• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.2
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• pp.135-140
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• 2012

Fuel Cell Hybrid Vehicles (FCHVs) have already become the subject of major interest among automotive industry as well as power management strategies of FCHVs, as the fuel economy of FCHVs depends on them. There are several types of power management strategies of FCHVs that have been developed to improve the fuel economy of FCHVs. Among them, optimal control theory is applied to this study. A problem is defined and its objective is to minimize the energy consumption of an FCHV and to find the optimal trajectories of powertrain parameters during driving. Necessary conditions for the optimal control are introduced and the simulation results of constant costate are compared to that of variable costate in order to prove that the variable costate can be replaced with the constant costate.

• Nuclear Engineering and Technology
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• v.52 no.3
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• pp.552-559
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• 2020

This paper presents an observer-based chattering free robust optimal control scheme to regulate the total power of a nuclear reactor. The non-linear model of nuclear reactor is linearized around a steady state operating point to obtain a linear model for which an optimal second order integral sliding mode controller is designed. A second order integral sliding mode observer is also designed to estimate the unmeasurable states. In order to avoid the chattering effect, the discontinuous input of both observer and controller are designed using the super-twisting algorithm. The proposed controller is realized by combining an optimal linear tracking controller with a second order integral sliding mode controller to ensure minimum control effort and robustness of the closed-loop system in the presence of uncertainties. The condition for the selection of gains of discontinuous control based on the super-twisting algorithm is derived using a strict Lyapunov function. Performance of the proposed observer based control scheme is demonstrated through non-linear simulation studies.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.2
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• pp.94-103
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• 2004

The vision system model used for this study involves the six parameters that permits a kind of adaptability in that relationship between the camera space location of manipulable visual cues and the vector of robot joint coordinates is estimated in real time. Also this vision control method requires the number of cameras to transform 2-D camera plane from 3-D physical space, and be used irrespective of location of cameras, if visual cues are displayed in the same camera plane. Thus, this study is to investigate the optimal number of cameras used for the developed vision control system according to the change of the number of cameras. This study is processed in the two ways : a) effectiveness of vision system model b) optimal number of cameras. These results show the evidence of the adaptability of the developed vision control method using the optimal number of cameras.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1146-1155
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• 2017

Normally, the artificial intelligence algorithms are widely applied to the optimal controller design. Then, it is expected that the best output performance is achieved. Unfortunately, when resulting controller parameters are implemented by using the practical devices, the output performance cannot be the best as expected. Therefore, the paper presents the optimal controller design using the combination between the state-space averaging model and the adaptive Tabu search algorithm with the new criteria as two penalty conditions to handle the mentioned problem. The buck-boost converter regulated by the cascade PI controllers is used as the example power system. The results show that the output performance is better than those from the conventional design method for both input and load variations. Moreover, it is confirmed that the reported controllers can be implemented using the realistic devices without the limitation and the stable operation is also guaranteed. The results are also validated by the simulation using the topology model of MATLAB and also experimentally verified by the testing rig.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1410-1413
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• 2003

This paper presents the design technique for controlling the oscillation in the Disk Drive Read System via Derivative State Constrained (DSC)-Optimal $H_2$ Controller. The Optimal $H_2$, DSC-Optimal $H_2$ and Incorporating of Stability Degree Specification DSC Optimal $H_2$ are discussed. The results among these schemes are compared to verify the merit of DSC that effectively suppresses the oscillation in oscillatory system. The suggestions of how to select the weights of optimal controls are given.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.433-438
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• 2004

In this paper, we at first describe the linear age-dependent population system. In addition, we introduce the nonlinear population system. Using these age-dependent population systems, we evaluate the stability of these age-dependent population systems and determine the optimal birth rates that realize a target distribution which relaxes an aging population. In this paper, we focus on Japan's population and we use the amount of demographic statistics of Japan in year 2000.

• Smart Structures and Systems
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• v.5 no.3
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• pp.241-260
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• 2009

Shape control of flexible structures using piezoelectric materials has attracted much attention due to its wide applications in controllable systems such as space and aeronautical engineering. The major work in the field is to find a best control voltage or an optimal placement of the piezoelectric actuators in order to actuate the structure shape as close as possible to the desired one. The current research focus on the investigation of static shape control of intelligent shells using spatially distributed piezoelectric curve beam actuators. The finite element formulation of the piezoelectric model is briefly described. The piezoelectric curve beam element is then integrated into a collocated host shell element by using nodal displacement constraint equations. The linear least square method (LLSM) is employed to get the optimum voltage distributions in the control system so that the desired structure shape can be well matched. Furthermore, to find the optimal placement of the piezoelectric curve beam actuators, a genetic algorithm (GA) is introduced in the computation model as well as the consideration of the different objective functions. Numerical results are given to demonstrate the validity of the theoretical model and numerical algorithm developed.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.85-97
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• 2003

An indefinite stochastic linear-quadratic(LQ) optimal control problem with cross term over an infinite time horizon is studied, allowing the weighting matrices to be indefinite. A systematic approach to the problem based on semidefinite programming (SDP) and .elated duality analysis is developed. Several implication relations among the SDP complementary duality, the existence of the solution to the generalized Riccati equation and the optimality of LQ problem are discussed. Based on these relations, a numerical procedure that provides a thorough treatment of the LQ problem via primal-dual SDP is given: it identifies a stabilizing optimal feedback control or determines the problem has no optimal solution. An example is provided to illustrate the results obtained.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.11
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• pp.1003-1012
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• 2000

When a robot hand grasp an object, the number of ways to grasp it stably are infinite and thus an optimal grasp planning is needed to find the optimal grasp points for satisfying the objective of the given task. In this paper, we first define some grasp indices to evaluate the quality of each feasible grasp and then a weighted composite grasp index by combining all of the grasp indices is also defined. Next, we propose a method to find the optimal grasp points of the given object by comparing the defined weighted composite grasp index for each feasible grasp points. By simulation results, we show the effectiveness of the proposed optimal grasp planning method and also discuss the trend of each grasp index as the grasp polygon.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.601-611
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• 2017

This paper proposes a simultaneous control of frequency deviation and electric vehicles (EVs) battery state of charge (SOC) using load frequency control (LFC) and EV controllers. In order to provide both frequency stabilization and SOC schedule near optimal performance within the whole operating regions, a multiple-input multiple-output model predictive control (MIMO-MPC) is employed for the coordination of LFC and EV controllers. The MIMO-MPC is an effective model-based prediction which calculates future control signals by an optimization of quadratic programming based on the plant model, past manipulate, measured disturbance, and control signals. By optimizing the input and output weights of the MIMO-MPC using particle swarm optimization (PSO), the optimal MIMO-MPC for simultaneous control of the LFC and EVs, is able to stabilize the frequency fluctuation and maintain the desired battery SOC at the certain time, effectively. Simulation study in a two-area interconnected power system with wind farms shows the effectiveness of the proposed MIMO-MPC over the proportional integral (PI) controller and the decentralized vehicle to grid control (DVC) controller.