• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.75-82
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• 2006

In this paper, we propose an optimal trajectory for biped robots to move up-and-down stairs using a genetic algorithm and a computed-torque control for biped robots to be dynamically stable. First, a Real-Coded Genetic Algorithm (RCGA) which of operators are composed of reproduction, crossover and mutation is used to minimize the total energy. Constraints are divided into equalities and inequalities: Equality constraints consist of a position condition at the start and end of a step period and repeatability conditions related to each joint angle and angular velocity. Inequality constraints include collision avoidance conditions of a swing leg at the face and edge of a stair, knee joint conditions with respect to the avoidance of the kinematic singularity, and the zero moment point condition with respect to the stability into the going direction. In order to approximate a gait, each joint angle trajectory is defined as a 4-th order polynomial of which coefficients are chromosomes. The effectiveness of the proposed optimal trajectory is shown in computer simulations with a 6-dof biped robot that consists of seven links in the sagittal plane. The trajectory is more efficient than that generated by the modified GCIPM. And various trajectories generated by the proposed GA method are analyzed in a viewpoint of the consumption energy: walking on even ground, ascending stairs, and descending stairs.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.424-430
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• 2001

A multi-level optimal power flow(OPF) algorithm has been evolved from a simple two stage optimal Power flow algorithm for constrained power economic dispatch control. In the proposed algorithm, we consider various constraints such as ower balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the two stage optimization method to an average gain of 2.99 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.926-928
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• 1998

A fast optimization algorithm has been evolved from a simple two stage optimal power flow(OPF) algorithm for constrained power economic dispatch. In the proposed algorithm, we consider various constraints such as power balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the coupled LP based OPF method to an average gain of 53.13 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.549-554
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• 2012

In this paper, we consider the optimal fuzzy filter of nonlinear discrete-time with estimation error variance constraint. First, the Takagi and Sugeno(T-S) fuzzy model is employed to approximate the nonlinear system. Next, the error state is mean square bounded, and the steady state variance of the estimation error of each state is not more than the individual predefined value. It is shown that, the addressed problem can be carried out by solving linear matrix inequality(LMI) and some algebraic quadratic matrix inequalities. Finally, some examples are provided to illustrate the design procedure and expected performance through simulations.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.1
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• pp.92-101
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• 2010

Recently, the magnetic bearings which have many advantages such as no noise, less mechanical friction are widely applied to the suspension of rotors on the rotary machineries. However, the magnetic bearing system is inherently unstable, nonlinear and MIMO(multi-input-multi-output) system as well. In this paper, we design a state feedback controller using linear matrix inequality(LMI) to the multi-objective synthesis, for the magnetic bearing system with integral type servo system. The design objectives include $H_{\infty}$ performance, asymptotic disturbance rejection, and time-domain constraints on the closed-loop pole location. The results of computer simulation show the validity of the designed controller.

• KDI Journal of Economic Policy
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• v.27 no.1
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• pp.1-38
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• 2005

Our paper aims to estimate a household consumption function in the presence of liquidity constraints as well as household characteristics. Empirical findings from a Korean cross-sectional data (National Survey of Household Income and Expenditure) reveal that several family characteristics, such as household size, number of working members, children in school, and educational level and age of the household head, turn out to be critical determinants of household consumption. Especially, the influence of household size on consumption decision is shown to be highly significant, not only indirectly through its impact on household income, but also directly by affecting the household's preference for consumption itself. While, the other family characteristics primarily influences household income. Our paper distinguishes itself from existing literature in that it greatly improves the explanatory power of the estimated household consumption function by measuring the degree of the liquidity constraint rather than simply identifying its presence. Based on the assumption that the present value of human capital is a function of household characteristics, the degree of the liquidity constraint is represented by the underestimated portion of the human capital. Such a method of implementing the liquidity constraint is useful in treating various types of assets according to their liquidity. Finally, our estimated household consumption function is applied to decompose cross-sectional variances of consumption inequality. The analysis confirms that the overall alleviation in liquidity constraints in Korea after the 1997 currency crisis reduced consumption inequality despite the worsening of income inequality and changes in the demographic composition of family characteristics during the same period.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.441-447
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• 2012

This paper presents a design technique of a Takagi-Sugeno (T-S) fuzzy-model-based $H_{\infty}$ controller for autonomous underwater vehicles (AUVs). The design procedure aims to render the stabilizing controller which satisfies performance of the diving control for AUVs in the presence of the disturbance. A nonlinear AUV is modeled by the T-S fuzzy system through the sector nonlinearity. By using Lyapunov function, the sufficient conditions are derived to guarantee the performance of robust depth control in the format of linear matrix inequality (LMI). To succeed for diving control of AUV, we add the constraints on the diving and pitch angles in the LMI conditions. Through the simulation, we confirm the effectiveness of the proposed methodology.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.2
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• pp.32-38
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• 2005

In this research, a procedure to improve the feasibility of design space is proposed by an approximation model. The Chebyshev Inequality is used as the criterion of modification of design space. This procedure is applied to the aero-elastic transonic wing design problem and the feasibility of the design space is greatly improved. Also the optimization results are improved by appling this procedure. That is, the probability to satisfy all imposed constraints is increased and the better design points are included in design space after this procedure. And the use of both a second-order response surface model and the Kriging model is investigated and compared in accuracy, efficiency, and robustness as approximation models in this procedure for different sampling methods. As a result, the second-order response surface model is more appropriate for our application than the Kriging model, because it is linear enough to be fitted well by the response surface model.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.3
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• pp.275-283
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• 2012

This paper presents a design method of a robust tracking controller satisfying multiple constraints using genetic algorithm. A robust $H_{\infty}$ constraint with loop shaping is used to address disturbance attenuation with error limits and a loop gain constraint is considered so as not to enlarge the tracking loop gain and bandwidth unnecessarily. The robust $H_{\infty}$ constraint is expressed by a matrix inequality and the loop gain constraint is considered as an objective function so that genetic algorithm can be applied. Finally, a robust tracking controller can be obtained by integrating genetic algorithm with LMI approach. The proposed tracking controller design method is applied to the track-following system of an optical DVD recording drive and is evaluated through the experimental results.

• Tribology and Lubricants
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• v.36 no.2
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• pp.96-104
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• 2020

The electric vehicle industry is rapidly developing because of enforced environmental regulations, and several studies have been conducted on the multispeed transmission to improve the fuel efficiency of electric vehicles. Among these studies, research on the power density improvement of electric vehicle transmission is critical. Thus, the optimal design of the gear train is necessary to enhance transmission efficiency. In this study, an optimal design methodology for the lightweight two-speed transmission of electric vehicles is proposed. Because a multispeed transmission has many operating conditions and equality and inequality constraints, a new gear design method that combines analytical and iterative methods is applied without using complex optimization algorithms. Sets of possible design variables are generated considering the operating conditions and various design variables. The modules and face width ratios of each stage gear that satisfy the corresponding operating conditions are analytically calculated. The volume of the gear train is calculated, evaluated, and arranged using these values to determine the optimal solution for minimizing the volume, and the proposed methodology is applied to the actual model to verify its effectiveness. The design of a two-speed transmission with multiple operating conditions and constraints without complicated optimization algorithms can be optimized.