• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.415-422
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• 2000

This paper presents a new algorithm for hierarchical optimal control of nonlinear systems. The proposed method is simple because the solutions are obtained by only exchanging informations of coefficient vector based on interaction prediction principle and FWT(fast Walsh transform) in upper and lower level. Since we solve two point boundary problem with Picard's iterative method and the backward integral operational matrix of Walsh function to obtain the optimal vector of each independent subsystem, the algorithm is simple and its operation is fast without inverse matrix and kronecker product operation. In simulation, the proposed algorithm's usefulness is proved by comparison with the global optimal control methods.

• ETRI Journal
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• v.5 no.2
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• pp.17-28
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• 1983

This paper deals with the problem of optimally controlling traffic flows in urban transportation traffic networks. For this, a nonlinear discrete-time model of urban traffic network is first suggested in order to handle the phenomenon of traffic flows such as oversaturatedness and/or undersaturatedness. Then an optimal control problem is formulated and a hierarchical optimization technique is applied, which is based upon a prediction-type two-level method of Hirvonen and Hakkala.

• Journal of Power Electronics
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• v.19 no.4
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• pp.989-999
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• 2019

This paper proposes a fault-tolerant control strategy with finite control set model predictive control (FCS-MPC) based on hierarchical optimization for five-level H-bridge neutral-point-clamped (5L-HNPC) inverter-fed induction motor drives. Fault-tolerant operation is analyzed, and the fault-tolerant control algorithm is improved. Adopting FCS-MPC based on hierarchical optimization, where the voltage is used as the controlled objective, called model predictive voltage control (MPVC), the postfault controller is simplified as a two layer control. The first layer is the voltage jump limit, and the second layer is the voltage following control, which adopts the optimal control strategy to ensure the current following performance and uniqueness of the optimal solution. Finally, simulation and experimental results verify that 5L-HNPC inverter-fed induction motor drives have strong fault tolerant capability and that the FCS-MPVC based on hierarchical optimization is feasible.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1066-1070
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• 1990

This paper presents a method for the optimal control of the distributed parameter systems (DPSs) by a hierarehical computational procedure. Approximate lumped parameter systems (LPSs) are derived by using the Galerkin method employing the Legendre polynomials as the basis functions. The DPSs however, are transformed into the large scale LPSs. And thus, the hierarchical control scheme is introduced to determine the optimal control inputs for the obtained LPSs. In addition, an approach to block pulse functions is applied to solve the optimal control problems of the obtained LPSs. The proposed method is simple and efficient in computation for the optimal control of DPSs.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.209-213
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• 1987

This paper presents decentralized discrete-time system which is optimized by hierarchical control for process automation via the extended interaction balance method. This proposed method can control general matrix which input matrix is not block diagonalization. Also, this paper shows convergence condition of proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.50.1-50
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• 2001

Dynamic optimization with partially structured model in a slurry-phase HDPE reactor is implemented by the modified hierarchical dynamic optimization. Optimal trajectories of MI and density of HDPE are calculated as controlled variables and optimal profiles of the concentrations of ethylene, hydrogen and comonomer are calculated as manipulated variables in dynamic optimization. MI, density, the concentrations of ethylene, hydrogen and comonomer are used as controlled variables and flow rates of ethylene, hydrogen and comonomer are sued as manipulated variables in control implementation. Two-level hierarchical method is applied in dynamic optimization to reduce computation time. In the upper level formulation ...

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1310-1315
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• 2003

In many practical engineering design problems, there are some design and manufacturing considerations that are difficult or infeasible to express in terms of an objective function or a constraint. In this situation, a set of optimal candidate designs having different topological complexities, not just a single optimal design, is preferred. To generate systematically such design candidates, we propose a hierarchical multiscale design resolution control scheme. In order to adjust its topological complexity by choosing a different starting resolution level in the hierarchical design space, we propose to employ a general M-band wavelet transform in transforming the original design space into the multiscale design space.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.8
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• pp.1161-1166
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• 1989

In this paper, a hierarchical state feedback control method is proposed for the optimal tracking of large-scale discrete-time systems with time-delays. The state feedback gain matrix and the compensation vector are computed from the optimal trajectories of the state variables and control inputs obtained hierarchically by the open-loop control method based on the interaction prediction method. The resulting feedback gain matrix and the compensation vector are optimal for the given initial condition. Computer simulation results show that the proposed method has better control performance and fewer second level iterations than the Tamura method.

• 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.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1595-1607
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• 2018

In this paper, a hierarchical control strategy is introduced to control a new three-port multidirectional DC-DC converter for integrating an energy storage system (ESS) to a bipolar DC microgrid (BPDCMG). The proposed converter provides a voltage-balancing function for the BPDCMG and adjusts the states of charge (SoC) of the ESS. Previous studies tend to balance the voltage of the BPDCMG buses with active sources or by transferring power from one bus to another. Furthermore, the batteries available in BPDCMGs were charged equally by both buses. However, this power sharing method does not guarantee efficient operation of the whole system. In order to achieve a higher efficiency and lower energy losses, a triple-layer hierarchical control strategy, including a primary droop controller, a secondary voltage restoration controller and a tertiary optimization controller are proposed. Thanks to the multi-functional operation of the proposed converter, its conversion stages are reduced. Furthermore, the efficiency and weight of the system are both improved. Therefore, this converter has a significant capability to be used in portable BPDCMGs such as electric DC ships. The converter modes are analyzed and small-signal models of the converter are extracted. Comprehensive simulation studies are carried out and a BPDCMG laboratory setup is implemented in order to validate the effectiveness of the proposed converter and its hierarchical control strategy. Simulation and experimental results show that using the proposed converter mitigates voltage imbalances. As a result, the system efficiency is improved by using the hierarchical optimal power flow control.