• Wind and Structures
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• v.32 no.1
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• pp.71-80
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• 2021

In steel cable bridges, the use of magnetorheological (MR) dampers between butt cables is constantly increasing to dampen vibrations caused by rain and wind. The biggest problem in the actual applications of those devices is to launch a kind of appropriate algorithm that can effectively and efficiently suppress the perturbation of the tie through basic calculations and optimal solutions. This article discusses the optimal evolutionary design based on a linear and quadratic regulator (hereafter LQR) to lessen the perturbation of the bridges with cables. The control numerical algorithms are expected to effectively and efficiently decrease the possible risks of the structural response in amplification owing to the feedback force in the direction of the MR attenuator. In addition, these numerical algorithms approximate those optimal linear quadratic regulator control forces through the corresponding damping and stiffness, which significantly lessens the work of calculating the significant and optimal control forces. Therefore, it has been shown that it plays an important and significant role in the practical application design of semiactive MR control power systems. In the present proposed novel evolutionary parallel distributed compensator scheme, the vibrational control problem with a simulated demonstration is used to evaluate the numerical algorithmic performance and effectiveness. The results show that these semiactive MR control numerical algorithms which are present proposed in the present paper has better performance than the optimal and the passive control, which is almost reaching the levels of linear quadratic regulator controls with minimal feedback requirements.

• Journal of the Korean Mathematical Society
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• v.52 no.3
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• pp.469-487
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• 2015

We consider a model of HIV infection with various compartments, including target cells, infected cells, viral loads and immune effector cells, to describe HIV type 1 infection. We show that the proposed model has one uninfected steady state and several infected steady states and investigate their local stability by using a Jacobian matrix method. We obtain equations for adjoint variables and characterize an optimal control by applying Pontryagin's Maximum Principle in a linear control problem. In addition, we apply techniques and ideas from linear optimal control theory in conjunction with a direct search approach to derive on-off HIV therapy strategies. The results of numerical simulations indicate that hybrid on-off therapy protocols can move the model system to a "healthy" steady state in which the immune response is dominant in controlling HIV after the discontinuation of the therapy.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.330-335
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• 2004

Phase specific models for cancer chemotherapy are described as optimal control problems. We review earlier results on scheduling optimal therapies when the controls represent the effectiveness of chemotherapeutic agents, or, equivalently, when the simplifying assumption is made that drugs act instantaneously. In this paper we discuss how to incorporate more realistic medical aspects which hitherto have been neglected in the models. They include pharmacokinetic equations (PK) which model the drug's plasma concentration and various pharmacodynamic models (PD) which describe the effect the concentrations have on cells. We also briefly discuss the important medical issue of drug resistance.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.485-487
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• 1999

We propose the algorithm with which one can solve the problem of the two-level hierarchical optimal control of nonlinear systems by repeatedly updating the state vectors using the haar function and Picard's iteration methods. Using the simple operation of the coefficient vectors from the fast haar transformation in the upper level and applying that vectors to Picard iteration methods in the independently lower level allow us to obtain the another method except the inversion matrix operation of the high dimention and the kronecker product in the optimal control algorithm.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.4
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• pp.350-357
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• 2002

Optimal control algorithms for the full storage ice cooling system were developed by using a dynamic simulation program. Control algorithms for the storage charging mode were developed for the chiller outlet temperature setpoint control and the chiller capacity control. Control algorithms for the storage discharging mode were developed for the proper mode selection, the storage-only mode control, and the storage-priority chiller-shared mode control. Two different cases of the expected outdoor air temperature profile and the expected cooling load profile were used to analyze the effectiveness of these algorithms. Simulation results show the energy savings and the satisfactory controls of the ice storage system. Therefore, control algorithms developed for this study may effectively be used for the improved control of the ice storage cooling system.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.323-327
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• 1995

A new air knife system for coating thickness control in hot dip galvanizing process had been developed and installed on the CGL in Pohang Steel Works, POSCO. This new system consists of air knives with remotely adjustable nozzle slot and an automatic control system which can control both longitudinal and traverse coating deviations. Based on the optimal control algorithm, a traverse coating deviation control was designed. The controller controls the lip profile of the air knives with flexible structure according to the deviation of coating weight. From the measured values which are dependent on the strip width, the lip gaps are calculated with optimal algorithm and the model of the coating deviation. Time delay between knives and a coating thickness gauge is solved by the Smith Predictor.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.110-117
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• 2013

Maximum Torque Per Amp (MTPA) control for induction motor drives seeks to achieve a desired torque with the minimum possible stator current. This is favorable in terms of inverter operation and nearly optimal in terms of motor efficiency. However, rotor resistance variation can cause significant performance degradation. This work demonstrates that existing MTPA controls perform sub-optimally as temperature varies. An adaptive MTPA control strategy is proposed that always achieves optimal performance without exhibiting hunting phenomenon regardless of rotor temperature. The proposed control is experimentally shown to accurately achieve the desired torque.

• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.145-158
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• 2005

We formulate a stochastic control problem on proportional reinsurance that includes impulse and regular control strategies. For the first time we combine impulse control with regular control, and derive the expected total discount pay-out (return function) from present to bankruptcy. By relying on both stochastic calculus and the classical theory of impulse and regular controls, we state a set of sufficient conditions for its solution in terms of optimal return function. Moreover, we also derive its explicit form and corresponding impulse and regular control strategies.

• Journal of the Korean Society of Safety
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• v.8 no.4
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• pp.213-222
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• 1993

This paper is concerned with automation of tower cranes in view of the robust control of tower crane during take-off, load hoisting, load lowering and landing. The model equation of the tower crane is induced by using Lagrange's equation and it is linearized at equillibrium point. The control is realized by adopting the optimal regulator method. The effectiveness is proved through the experimental results for the oscillation control of cargo rope and the position controls of trolley and boom by the implementation of digital control using 16 bits microcomputer for the designed optimal control law.

• International Journal of Air-Conditioning and Refrigeration
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• v.12 no.3
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• pp.123-130
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• 2004

Control algorithms for an absorption air conditioning system may be developed by using dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help to develop effective control algorithms for the system. In this study, control algorithms for an absorption air conditioning system were developed by using a dynamic simulation program. A cooling water inlet temperature control algorithm, a chilled water outlet temperature control algorithm, and a supply air temperature control algorithm, were developed and analyzed. The steepest descent method was used as an optimal algorithm. Simulation results showed energy savings and the effective controls of an absorption air conditioning system.