• Journal of the Earthquake Engineering Society of Korea
• /
• v.20 no.2
• /
• pp.113-123
• /
• 2016

This paper is concerned with an experimental research to control of random vibration caused by external loads specially in cable-stayed bridges which tend to be structurally flexible. For the vibration control, we produced a model structure modelled on Seohae Grand Bridge, and we designed a shear type MR damper. On the center of its middle span, we placed a shear type MR damper which was to control its vibration and also acquire its structural responses such as displacement and acceleration at the same site. The experiments concerning controlling vibration were performed according to a variety of theories including un-control, passive on/off control, and clipped-optimal control. Its control performance was evaluated in terms of the absolute maximum displacements, RMS displacements, the absolute maximum accelerations, RMS accelerations, and the total power required to control the bridge which differ from each different experiment method. Among all the methods applied in this paper, clipped-optimal control method turned out to be the most effective to reduces of displacements, accelerations, and external power. Finally, It is proven that the clipped-optimal control method was effective and useful in the vibration control employing a semi-active devices such MR damper.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2004-2009
• /
• 2003

A robust optimal control design is proposed in this study for rigid robotic systems under the unknown load and the other uncertainties. The uncertainties are quadratically bounded for some positive definite matrix. Iterative method finding the Q weighting matrix is shown. Computer simulations have been done for a weight-lifting operation of a two-link manipulator and the result of the simulation shows that the proposed algorithm is very effective for a robust control of robotic systems.

• Journal of applied mathematics & informatics
• /
• v.15 no.1_2
• /
• pp.185-200
• /
• 2004

A stochastic optimal LQR control problem under some integral quadratic (IQ) constraints is studied, with cross terms in both the cost and the constraint functionals, allowing all the control weighting matrices being indefinite. Sufficient conditions for the well-posedness of this problem are given. When these conditions are satisfied, the optimal control is explicitly derived via dual theory.

• Journal of Advanced Marine Engineering and Technology
• /
• v.22 no.4
• /
• pp.498-504
• /
• 1998

This paper presents an optimal control algorithm for the overhead crane. To control the swing motion and the position tracking of the payload of the overhead crane a state feedback control algorithm is applied. by using a hybrid genetic algorithm the feedback gains of the state feedback is optimized to minimize the cost function composed of position errors and payload swing angle under unknown constant disturbances. Computer simulation is performed to demonstrate the effectiveness of the proposed control algorithm.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.5
• /
• pp.533-536
• /
• 2014

In this paper, a near optimal decentralized observer-controller design method is proposed for ramp metering systems based on SDRE (State Dependent Riccati Equation) approach. The optimal nonlinear observer gain is parameterized in terms of the solution matrix of an SDRE. This paper gives a simple algorithm to compute the near optimal observer gain. The optimal control design problem is also considered. Finally, numerical simulation results are given to illuminate the effectiveness and practicality of the proposed design method.

• Microbiology and Biotechnology Letters
• /
• v.27 no.3
• /
• pp.223-229
• /
• 1999

The two optimal control algorithms, singular approximation and minimum principle, were compared in this paper. The switching time with singular approximation was determined with mathematical derivation and the optimal control profile of specific growth rate was also calculated with minimum principle. The optimal control profiles were calculated by making simple model correlating the specific cell growth rate and specific product formation rate. The optimal control profiles calculated by singular approximation approach were similar to stepwise form of those calculatd by minimum principles. With the minimum principle, the product concentration was 8% more than that of singular approximation. This performance difference was due to a linearization of a nonlinear function with singular approximation. This optimal approaches were applicable to any system with different optimal cell growth and product formation.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.7
• /
• pp.354-362
• /
• 2000

This paper presents the new adaptive optimal scheme for the nonlinear systems, which is based on the Picard's iterative approximation and fast Walsh transform. It is well known that the Walsh function approach method is very difficult to apply for the analysis and optimal control of nonlinear systems. However, these problems can be easily solved by the improvement of the previous adaptive optimal scheme. The proposed method is easily applicable to the analysis and optimal control of nonlinear systems.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.295-298
• /
• 1996

In this paper, a self-tuning optimal control algorithm is proposed to retain the optimal performance of an active suspension system, when the vehicle has some time varying parameters and parameter uncertainties. We consider a 2 DOF time-varying quarter car model which has the parameter variation of sprung mass, suspension spring constant and suspension damping constant. Instead of solving algebraic riccati equation on line, we propose a neural network approach as an alternative. The optimal feedback gains obtained from the off line computation, according to parameter variations, are used as the neural network training data. When the active suspension system is on, the parameters are identified by the recursive least square method and the trained neural network controller designer finds the proper optimal feedback gains. The simulation results are represented and discussed.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.18 no.1
• /
• pp.1-15
• /
• 2014

We have investigated optimal control strategies for prevention of ecstasy use. Ecstasy use has continued at raves and nightclubs in recent years and the reduction of ecstasy use has become one of the important issues in society. We apply optimal control theory to a model of the peer-driven dynamics of ecstasy use. Our goal is to minimize the ecstasy use class and the intervention cost. Optimal control is characterized in terms of the solution of optimality system, which is the state system coupled with the adjoint system and the optimality equations. The numerical simulations show the optimal prevention policies of ecstasy use in various scenarios.

• International Journal of Automotive Technology
• /
• v.8 no.5
• /
• pp.563-573
• /
• 2007

Optimal design of an automotive catalytic converter for minimization of cold-start emissions is numerically performed using a micro genetic algorithm for two optimization problems: optimal geometry design of the monolith for various operating conditions and optimal axial catalyst distribution. The optimal design process considered in this study consists of three modules: analysis, optimization, and control. The analysis module is used to evaluate the objective functions with a one-dimensional single channel model and the Romberg integration method. It obtains new design variables from the control module, produces the CO cumulative emissions and the integral value of a catalyst distribution function over the monolith volume, and provides objective function values to the control module. The optimal design variables for minimizing the objective functions are determined by the optimization module using a micro genetic algorithm. The control module manages the optimal design process that mainly takes place in both the analysis and optimization modules.