• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.03a
• /
• pp.77-80
• /
• 1998

The theoretical foundations of simple genetic algorithm(SGA) are the Schema Theorem and the Building Block Hypothesis. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum in GA-hard problems and deceptive problems. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and cooperate each other. In this paper we show why the co-evolutionary algorithm works better than SGA in terms of an extended schema theorem. Also the experimental results show a co-evolutionary algorithm works well in optimization problems.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.3 no.2
• /
• pp.42-52
• /
• 2000

A torque control method of a switched reluctance motor for the position control of a tank gun is presented. One of the widely used torque control scheme, torque sharing function method, is investigated and a new torque sharing function method is proposed that extends the definition region of the conventional TSF to both the positive and negative torque production regions. By using this definition, all kinds of the control inputs that consider switching on/off angle control as well as the current profiling can be described. A parametrized representation of the current profiles is proposed by using a series of B-spline functions, which reduces memory requirement and enables additional controllers. Optimal determination of the TSFs are also investigated for various control objectives. Moreover, the comparison study of each objective is presented. Since this method generalizes all of the possible control input, the current and torque profiles obtained from the optimization are the most suitable control input that satisfy the objectives.

• Journal of Magnetics
• /
• v.16 no.3
• /
• pp.268-270
• /
• 2011

This study introduces a new topology optimization scheme combing the genetic algorithm (GA) with the on/off sensitivity method for the magnetic actuator core and the armature design. The design process intended to maximize the first eigen-frequency of the armature part and the magnetic actuating force acting on the armature simultaneously. GA based optimal design was carried out to obtain the initial structure and the modified on/off sensitivity method was succeeded to accelerate the design process. Final results show tens of percent improvement in actuating force as well as the first eigen-frequency of the armature.

• Proceedings of the ESK Conference
• /
• 1994.04a
• /
• pp.124-135
• /
• 1994

A biomechanical model of lower extremity in seated postures was developed to assess muscular activities of lower extremity involved in a variety of foot pedal operations. It is found that nonlinear optimization method which has been used for modeling the articulated body segments does not predict the forces generated from biarticular muscles reasonably, so the revised nonlinear optimization scheme was employed to consider the synergistic effects of biarticular muscles in the model, assuming that the muscle forces are distributed proportionally based on their physiological cross sectional area and moment arm. The model incorporated four rigid body segments with the nine muscles to represent lower extreimity. For the model valida- tion, three male subjects performed the experiments in which EMG activities of the nine lower extremity muscles were measured. Predicted muscle forces were compared with the corresponding EMG amplitudes and it showed no statistical difference. The developed model can be used to design and to assess the pedals and foot-related equipments design.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.2
• /
• pp.134-139
• /
• 2010

In order to overcome some problems of existing anti-windup methods, this paper defines LQ (Linear Quadratic) observer and proposes a new anti-windup method using the LQ observer. LQ observer is derived by linear quadratic optimization in order to calculate controller states, which make the controller outputs equal to the plant inputs. And we propose an algorithm so that it can be implemented by a digital controller easily. The relationship between the design parameters and the anti-windup performance is shown via some numerical examples, which cover the cases with the anti-windup method using LQ observer designed and the case without it. Finally, the anti-windup performance of the proposed method is exemplified via comparison with the existing model-based conditioning scheme method[4].

• International Journal of Advanced Culture Technology
• /
• v.8 no.2
• /
• pp.260-269
• /
• 2020

The Steam Assisted Gravity Drainage (SAGD) process is an enhanced method to extract oil from bitumen which involves surface and central process facilities. This paper describes the Central Process Facilities (CPF) of SAGD and proposes several retrofit plans to the Heat Exchanger Network (HEN). In this approach, the process integration scheme is applied to estimate the energy saving in HENs, and various cases are modeled in favor of a commercial simulator. Throughout this work, a minimum approach temperature of 10℃ is assumed. The results reveal that, due to the HEN optimization using process integration, the heating and cooling duties can be reduced to 29.68MW and 1.886MW, respectively. Compared with the Husky case, all cases considered in this study indicate a potential reduction of at least 6% in total cost, including investment and operation costs.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2002.04a
• /
• pp.249-256
• /
• 2002

A new optimization procedure with approximate reanalysis module, using the staged hybrid methods with substructuring, is proposed in is study. In this procedure, displacements are calculated with two step mixed procedures. First step is to introduce the conservative approximation, which is a hybrid form of the linear and reciprocal approximation, as local approximation. In the next step, it is combined with the global approximation by reduced basis approach. The quality of reanalyzed quantities can be greatly improved through these staged hybrid approximations, specially for large changes in the design. Overall procedures are based on substructuring scheme. Several numerical examples illustrate the validity and effectiveness of the proposed methods.

• Phonetics and Speech Sciences
• /
• v.2 no.4
• /
• pp.137-143
• /
• 2010

In this paper, a speech endpoint detection algorithm is proposed. The proposed algorithm is a kind of state transition-based ones for speech detection. To reject short-duration acoustic pulses which can be considered noises, it utilizes duration information of all detected pulses. For the optimization of parameters related with pulse lengths and energy threshold to detect speech intervals, an exhaustive search scheme is adopted while speech recognition rates are used as its performance index. Experimental results show that the proposed algorithm outperforms the baseline state-based endpoint detection algorithm. At 5 dB input SNR for the beamforming input, the word recognition accuracies of its outputs were 78.5% for human voice noises and 81.1% for music noises.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.553-559
• /
• 1998

Simple Genetic Algorithm(SGA) proposed by J. H. Holland is a population-based optimization method based on the principle of the Darwinian natural selection. The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. Although GA goes well in many applications as an optimization method, still it does not guarantee the convergence to a global optimum in some problems. In designing intelligent systems, specially, since there is no deterministic solution, a heuristic trial-and error procedure is usually used to determine the systems' parameters. As an alternative scheme, therefore, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve. In this paper we review the existing co-evolutionary algorithms and propose co-evolutionary schemes designing intelligent systems according to the relation between the system's components.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.1C
• /
• pp.110-116
• /
• 2008

Maximum likelihood(ML) diretion-of-arrival(DOA) estimation is essentially optimization of multivariable nonlinear cost function. Since the final estimate is highly dependent on the initial estimate, an initialization is critical in nonlinear optimization. We propose a multi-dimensional(M-D) search scheme of uniform exhaustive search and improved exhaustive search. Improved exhaustive search is superior to uniform exhaustive search in terms of the computational complexity and the accuracy of the estimates.