• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.111-121
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• 2024

Recently, thanks to the development of artificial intelligence technologies such as image recognition, research on unmanned aerial vehicles is being actively conducted. In particular, related research is increasing in the field of military drones, which costs a lot to foster professional pilot personnel, and one of them is the study of an intelligent framework for autonomous mission performance of reconnaissance drones. In this study, we tried to design an intelligent framework for unmanned aerial vehicles using the methodology of designing an intelligent framework for service robots. For the autonomous mission performance of unmanned aerial vehicles, the intelligent framework and unmanned aerial vehicle module must be smoothly linked. However, it was difficult to provide interworking for drones using periodic message protocols with model-based interfaces of intelligent frameworks for existing service robots. First, the message model lacked expressive power for periodic message protocols, followed by the problem that interoperability of asynchronous data exchange methods of periodic message protocols and intelligent frameworks was not provided. To solve this problem, this paper proposes a message model extension method for message periodic description to secure the model's expressive power for the periodic message model, and proposes periodic and asynchronous data exchange methods using the extended model to provide interoperability of different data exchange methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.262-269
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• 2016

In this paper, we propose a novel dynamical love model of Romeo and Juliet, which has an external force with a fuzzy membership function. The external force used in the model has the characteristics of a Gaussian function. The chaotic behavior in the model is demonstrated using time series and phase portraits.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.23-27
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• 2000

In this paper, we propose an emotional evaluation model based on information fusion. This model can transform the physical features of a color pattern to the emotional features. Our proposed model consists of the fuzzy logic system and neural network model. The evaluation values produced by them were fused. The model shows comparable performances to the neural network and fuzzy logic system for the approximation of the nonlinear transforms. We believe the evaluated results of a color pattern can be used to the emotion-based color image retrievals.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.129-132
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• 2001

In this paper, in order to control uncertain missile autopilot, an adaptive fuzzy control(AEC) scheme via parallel distributed compensation(PDC) is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy model. Moreover adaptive law is designed so that the plant output tracks the stable reference model(SRM), From the simulations results, we can conclude that the suggested scheme can effectively solve the control problems of uncertain missile systems based on T-S fuzzy model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.64-71
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• 2016

This paper proposes nonlinear behavior in a love model for Romeo and Juliet with an external force of discontinuous time. We investigated the periodic motion and chaotic behavior in the love model by using time series and phase portraits with respect to some variable and fixed parameters. The computer simulation results confirmed that the proposed love model with an external force of discontinuous time shows periodic motion and chaotic behavior with respect to parameter variation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.302-309
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• 2005

We have studied a model and application that evolves the behavioral knowledge of a virtual robot. The knowledge is represented in classification rules and a neural network, and is learned by a genetic algorithm. The model consists of a virtual robot with behavior knowledge, an environment that it moves in, and an evolution performer that includes a genetic algorithm. We have also applied our model to an environment where the robots gather food into a nest. When comparing our model with the conventional method on various test cases, our model showed superior overall learning.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.233-242
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• 1995

In this paper, we introduce the identification model of dynamic system using the neural networks, We propose two identification models. The output of the parallel identification model is a linear combination of its past values as well as those of the input. The series-parallel model is a linear combination of the past values in the input and output of the plant. To generate stable adaptive laws, we prove that the series-parallel model is found to be proferable.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.333-334
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• 2006

A novel mathematical modeling in web transport systems for Continuous Annealing Processes (CAP) is proposed. Despite of thermal and weight effects in dynamics of web transport systems, the conventional mathematical model does not consider those effects. Disregard of these effects causes the low manufacturing quality of webs in CAP. In order to improve the manufacturing quality of webs in CAP, moreover, precise tension control is required based on the mathematical model. Therefore, an advanced mathematical model considering thermal and weight effects in CAP should be established. The effectiveness of a novel mathematical model is evaluated by comparing the performances of the PI tension control system based on the proposed mathematical model with that based on the conventional one through the computer simulation.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1821-1830
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• 2018

With the wide application of intelligent household appliances, the optimization of electricity behavior has become an important component of home-based intelligent electricity. In this study, a multi-objective optimization model in an intelligent electricity environment is proposed based on economy and comfort. Firstly, the domestic consumer's load characteristics are analyzed, and the operating constraints of interruptible and transferable electrical appliances are defined. Then, constraints such as household electrical load, electricity habits, the correlation minimization electricity expenditure model of household appliances, and the comfort model of electricity use are integrated into multi-objective optimization. Finally, a continuous search multi-objective particle swarm algorithm is proposed to solve the optimization problem. The analysis of the corresponding example shows that the multi-objective optimization model can effectively reduce electricity costs and improve electricity use comfort.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1278-1282
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• 2003

A new interacting multiple model (IMM) method using intelligent input estimation (IIE) is proposed to track a maneuvering target. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown acceleration input by a fuzzy system using the relation between maneuvering filter residual and non-maneuvering one. The genetic algorithm (GA) is utilized to optimize a fuzzy system for a sub-model within a fixed range of acceleration input. Then, multiple models are composed of these fuzzy systems, which are optimized for different ranges of acceleration input. In computer simulation for an incoming ballistic missile, the tracking performance of the proposed method is compared with those of the input estimation (IE) technique and the adaptive interacting multiple model (AIMM) method.