• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.1-23
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• 2005

The decentralized static output feedback design problem is considered. A constrained trust region method is developed that solves this optimal control problem when a complete set of state variables is not available. The considered problem is interpreted as a non-linear (non-convex) constrained matrix optimization problem. Then, a decentralized constrained trust region method is developed for this problem class exploiting the diagonal structure of the problem and using inexact computations. Finally, numerical results are given for the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.56-59
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• 1996

Worst-case state estimation will be proposed in this paper. By using the worst-case disturbance and worst-case state estimation, we can obtain right/left constrained coprime factors. If constrained coprime factors are used in designing a controller, the infinity-norm of closed-loop transfer matrix can be smaller than any constant .gamma.(> .gamma.$_{opt}$) without matrix dilation optimization. The derivation of left/right constrained coprime factors is achieved by doubly coprime factorization for the plant constrained by the infinity norm. And the parameterization of stabilizing controllers gives us easily understanding for H$_{\infty}$ control theory.ry.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.4
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• pp.52-57
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• 2001

The flexural vibration of aluminum beams with active and passive constrained-layer damping has been investigated experimentally to design a structure with maximum possible damping capacity. Piezoelectric film is used as a sensor and piezoceramic as an actuator for the negative velocity feedback control. The experimental results are compared with those by the finite element analysis. This paper shows the effectiveness of active constrained-layer damping treatment through experiments, and we have carried out an experiment to study the effect of beam thickness.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.759-772
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• 2012

In this paper, semi-infinite constrained programming, a class of constrained nonsmooth optimization problems, are transformed into unconstrained nonsmooth convex programs under the help of exact penalty function. The unconstrained objective function which owns the primal-dual gradient structure has connection with $\mathcal{VU}$-space decomposition. Then a $\mathcal{VU}$-space decomposition method can be applied for solving this unconstrained programs. Finally, the superlinear convergence algorithm is proved under certain assumption.

• Architectural research
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• v.8 no.2
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• pp.37-42
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• 2006

Starting from the quadratic optimal control algorithm, this study obtains the relation of the performance index for constrained systems and Gauss's principle. And minimizing a function of the variation in kinetic energy at constrained and unconstrained states with respect to the velocity variation, the dynamic equation is derived and it is shown that the result compares with the generalized inverse method proposed by Udwadia and Kalaba. It is investigated that the responses of a 10-story building are constrained by the installation of a two-bar structure as an application to utilize the derived equations. The structural responses are affected by various factors like the length of each bar, damping, stiffness of the bar structure, and the junction positions of two structures. Under an assumption that the bars have the same mass density, this study determines the junction positions to minimize the total dynamic responses of the structure.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.2
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• pp.119-128
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• 2015

In this paper, we propose a new motion control technology to design robust control system of industrial robot. The system modeling of robotic manipulation tasks with constraints is presented, and the control architecture for unconstrained and constrained motion system with parametric uncertainties is synthesized. The optimal reference of robot manipulator is generated by the reference controller as a discrete state system and the control behavior of constrained system which has poor modeling information and time-invariant constraint function is improved motion control system is successfully evaluated by experiment to the desired tasks.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.376-382
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• 1991

In the analysis of constrained holonomic systems, the Lagange multiplier method yields a system of second-order ordinary differential equations of motion and algebraic constraint equations. Conventional holonomic or nonholonomic constraints are defined as geometric constraints in this paper. Previous works concentrate on the geometric constraints. However, if the total energy of a dynamic system can be computed from the initial energy plus the time integral of the energy input rate due to external or internal forces, then the total energy can be artificially treated as a constraint. The violation of the total energy constraint due to numerical errors can be used as information to control these errors. It is a necessary condition for accurate simulation that both geometric and energy constraints be satisfied. When geometric constraint control is combined with energy constraint control, numerical simulation of a constrained dynamic system becomes more accurate. A new convenient and effective method to implement energy constraint control in numerical simulation is developed based on the geometric interpretation of the relation between constraints in the phase space. Several combinations of energy constraint control with either Baumgarte's Constraint Violation Stabilization Method (CVSM) are also addressed.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1065-1070
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• 2003

We present a power control with variable state feedback gain (VFPC) to improve outage convergence rate of distributed constrained power control. The variable state feedback gain includes the information of the desired SIR changes and must be a decreasing sequence for the convergence. The proof of the convergence is given. The proposed algorithm can improve the outage convergence rate and SIR (Signal to Interference Ratio) response at transient as well as at steady state. The simulation results are given to demonstrate the feasibility of the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.42-47
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• 2014

This paper investigates an adaptive approximation design problem for the tracking control of output-constrained non-affine pure-feedback systems. To satisfy the desired performance without constraint violation, we employ a barrier Lyapunov function which grows to infinity whenever its argument approaches some limits. The main difficulty in dealing with pure-feedback systems considering output constraints is that the system has a non-affine appearance of the constrained variable to be used as a virtual control. To overcome this difficulty, the implicit function theorem and mean value theorem are exploited to assert the existence of the desired virtual and actual controls. The function approximation technique based on adaptive neural networks is used to estimate the desired control inputs. It is shown that all signals in the closed-loop system are uniformly ultimately bounded.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.289-295
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• 2002

In this paper, a linear matrix inequality(LMI)-based robust control method, which combines model predictive control(MPC) with the feedback linearization(FL), is presented for constrained nonlinear systems with parameter uncertainty. The design procedures consist of the following 3 steps: Polytopic description of nonlinear system with a parameter uncertainty via FL, Mapping of actual input constraint by FL into constraint on new input of linearized system, Optimization of the constrained MPC problem based on LMI. To verify the performance and usefulness of the control method proposed in this paper, some simulations with application to a flexible single link manipulator are performed.