• Title/Summary/Keyword: Multi-Tuning

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Phenomenological Nonlinear Gain Saturation Effect on the Noise Characteristics of a Multi-electrode DBR Laser with Continuous Frequency Tuning (연속 파장 가변시 현상론적인 비선형 이득포화효과가 다전극 DBR 레이저의 잡음특성에 미치는 영향)

  • 이석목;최원준;한일기;김회종;우덕하;김선호;이정일;감광남;박홍이
    • Korean Journal of Optics and Photonics
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    • v.6 no.2
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    • pp.135-141
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    • 1995
  • Phenomenological nonlinear gain saturation effect on the noise characteristics of a multi-electrode DBR laser, when the lasing wavelength changes continuously, is presented theoretically. Using the optical transmission line theory, noise characteristics reliant on output power are analyzed by taking into account both the spontaneous enhancement factor K due to the distribution of the spontaneous emission along the active cavity and the nonlinear gain saturation effect. Spontaneous emission rate was increased due to an increase in injected current into the passive section, which in turn lead to increase in relative intensity noise (RIN) and frequency noise. Phenomenological nonlinear gain saturation was found to have significant effect on RIN and frequency noise characteristics. However. Iinewidth was found to decrease due to a phenomenological nonlinear gain saturation effect. ffect.

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Optimum Design of Integer and Fractional-Order PID Controllers for Boost Converter Using SPEA Look-up Tables

  • Amirahmadi, Ahmadreza;Rafiei, Mohammadreza;Tehrani, Kambiz;Griva, Giovanni;Batarseh, Issa
    • Journal of Power Electronics
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    • v.15 no.1
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    • pp.160-176
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    • 2015
  • This paper presents a method of designing optimal integer- and fractional-order proportional-integral-derivative (FOPID) controllers for a boost converter to gain a set of favorable characteristics at various operating points. A Pareto-based multi-objective optimization approach called strength Pareto evolutionary algorithm (SPEA) is used to obtain fast and low overshoot start-up and dynamic responses and switching stability. The optimization approach generates a set of optimal gains called Pareto set, which corresponds to a Pareto front. The Pareto front is a set of optimal results for objective functions. These results provide designers with a trade-off look-up table, in which they can easily choose any of the optimal gains based on design requirements. The SPEA also overcomes the difficulties of tuning the FOPID controller, which is an extension to the classic integer-order PID controllers and potentially promises better results. The proposed optimized FOPID controller provides an excellent start-up response and the desired dynamic response. This paper presents a detailed comparison of the optimum integer- and the fractional-order PID controllers. Extensive simulation and experimental results prove the superiority of the proposed design methodology to achieve a wide set of desired technical goals.

Fuzzy-PID controller for motion control of CFETR multi-functional maintenance platform

  • Li, Dongyi;Lu, Kun;Cheng, Yong;Zhao, Wenlong;Yang, Songzhu;Zhang, Yu;Li, Junwei;Wu, Huapeng
    • Nuclear Engineering and Technology
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    • v.53 no.7
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    • pp.2251-2260
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    • 2021
  • The motion control of the divertor maintenance system of the China Fusion Engineering Test Reactor (CFETR) was studied in this paper, in which CFETR Multi-Functional Maintenance Platform (MFMP) was simplified as a parallel robot for the convenience of theoretical analysis. In order to design the motion controller of parallel robot, the kinematics analysis of parallel robot was carried out. After that, the dynamic modeling of the hydraulic system was built. As the large variation of heavy payload on MFMP and highly nonlinearity of the system, A Fuzzy-PID controller was built for self-tuning PID controller parameters by using Fuzzy system to achieve better performance. In order to test the feasibility of the Fuzzy-PID controller, the simulation model of the system was built in Simulink. The results have showed that Fuzzy-PID controller can significantly reduce the angular error of the moving platform and provide the stable motion for transferring the divertor.

No-Reference Image Quality Assessment based on Quality Awareness Feature and Multi-task Training

  • Lai, Lijing;Chu, Jun;Leng, Lu
    • Journal of Multimedia Information System
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    • v.9 no.2
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    • pp.75-86
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    • 2022
  • The existing image quality assessment (IQA) datasets have a small number of samples. Some methods based on transfer learning or data augmentation cannot make good use of image quality-related features. A No Reference (NR)-IQA method based on multi-task training and quality awareness is proposed. First, single or multiple distortion types and levels are imposed on the original image, and different strategies are used to augment different types of distortion datasets. With the idea of weak supervision, we use the Full Reference (FR)-IQA methods to obtain the pseudo-score label of the generated image. Then, we combine the classification information of the distortion type, level, and the information of the image quality score. The ResNet50 network is trained in the pre-train stage on the augmented dataset to obtain more quality-aware pre-training weights. Finally, the fine-tuning stage training is performed on the target IQA dataset using the quality-aware weights to predicate the final prediction score. Various experiments designed on the synthetic distortions and authentic distortions datasets (LIVE, CSIQ, TID2013, LIVEC, KonIQ-10K) prove that the proposed method can utilize the image quality-related features better than the method using only single-task training. The extracted quality-aware features improve the accuracy of the model.

A novel multi-feature model predictive control framework for seismically excited high-rise buildings

  • Katebi, Javad;Rad, Afshin Bahrami;Zand, Javad Palizvan
    • Structural Engineering and Mechanics
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    • v.83 no.4
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    • pp.537-549
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    • 2022
  • In this paper, a novel multi-feature model predictive control (MPC) framework with real-time and adaptive performances is proposed for intelligent structural control in which some drawbacks of the algorithm including, complex control rule and non-optimality, are alleviated. Hence, Linear Programming (LP) is utilized to simplify the resulted control rule. Afterward, the Whale Optimization Algorithm (WOA) is applied to the optimal and adaptive tuning of the LP weights independently at each time step. The stochastic control rule is also achieved using Kalman Filter (KF) to handle noisy measurements. The Extreme Learning Machine (ELM) is then adopted to develop a data-driven and real-time control algorithm. The efficiency of the developed algorithm is then demonstrated by numerical simulation of a twenty-story high-rise benchmark building subjected to earthquake excitations. The competency of the proposed method is proven from the aspects of optimality, stochasticity, and adaptivity compared to the KF-based MPC (KMPC) and constrained MPC (CMPC) algorithms in vibration suppression of building structures. The average value for performance indices in the near-field and far-field (El earthquakes demonstrates a reduction up to 38.3% and 32.5% compared with KMPC and CMPC, respectively.

Metaheuristic-designed systems for simultaneous simulation of thermal loads of building

  • Lin, Chang;Wang, Junsong
    • Smart Structures and Systems
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    • v.29 no.5
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    • pp.677-691
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    • 2022
  • Water cycle algorithm (WCA) has been a very effective optimization technique for complex engineering problems. This study employs the WCA for simultaneous prediction of heating load (LH) and cooling load (LC) in residential buildings. This algorithm is responsible for optimally tuning a neural network (NN). Utilizing 614 records, the behavior of the LH and LC is explored and the captured knowledge is then used to predict for 154 unanalyzed building conditions. Since the WCA is a population-based algorithm, different numbers of the searching agents were tested to find the most optimum configuration. It was observed that the best solution is discovered by 500 agents. A comparison with five newly-developed benchmark optimizers, namely equilibrium optimizer (EO), multi-tracker optimization algorithm (MTOA), slime mould algorithm (SMA), multi-verse optimizer (MVO), and electromagnetic field optimization (EFO) revealed that the WCANN predicts the desired parameters with considerably larger accuracy. Obtained root mean square errors (1.4866, 2.1296, 2.8279, 2.5727, 2.5337, and 2.3029 for the LH and 2.1767, 2.6459, 3.1821, 2.9732, 2.9616, and 2.6890 for the LC) indicated that the most reliable prediction was presented by the proposed model. The EFONN, however, provided a more time-effective solution. Lastly, an explicit predictive formula was elicited from the WCANN.

A Study on Analytical Method of Driving Characteristics of Carrier Aircraft Towing Vehicles Using Dynamic Simulation (동역학 시뮬레이션을 이용한 함재기 견인차량의 주행특성 분석 기법에 관한 연구)

  • Jaewon Oh;Sa Young Hong;Sup Hong
    • Journal of the Society of Naval Architects of Korea
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    • v.60 no.4
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    • pp.288-295
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    • 2023
  • This paper deals with the dynamic simulation method for analysis of driving characteristics of aircraft and towing vehicles (TUG) on carrier vessel in wave motions. For prompt deployment in a short period of time, optimization of the movement of carrier aircraft becomes a major issue. In this regards, strategy studies using real-time simulation technology and optimal decision-making technologies are being conducted. In the present work, the dynamic characteristics of carrier aircraft and TUG connected by towbar or towbarless mechanism were investigated by means of multi-body dynamics model. Meanwhile, for real-time simulation, Dugoff's model of tire loads calculation was adopted. Through comparative analysis it was confirmed that the similarity of results between the multi-body contact model and the tire load calculation model can be achieved by coefficients tuning.

Adaptive Predictive Control using Multiple Models, Switching and Tuning

  • Giovanini Leonardo;Ordys Andrzej W.;Grimble Michael J.
    • International Journal of Control, Automation, and Systems
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    • v.4 no.6
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    • pp.669-681
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    • 2006
  • In this work, a new method of design adaptive controllers for SISO systems based on multiple models and switching is presented. The controller selects the model from a given set, according to a switching rule based on output prediction errors. The goal is to design, at each sample instant, a predictive control law that ensures the robust stability of the closed-loop system and achieves the best performance for the current operating point. At each sample the proposed control scheme identifies a set of linear models that best characterizes the dynamics of the current operating region. Then, it carries out an automatic reconfiguration of the controller to achieve the best possible performance whilst providing a guarantee of robust closed-loop stability. The results are illustrated by simulations a nonlinear continuous and stirred tank reactor.

Performance Management and Analysis for Guaranteed End-to-End QoS Provisioning on MPLS-based Virtual Private LAN Service(VPLS)

  • Kim, Seong-Woo;Kim, Chul;Kim, Young-Tak
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.2B
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    • pp.144-156
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    • 2003
  • Internet/Intranet has been continuously enhanced by new emerging IP technologies such as differentiate service(DiffServ), IPSec(IP Security) and MPLS(Multi-protocol Label Switching) traffic engineering. According to the increased demands of various real-time multimedia services, ISP(Internet Service Provider) should provide enhanced end-to-end QoS(quality of service) and security features. Therefore, Internet and Intranet need the management functionality of sophisticated traffic engineering functions. In this paper, we design and implement the performance management functionality for the guaranteed end-to-end QoS provisioning on MPLS-based VPLS(Virtual Private LAN Service). We propose VPLS OAM(Operation, Administration and Maintenance) for efficient performance management. We focus on a scheme of QoS management and measurement of QoS parameters(such as delay, jitter, loss, etc.) using VPLS OAM functions. The proposed performance management system also supports performance tuning to enhance the provided QoS by re-adjusting the bandwidth of LSPs for VPLS. We present the experimental results of performance monitoring and analysis using a network simulator.

Automatic GA fuzzy modeling with fine tuning method

  • Son, You-Seok;Chang, Wook;Park, Jin-Bae;Joo, Young-Hoon
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.189-192
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    • 1996
  • This paper presents a systematic approach to identify a linguistic fuzzy model for a multi-input and single-output complex system. Such a model is composed of fuzzy rules, and its output is inferred by the simplified reasoning. The structure and membership function parameters for a fuzzy model are automatically and simultaneously identified by GA (Genetic Algorithm). After GA search, optimal parameters for the fuzzy model are finely tuned by a gradient method. A numerical example is provided to evaluate the feasibility of the proposed approach. Comparison shows that the suggested approach can produce the linguistic fuzzy model with higher accuracy and a smaller number of rules than the ones achieved previously in other methods.

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