• Journal of Power Electronics
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• v.15 no.5
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• pp.1329-1337
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• 2015

By placing distributed generation power sources beside a big nonlinear load, these sources can be used as a power quality enhancer, while injecting some active power to the network. In this paper, a new scheme to use the distributed generation power source in both operation modes is presented. In this scheme, a fuzzy controller is added to adjust the optimal set point of inverter between compensating mode and maximum active power injection mode, which works based on the harmonic content of the nonlinear load. As the high order current harmonics can be easily rejected using passive filters, the DG is used to compensate the low order harmonics of the load current. Multilevel transformerless cascade inverters are preferred in such utilization, as they have more flexibility in current/voltage waveform. The proposed scheme is simulated in MATLAB/SIMULINK to evaluate the circuit performance. Then, a 1kw single phase prototype of the circuit is used for experimental evaluation of the paper. Both simulative and experimental results prove that such a circuit can inject a well-controlled current with desired harmonics and THD, while having a smaller switching frequency and better efficiency, related to previous 3-phase inverter schemes in the literature.

• Structural Engineering and Mechanics
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• v.89 no.2
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• pp.213-223
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• 2024

This paper proposes a composite design of fuzzy adaptive control scheme based on TMD RC structural system and the gain of two-dimensional fuzzy control is controlled by parameters. Monitoring and learning in LMI then produces performance indicators with a weighting matrix as a function of cost. It allows to control the trade-off between the two efficiencies by adjusting the appropriate weighting matrix. The two-dimensional Boost control model is equivalent to the LMI-constrained multi-objective optimization problem under dual performance criteria. By using the proposed intelligent control model, the fuzzy nonlinear criterion is satisfied. Therefore, the data connection can be further extended. Evaluation of controller performance the proposed controller is compared with other control techniques. This ensures good performance of the control routines used for position and trajectory control in the presence of model uncertainties and external influences. Quantitative verification of the effectiveness of monitoring and control. The purpose of this article is to ensure access to adequate, safe and affordable housing and basic services. Therefore, it is assumed that this goal will be achieved in the near future through the continuous development of artificial intelligence and control theory.

• Steel and Composite Structures
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• v.51 no.5
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• pp.473-485
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• 2024

This paper proposes a composite form of fuzzy adaptive control plan based on a robust observer. The fuzzy 2D control gains are regulated by the parameters in the LMIs. Then, control and learning performance indices with weight matrices are constructed as the cost functions, which allows the regulation of the trade-off between the two performance by setting appropriate weight matrices. The design of 2D control gains is equivalent to the LMIs-constrained multi-objective optimization problem under dual performance indices. By using this proposed smart tracking design via fuzzy nonlinear criterion, the data link can be further extended. To evaluate the performance of the controller, the proposed controller was compared with other control technologies. This ensures the execution of the control program used to track position and trajectory in the presence of great model uncertainty and external disturbances. The performance of monitoring and control is verified by quantitative analysis. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1400-1407
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• 2015

In the paper, we suggest bettered EHMECS(Enhanced Hybrid Multi Electrical Cupping System) to regulate automatically vacuum pressure using many cupping cup at once. We controlled accurately the pressure using S-PI control technique in pump motor to input the air inside cupping cup. S-PI control compared constant velocity, load and velocity variance between existing PI and FLC(Fuzzy Logic Control). The stabilization time of suggested S-PI control improve 20% of existing PI and 8% of FLC. The error constant of normal condition improved 71% of existing PI and 62% of FLC in steady speed and 80% of existing PI and 67% of FLC in load change. Also the error constant about velocity variance improve 45% of PI control. It is prove the suggested S-PI control technique. When use long time vacuum pressure of cupping cup regulated the suggested S-PI control technique, can loosen knotted muscles.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.4 s.44
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• pp.55-66
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• 2005

The effectiveness of fuzzy supervisory control technique for the control of seismic responses of smart base isolation system is investigated in this study. To this end, first generation base isolated building benchmark problem is employed for the numerical simulation. The benchmark structure under consideration is an eight-story base isolated building having irregular plan and is equipped with low-damping elastometric bearings and magnetorheological (MR) dampers for seismic protection. Lower level fuzzy logic controllers (FLC) for far-fault or near-fault earthquakes are developed in order to effectively control base isolated building using multi-objective genetic algorithm. Four objectives, i.e. reduction of peak structural acceleration, peak base drift, RMS structural acceleration and RMS base drift, are used in multi-objective optimization process. When earthquakes are applied to benchmark building, each of low level FLCs provides different command voltage and supervisory fuzzy controller combines two command voltages io one based on fuzzy inference system in real time. Results from the numerical simulations demonstrate that base drift as well as superstructure responses can be effectively reduced using the proposed supervisory fuzzy control technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.219-224
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• 2016

The vibration control performance of a semi-active damper connected to adjacent buildings subjected to seismic loads was investigated. The MR damper was used as a semi-active control device. A fuzzy logic control algorithm was used for effective control of the adjacent buildings connected to the MR damper. In the buildings control coupled with a MR damper, the response reduction of one building results in an increase in the response in another building. Because of these conflict characteristics, multi-objective optimization is required. Therefore, a fuzzy logic control algorithm for the control of a MR damper was optimized using a multi-objective genetic algorithm. Based on numerical analyses, the semi-active fuzzy control of MR damper for adjacent coupled buildings can provide good control performance.

• Journal of Korean Association for Spatial Structures
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• v.14 no.2
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• pp.87-94
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• 2014

In this study, a smart isolation platform has been developed for control of microvibration of high-technology facilities, such as semi-conductor plants and TFT-LCD plants. Previously, microvibration control performance of a smart base isolation system has been investigated. This study compared microvibration control performance of a smart isolation platform with that of conventional base isolation and fixed base. For this purpose, train-induced ground acceleration is used for time history analysis. An MR damper was used to compose a smart isolation platform. A fuzzy logic controller was used as a control algorithm and it was optimized by a multi-objective genetic algorithm. Numerical analysis shows that a smart isolation platform can effectively control microvibration of a high-technology facility subjected to train-induced excitation compared with other models.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.150-153
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• 2007

The intent of this paper is to describe a neural network structure called multi dynamic neural network(MDNN), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the MDNN, are described. Computer simulations are demonstrate the effectiveness of the proposed learning using the MDNN.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.368-373
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• 2000

In this paper, a control algorthm suitable for multi-objective control is proposed based on the orthogonal array which is normally used in statics and industrial engineering. And a newly defined Nthcertainty factor is suggested, which can effectively exclude the less confident rule. The Nth-certainty factor is defined by the F-values of the ANOVA(analysis of variance) table. It is shown that the algorithm can be successfully adopted to the design of controller for an active magnetic bearing system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.63-68
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• 2000

In this paper, a control algorithm suitable for multi-objective control problems is proposed based on the orthogonal array which is normally used in statistics and industrial engineering. And a newly defined Nth-certainty factor is suggested, which can effectively exclude the less confident rules. The Nth-certainty factor is defined by the F-values of the ANOVA(analysis of variance) table. It is shown that the algorithm can be successfully adopted to the design of controller for an active magnetic bearing system.