• Journal of Mechanical Science and Technology
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• 제19권9호
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• pp.1720-1730
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• 2005

Automatic guided vehicle in the factory has an important role to advance the flexible manufacturing system. In this paper, we propose a novel object-transportation control algorithm of cooperative AGV systems to apply decentralized control to multiple AGV systems. Each AGV system is under nonholonomic constraints and conveys a common object-transportation in a horizontal plain. Moreover it is shown that cooperative robot systems ensure stability and the velocities of augmented systems convergence to a scaled multiple of each desired velocity field for cooperative AGV systems. Finally, the application of proposed virtual passivity-based decentralized control algorithm via system augmentation is applied to trace a circle. Finally, the simulation and experimental results for the object-transportation by two AGV systems illustrates the validity of the proposed virtual-passivity decentralized control algorithm.

• ETRI Journal
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• 제43권1호
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• pp.17-30
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• 2021

At present, multiple input multiple output radars offer accurate target detection and better target parameter estimation with higher resolution in high-speed wireless communication systems. This study focuses primarily on power allocation to improve the performance of radars owing to the sparsity of targets in the spatial velocity domain. First, the radars are clustered using the kernel fuzzy C-means algorithm. Next, cooperative and noncooperative clusters are extracted based on the distance measured using the kernel fuzzy C-means algorithm. The power is allocated to cooperative clusters using the Pareto optimality particle swarm optimization algorithm. In addition, the Nash equilibrium particle swarm optimization algorithm is used for allocating power in the noncooperative clusters. The process of allocating power to cooperative and noncooperative clusters reduces the overall transmission power of the radars. In the experimental section, the proposed method obtained the power consumption of 0.014 to 0.0119 at K = 2, M = 3 and K = 2, M = 3, which is better compared to the existing methodologies-generalized Nash game and cooperative and noncooperative game theory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권4호
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• pp.1075-1089
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• 2024

In this paper, the optimizations of multi-hop cooperative molecular communication (CMC) system in cylindrical anomalous-diffusive channel in three-dimensional enviroment are investigated. First, we derive the performance of bit error probability (BEP) of CMC system under decode-and-forward relay strategy. Then for achieving minimum average BEP, the optimization variables are detection thresholds at cooperative nodes and destination node, and the corresponding optimization problem is formulated. Furthermore, we use conjugate gradient (CG) algorithm to solve this optimization problem to search optimal detection thresholds. The numerical results show the optimal detection thresholds can be obtained by CG algorithm, which has good convergence behaviors with fewer iterations to achieve minimized average BEP compared with gradient decent algorithm and Bisection method which are used in molecular communication.

• 한국항행학회논문지
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• 제12권6호
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• pp.619-626
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• 2008

본 논문에서는 무선센서네트워크에서 미지의 노드 위치를 추정하기 위하여 VRN을 이용한 수신신호 세기 기반의 협력 위치 추정 알고리즘을 제안하였다. 제안한 위치추정 시스템은 모든 노드들을 모니터링하고 중첩 영역의 반복적 이용과 협력적 위치추정을 통해 BN의 좌표를 추정하였다. 실험결과 협력위치 추정시 반복횟수가 증가함에 따라 BN의 존재가능 영역이 줄어듦을 확인하였으며, RN의 수가 적을수록 최소 4회 이상의 반복적인 위치추정 횟수가 확보되어야만 BN의 존재가능 영역이 현저히 협소해짐을 보였다. 또한 위치추정 오차거리는 RN의 수가 4개인 경우에도 기존의 위치추정 알고리즘에 비해 약 71.6%의 성능이 향상되었다. 따라서 본 논문에서 제안한 VRN을 활용한 위치추정 알고리즘이 기존의 RSS기반의 위치추정 알고리즘에 비해 우수한 위추정 성능이 나타남을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.1053-1056
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• 2009

본 논문에서는 실내외 환경에서 상호 정보를 바탕으로 대상의 위치를 추적할 수 있는 영역축소 기법을 이용한 협력 위치추정 알고리즘을 제안하였다. 제안한 알고리즘은 고정노드의 수가 제한된 환경에서 미지의 노드 위치 정보를 활용한 상호 협력적인 위치추정 방식으로 본 연구에서는 3단계에 걸쳐 노드의 위치를 추정하였다. 실험 결과 동일한 개수의 RN일 때 BN의 수가 증가할수록 본 논문에서 제안한 영역축소 방법을 이용한 협력위치추정의 정밀도가 향상됨을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.4873-4888
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• 2018

