertain system is quadratically stable, if the augmented system composed of the uncertain system and the filter is controllable, the proposed filter can provide the upper bound of the estimation error variance for all admissible uncertain parameters. This upper bound can be represented as the convex function of a parameter introduced in the design procedure, and the optimized upper bound of the estimation error variance can also be found via the optimization of this convex function.

• International Journal of Aerospace System Engineering
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• v.6 no.2
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• pp.1-10
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• 2019

In this paper, the probabilistic free vibration analysis of a geometrically coupled cantilever wing with uncertain material properties is carried out using stochastic finite element (SFEM) based on first order perturbation technique. Here, both stiffness and damping of the system are considered as random parameters. The bending and torsional rigidities are assumed as spatially varying second order Gaussian random fields and represented by Karhunen Loeve (K-L) expansion. Here, the expected value, standard deviation, and probability distribution of random natural frequencies and damping ratios are computed. The results obtained from the present approach are also compared with Monte Carlo simulations (MCS). The results show that the uncertain bending rigidity has more influence on the damping ratio and frequency of modes 1 and 3 while uncertain torsional rigidity has more influence on the damping ratio and frequency of modes 2 and 3.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.34.3-34
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• 2001

The design method of H$\infty$ filter for discrete-time uncertain linear systems with multiple state delays is investigated. The uncertain parameters are assumed to be unknown but belonging to known convex compact set of polytope type less conservative than norm bounded parameter uncertainty. The modified H$\infty$ performance measure is introduced to consider the initial states values which affect the performance of filter. The objective is to design a stable H$\infty$ filter guaranteeing asymptotic stability of filtering error dynamics and minimizing H$\infty$ norm bound. The sufficient condition for the existence of filter and the filter design method are established by LMI (linear matrix inequality) approach.

• Journal of KIEE
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• v.10 no.1
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• pp.29-34
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• 2000

In this paper, a design method of a controller is presented for a class of nonlinear systems which have time-varying parametric uncertainly. Some features of this controller are that it can tackle 1) nonlinear parametrization(i.e. uncertain parameters enter the system in the nonlinear form) and 2) nonvanishing peturbation (i.e. uncertainty need not vanish at the origin). The class of systems considered in this paper has the triangular structure for which the well-known backstepping design can be applied. The uncertain parameter is assumed to be contained in the bounded set whose size can be arbitrarily large. Also, the uncertain system are globally uniformly bounded and converge to a compact set whose size is designable. In particular, the first state of the system can be made arbitrarily small, which can be seen by the presented simulation result.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.22 no.1
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• pp.50-65
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• 1993

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.321-324
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• 2003

This paper discusses a robust stochastic stabilization of uncertain Takagi-Sugeno (T-S) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretixzd T-S fuzzy system is represented by a uncertain discrete-time T-S fuzy system with jumping parameters. The robust stochastic stabilizibility of the uncertain jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs).