• 전기의세계
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• 제26권2호
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• pp.84-88
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• 1977

In this paper we apply the maximum principle to design of time optimal nonlinear sampled-data control systems. We introduce the general design procedures and the mathematical formalas for time optimal processes and trajectories. Then we show the application of the technique to determine the optimal control signal, control sequence, switching time and sampling period to the given 4th order process.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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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.

• International Journal of Control, Automation, and Systems
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• 제4권6호
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• pp.714-724
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• 2006

In this note a method of designing optimal vibration control based on Haar functions to control of bounce and pitch vibrations in engine-body vibration structure is presented. Utilizing properties of Haar functions, a computational method to find optimal vibration control for the engine-body system is developed. It is shown that the optimal state trajectories and optimal vibration control are calculated approximately by solving only algebraic equations instead of solving the Riccati differential equation. Simulation results are included to demonstrate the validity and applicability of the technique.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2002년도 추계학술발표논문집
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• pp.141-144
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• 2002

Recently, the operation of power distribution systems has become more difficult because the peak demand load is increasing continuously and the daily load factor is getting worse and worse. Also, the consideration of deregulation and global environment in electric power industry is required. In order to overcome these problems, a study on the planning and operation in distribution systems of dispersed generating sources such as fuel cell systems, photovoltaic systems and wind power systems has been performed energetically. This study presents a method for determining an optimal operation strategy of dispersed co-generating sources, especially fuel cell systems, in the case of both only electric power supply and thermal supply as well as electric power supply. In other words, the optimal operation of these sources can be determined easily by the principle of equal incremental fuel cost and the thermal merits is evaluated quantitatively through Kuhn-Tucker's optimal conditions. In order to select the optimal locations of those sources, an priority method using the comparison of total cost at the peak load time interval is also presented. The validity of the proposed algorithms is demonstrated using a model system.

• 제어로봇시스템학회논문지
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• 제21권1호
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• pp.28-33
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• 2015

In this paper, we propose a near optimal controller design method for permanent magnet synchronous generators (PMSGs) of MW-class direct-driven wind turbine systems based on SDRE (State Dependent Riccati Equation) approach. Using the solution matrix of an SDRE, we parameterize the optimal controller gain. We present a simple algorithm to compute the near optimal controller gain. The proposed optimal controller can enable PMSGs to precisely track the reference speed determined by the MPPT algorithm. Finally, numerical simulation results are given to verify the effectiveness of the proposed optimal controller.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1270-1273
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• 1993

Fuzzy optimal control is considered. An optimal sequence of controls is sought best satisfying fuzzy constraints on the controls and fuzzy goals on the states (outputs), with a fuzzy system under control Control over a fixed and specified, implicitly specified, fuzzy, and infinite termination time is discussed. For computational efficiency a small number of reference fuzzy staters and controls is to be assumed by which fuzzy controls and stated are approximated. Optimal control policies reference fuzzy states are determined as a fuzzy relation used, via the compositional rule of inference, to derive an optimal control. Since this requires a large number of overlapping reference fuzzy controls and states implying a low computational efficiency, a small number of nonoverlapping reference fuzzy states and controls is assumed, and then interpolative reasoning is used to infer an optimal fuzzy control for a current fuzzy state.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권3호
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• pp.111-116
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• 2000

In this paper, we presented a new algebraic iterative algorithm for the optimal control of the nonlinear systems. The algorithm is based on tow steps. The first step transforms optimal control problem into a sequence of linear optimal control problem using the quasilinearization method. In the second step, TPB(two point boundary condition problem) is solved by algebraic equations instead of differential equations using BPF(block pulse functions). The proposed algorithm is simple and efficient in computation for the optimal control of nonlinear systems. In computer simulation, the algorithm was verified through the optimal control design of Van del pole system and Volterra Predatory-prey system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1258-1261
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• 1993

This paper presents a methodology of path planning and navigation for an autonomous mobile robot. A fast algorithm using decomposition technique, which computes the optimal paths between all pairs of nodes, is proposed for real-time calculation. The robot is controlled by fuzzy approximation reasoning. Our new methodology has been implemented on a mobile robot. The results show that the robot successfully navigates to its destination following the optimal path.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3689-3700
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• 2016

It is not practically feasible to apply hardware-based fault-tolerant schemes, such as hardware replication, in mobile devices. Therefore, software-based fault-tolerance techniques, such as checkpoint and rollback schemes, are required. In checkpoint and rollback schemes, the optimal checkpoint interval should be applied to obtain the best performance. Most previous studies focused on minimizing the expected execution time or response time for completing a given task. Currently, most mobile applications run in real-time environments. Therefore, it is extremely essential for mobile devices to employ optimal checkpoint intervals as determined by the real-time constraints of tasks. In this study, we tackle the problem of determining the optimal inter-checkpoint interval of checkpoint and rollback schemes to maximize the deadline meet ratio in real-time systems and to build a probabilistic cost model. From this cost model, we can numerically find the optimal checkpoint interval using mathematical tools. The performance of the proposed solution is evaluated using analytical estimates.

• Structural Engineering and Mechanics
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• 제23권4호
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• pp.325-337
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• 2006

A hybrid structural design and optimization methodology that combines the strengths of genetic algorithms, local search techniques, and parallel computing is developed to evolve optimal truss systems in this research effort. The primary objective that is met in evolving near-optimal or optimal structural systems using this approach is the capability of satisfying user-defined design criteria while minimizing the computational time required. The application of genetic algorithms to the design and optimization of truss systems supports conceptual design by facilitating the exploration of new design alternatives. In addition, final shape optimization of the evolved designs is supported through the refinement of member sizes using local search techniques for further improvement. The use of the hybrid approach, therefore, enhances the overall process of structural design. Parallel computing is implemented to reduce the total computation time required to obtain near-optimal designs. The support of human-computer interaction during layout optimization and local optimization is also discussed since it assists in evolving optimal truss systems that better satisfy a user's design requirements and design preferences.