A joint blind parameter estimation algorithm based on minimum channel stability function aimed at the non-cooperative high-order modulated paired carrier multiple access (PCMA) signals is proposed. The method, which uses hierarchical search to estimate time delay, amplitude and frequency offset and the estimation of phase offset, including finite ambiguity, is presented simultaneously based on the derivation of the channel stability function. In this work, the structure of hierarchical iterative processing is used to enhance the performance of the algorithm, and the improved algorithm is used to reduce complexity. Compared with existing data-aided algorithms, this algorithm does not require a priori information. Therefore, it has significant advantage in solving the problem of blind parameter estimation of non-cooperative high-order modulated PCMA signals. Simulation results show the performance of the proposed algorithm is similar to the modified Cramer-Rao bound (MCRB) when the signal-to-noise ratio is larger than 16 dB. The simulation results also verify the practicality of the proposed algorithm.

• International Journal of Aeronautical and Space Sciences
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• 제15권3호
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• pp.281-292
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• 2014

We propose a novel cooperative guidance law design method based on the finite time disturbance observer (FTDO) for multiple near space interceptors (NSIs) with impact time control. Initially, we construct a cooperative guidance model with head pursuit, and employ the FTDO to estimate the system disturbance caused by target maneuvering. We subsequently separate the cooperative guidance process into two stages, and develop the normal acceleration command based on the super-twisting algorithm (STA) and disturbance estimated value, to ensure the convergence of the relative distance. Then, we also design the acceleration command along the line-of-sight (LOS), based on the nonsingular fast terminal sliding mode (NFTSM) control, to ensure that all the NSIs simultaneously hit the target. Furthermore, we prove the stability of the closed-loop guidance system, based on the Lyapunov theory. Finally, our simulation results of a three-to-one interception scenario show that the proposed cooperative guidance scheme makes all the NSIs hit the target at the same time.

• International Journal of Control, Automation, and Systems
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• 제6권2호
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• pp.282-287
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• 2008

In distributed mobile robot systems, autonomous robots accomplish complicated tasks through intelligent cooperation with each other. This paper presents behavior learning and online distributed evolution for cooperative behavior of a group of autonomous robots. Learning and evolution capabilities are essential for a group of autonomous robots to adapt to unstructured environments. Behavior learning finds an optimal state-action mapping of a robot for a given operating condition. In behavior learning, a Q-learning algorithm is modified to handle delayed rewards in the distributed robot systems. A group of robots implements cooperative behaviors through communication with other robots. Individual robots improve the state-action mapping through online evolution with the crossover operator based on the Q-values and their update frequencies. A cooperative material search problem demonstrated the effectiveness of the proposed behavior learning and online distributed evolution method for implementing cooperative behavior of a group of autonomous mobile robots.

• 경영과학
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• 제29권2호
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• pp.21-34
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• 2012

This paper addresses a network design problem in a supply chain system that involves locating both plants and distribution centers, and determining the best strategy for distributing products from the suppliers to the plants, from the plants to the distribution centers and from the distribution centers to the customers. This paper suggests a cooperative coevolutionary algorithm (CCEA) approach to solve the model. First, the problem is decomposed into three subproblems for each of which the chromosome population is created correspondingly. Each chromosome in each population is represented as a permutation denoting the priority. Then an algorithm generating a solution from the combined set of chromosomes from each population is suggested. Also an algorithm evaluating the performance of a solution is suggested. An experimental study is carried out. The results show that our CCEA tends to generate better solutions than the previous CCEA as the problem size gets larger and that the permutation representation for chromosome used here is better than other representation.

• 한국지능시스템학회논문지
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• 제19권3호
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• pp.432-436
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• 2009

We have developed a new optimization algorithm termed simple bacteria cooperative optimization (sBCO) based on bacteria behavior patterns [1]. In [1], we have introduced the algorithm with basic operations and showed its feasibility with some function optimization problems. Since the sBCO was the first version with only basic operations, its performance was not so good. In this paper, we adopt a new operation, rank replacement, to the sBCO for improving its performance and compare its results to those of the simple genetic algorithm (sGA) which has been well known and widely used as an optimization algorithm. It was found from the experiments with four function optimization problems that the sBCO with rank replacement was superior to the sGA. This shows that our algorithm can be a good optimization algorithm.