• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.17-27
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• 2007

Minimum-time attitude maneuvers of three-axis stabilized spacecraft are presented to study the feasibility of using three magnetic torquers perform large angle maneuvers. Previous applications of magnetic torquers have been limited to spin-stabilized satellites or supplemental actuators of three axis stabilized satellites because of the capability of magnetic torquers to produce torques about a specific axes. The minimum-time attitude maneuver problem is solved by applying a parameter optimization method for orbital cases to verify that the magnetic torque system can perform as required. Direct collocation and a nonlinear programming method with a constraining method by Simpson's rule are used to convert the minimum-time maneuver problems into parameter optimization problems. An appropriate number of nodes is presented to find a bang-bang type solution to the minimum-time problem. Some modifications in the boundary conditions of final attitude are made to solve the problem more robustly and efficiently. The numerical studies illustrate that the presented method can provide a capable and robust attitude reorientation by using only magnetic torquers. However, the required maneuver times are relatively longer than when thrusters or wheels are used. Performance of the system in the presence of errors in the magnetometer as well as the geomagnetic field model still good.

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.413-419
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• 2007

The optimal power flow (OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, it has been intensively studied and widely used in power system operation and planning. In the past few decades, many stochastic optimization methods such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm Optimization (PSO) have been applied to solve the OPF problem. In particular, PSO is a newly proposed population based stochastic optimization algorithm. The main idea behind it is based on the food-searching behavior of birds and fish. Compared with other stochastic optimization methods, PSO has comparable or even superior search performance for some hard optimization problems in real power systems. Nowadays, some modifications such as breeding and selection operators are considered to make the PSO superior and robust. In this paper, we propose the Modified PSO (MPSO), in which the mutation operator of GA is incorporated into the conventional PSO to improve the search performance. To verify the optimal solution searching ability, the proposed approach has been evaluated on an IEEE 3D-bus test system. The results showed that performance of the proposed approach is better than that of the standard PSO.

• Journal of Communications and Networks
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• v.13 no.4
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• pp.327-338
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• 2011

With the incitation to reduce power consumption and the aggressive reuse of spectral resources, there is an inevitable trend towards the deployment of small-cell networks by decomposing a traditional single-tier network into a multi-tier network with very high throughput per network area. However, this cell size reduction increases the complexity of network operation and the severity of cross-tier interference. In this paper, we consider a downlink two-tier network comprising of a multiple-antenna macrocell base station and a single femtocell access point, each serving multiples users with a single antenna. In this scenario, we treat the following beamforming optimization problems: i) Total transmit power minimization problem; ii) mean-square error balancing problem; and iii) interference power minimization problem. In the presence of perfect channel state information (CSI), we formulate the optimization algorithms in a centralized manner and determine the optimal beamformers using standard convex optimization techniques. In addition, we propose semi-decentralized algorithms to overcome the drawback of centralized design by introducing the signal-to-leakage plus noise ratio criteria. Taking into account imperfect CSI for both centralized and semi-decentralized approaches, we also propose robust algorithms tailored by the worst-case design to mitigate the effect of channel uncertainty. Finally, numerical results are presented to validate our proposed algorithms.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.79-90
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• 2004

Systematical robust stability analysis and design scheme for the feedback linearization control systems via fuzzy modeling are proposed. It is considered that uncertainty and disturbances are included in the Takagi-Sugeno fuzzy models representing the nonlinear plants. Robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions and by converting the analysis and design problems into the linear matrix inequality optimization, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.617-635
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• 2020

The purpose of this study is to discuss how to improve the maneuverability of lifting and diving for underwater vehicle's vertical motion. Therefore, to solve these problems, applied the 3-D numerical simulation, Taguchi's Design of Experiment (DOE), and intelligent parameter design methods, etc. We planned four steps as follows: firstly, we applied the 2-D flow simulation with NACA series, and then through the Taguchi's dynamic method to analyze the sensitivity (β). Secondly, take the data of pitching torque and total resistance from the Taguchi orthogonal array (L9), the ignal-to-noise ratio (SNR), and analysis each factorial contribution by ANOVA. Thirdly, used Radial Basis Function Network (RBFN) method to train the non-linear meta-modeling and found out the best factorial combination by Particle Swarm Optimization (PSO) and Weighted Percentage Reduction of Quality Loss (WPRQL). Finally, the application of the above methods gives the global optimum for multi-quality characteristics and the robust design configuration, including L/D is 9.4:1, the foreplane on the hull (Bow-2), and position of the sail is 0.25 Ls from the bow. The result shows that the total quality is improved by 86.03% in comparison with the original design.

• Design & Manufacturing
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• v.1 no.1
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• pp.17-21
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• 2007

In the manufacture and processing of large plastic materials, product quality is tested and verified through several techniques such as injection processing, residual stress through injection molding and shrinkage. With regards to the injection molding process, common problems such as inconsistent density is seen when different points of the product are discovered to have varying thickness levels. Sink marks in product are then evident. This occurs when there is poor molding conditions caused about by poor runner and packaging systems incorporated into the process. We designed the runner system which is possible balanced filling to cavities using CAE program $Moldflow^{TM}$ and then obtained optimal processing conditions by Taguchi's Robust Design technique.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.1
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• pp.172-178
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• 2003

Driving range is one of the main problems in development of Electric Vehicles(EV). The Regenerative. braking system is required to overcome the problem, which converts kinetic energy of the vehicle during braking into electrical energy. This paper discusses the braking system of EV and Robust design especially developed to maximize energy recovery and to optimize braking performance. This is promised to be applied to the design of elements for EV braking system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.402-409
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• 1999

Variable structure control law is well known to be a robust control algorithm and evolution strategy is used as an effective search algorithm in optimization problems. In this paper, we propose a variable structure controller with time-varying switching surface. We calculate the maximum value of seitching surface gradient that is of the 3rd order polynomial form. Evolution strategy is used to optimize the parameters of the switching surface gradient. Finally, the proposed method is applied to position tracking control for BLDC motor. Experimental results show that the proposed method is more useful than the conventional variable structure controller.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.15-26
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• 2014

This paper proposes a Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients (MPSO-TVAC) for solving economic load dispatch (ELD) problem. Due to prohibited operating zones (POZ) and ramp rate limits of the practical generators, the ELD problems become nonlinear and nonconvex optimization problem. Furthermore, the ELD problem may be more complicated if transmission losses are considered. Particle swarm optimization (PSO) is one of the famous heuristic methods for solving nonconvex problems. However, this method may suffer to trap at local minima especially for multimodal problem. To improve the solution quality and robustness of PSO algorithm, a new best neighbour particle called 'rbest' is proposed. The rbest provides extra information for each particle that is randomly selected from other best particles in order to diversify the movement of particle and avoid premature convergence. The effectiveness of MPSO-TVAC algorithm is tested on different power systems with POZ, ramp-rate limits and transmission loss constraints. To validate the performances of the proposed algorithm, comparative studies have been carried out in terms of convergence characteristic, solution quality, computation time and robustness. Simulation results found that the proposed MPSO-TVAC algorithm has good solution quality and more robust than other methods reported in previous work.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.2
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• pp.126-134
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• 2007

Although there has been substantial research on the squeal noise for the automotive brake system, robust design issues with respect to control factors equivalent to design variables in optimization, noise factors due to system uncertainties, and signal factors designed to accommodate a user-adjustable setting still need to be addressed. For the purpose, the robust design applied to the disk brake system has been investigated by DOE (Design of Experiments) based Taguchi analysis with dynamic characteristics. The specific goal of this methodology is to identify a design with linear signal-response relationship, and variability minimization. The finite element models of the disk brake assembly have been constructed, and the squeal noise problems have been solved by complex eigenvalue analysis. As the practical robust design to reduce the brake squeal noise, material properties of pad, disk, and backplate, thickness and geometry of pad are selected as control factors, material properties of pad and disk, and the contact stiffness have been considered as noise factors, and friction coefficient between pad and disk is chosen as a signal factor. Through the DOE based robust design, the signal-to-noise ratio and the sensitivity for each orthogonal array experiment have been analyzed. Also, it has been proved that the proposed robust design is effective and adequate to reduce the brake squeal noise.