• Journal of the Korean Mathematical Society
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• v.36 no.1
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• pp.173-192
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• 1999

We study a boundary optimal control problem of the fluid flow governed by the Navier-Stokes equations. the control problem is formulated with the flow through a channel with steps. The first-order optimality condition of the optimal control is derived. Finite element approximations of the solutions of the optimality system are defined and optimal error estimates are derived. finally, we present some numerical results.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1169-1172
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• 1996

A time-optimal control law for quick, strongly nonlinear systems has been developed and demonstrated. This procedure involves the utilization of neural networks as state feedback controllers that learn the time-optimal control actions by means of an iterative minimization of both the final time and the final state error for the known and unknown systems with constrained inputs and/or states. The nature of neural networks as a parallel processor would circumvent the problem of "curse of dimensionality". The control law has been demonstrated for a velocity input type motor identified by a genetic algorithm called GENOCOP.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.31 no.7
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• pp.18-24
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• 1982

We derived an optimal control of the Stochastic Bilinear Systems. For that we, firstly, formulated stochastic bilinear system and estimated its state when the system state is not directly observable. Optimal control problem of this system is reviewed on the line of three optimization techniques. An optimal control is derived using Hamilton-Jacobi-Bellman equation via dynamic programming method. It consists of combination of linear and quadratic form in the state. This negative feedback control, also, makes the system stable as far as value function is chosen to be a Lyapunov function. Several other properties of this control are discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4260-4266
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• 2015

In this study, the optimal control method for minimizing of energy consumption for central cooling system with proper occupant comfort level is researched by simulation. The optimal control method is that the optimal set temperatures such as the condenser water temperature, supply air temperature, and chilled water temperature with environment variable change such as outdoor air dry-bulb and wet-bulb temperatures are obtained by suggested optimal control algorithm with maximum and part building load. The TRNSYS program is used for system modeling and the control performances with the suggested optimal control method are compared with the existing control method of fixed set points. The suggested optimal control method shows better responses in energy consumption in comparison with existing control ones.

• ETRI Journal
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• v.36 no.2
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• pp.280-285
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• 2014

In this paper, the optimal power control problem in a cooperative relay network is investigated and a new power control scheme is proposed based on a non-cooperative differential game. Optimal power allocated to each node for a relay is formulated using the Nash equilibrium in this paper, considering both the throughput and energy efficiency together. It is proved that the non-cooperative differential game algorithm is applicable and the optimal power level can be achieved.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1086-1089
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• 2012

We propose a near optimal controller design method for ramp metering based on SDRE (State Dependent Riccati Equation) approach. We parameterize the optimal nonlinear controller in terms of the solution matrices of an SDRE. We also give a simple algorithm to obtain the controller gain. Finally we give numerical results to show the effectiveness of the proposed near optimal traffic controller design method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.4
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• pp.198-204
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• 2003

In this paper, we presented a new algebraic iterative algorithm for the optimal control of the nonlinear systems. The algorithm is based on two steps. The first step transforms nonlinear optimal control problem into a sequence of linear optimal control problem using the quasilinearization method. In the second step, TPBCP(two point boundary condition problem) is solved by algebraic equations instead of differential equations using the new integral operational matrix of BPF(block pulse functions). The proposed algorithm is simple and efficient in computation for the optimal control of nonlinear systems and is less error value than that by the conventional matrix. In computer simulation, the algorithm was verified through the optimal control design of synchronous machine connected to an infinite bus.

• Journal of Mechanical Science and Technology
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• v.14 no.7
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• pp.764-772
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• 2000

In this paper, an engine-CVT integrated control algorithm is suggested by considering the inertia torque and the CVT ratio change response lag in acceleration. In order to compensate for drive torque time delay due to CVT response lag, two algorithms are presented: (1) an optimal engine torque compensation algorithm, and (2) an optimal engine speed compensation algorithm. Simulation results show that the optimal engine speed compensation algorithm gives better engine operation around the optimal operation point compared to the optimal torque compensation while showing nearly the same acceleration response. The performance of the proposed engine-CVT integrated control algorithms are compared with those of conventional CVT control, and It is found that optimal engine operation can be achieved by using integrated control during acceleration, and improved fuel economy can be expected while also satisfying the driver's demands.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.473-480
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• 2002

The problems of quasi time-optimal digital control are discussed. A new design methodology of quasi time-optimal fuzzy controllers based on approximation of prototype discrete controller is suggested. Four kinds of practicable structures for fuzzy controllers are considered. Examples of computer design of quasi time-optimal fuzzy control systems are given.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1086-1091
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• 2005

This paper focuses on intelligent control of induction motor by hybrid system consisting of GA-PSO. Induction motor has been using in industrial area. However, it is challengeable on how we control effectively. From this point, an optimal solution using GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) is introduced to intelligent control. In this case, it is possible to obtain local solution because chromosomes or individuals which have only a close affinity can convergent. To improve an optimal learning solution of control, This paper deal with applying PSO and Euclidian data distance to mutation procedure on GA's differentiation. Through this approaches, we can have global and local optimal solution together, and the faster and the exact optimal solution without any local solution. Four test functions are used for proof of this suggested algorithm.