• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.245-246
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• 2008

The Correlation FXLMS (Co-FXLMS) algorithm was developed to improve the control performance. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Modified Co-FXLMS is presented in comparison with that of the CO-FXLMS algorithm. Simulation results show that active noise control using Modified Co-FXLMS is effective to control performance of algorithm and prevent divergence.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.191-200
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• 2022

Constrained Application Protocol (CoAP) is a standardized protocol by the Internet Engineering Task Force (IETF) for the Internet of things (IoT). IoT devices have limited computation power, memory, and connectivity capabilities. One of the significant problems in IoT networks is congestion control. The CoAP standard has an exponential backoff congestion control mechanism, which may not be adequate for all IoT applications. Each IoT application would have different characteristics, requiring a novel algorithm to handle congestion in the IoT network. Unnecessary retransmissions, and packet collisions, caused due to lossy links and higher packet error rates, lead to congestion in the IoT network. This paper presents an adaptive congestion control protocol for CoAP, Adaptive Congestion Control with a Backoff algorithm (ACCB). AACB is an extension to our earlier protocol AdCoCoA. The proposed algorithm estimates RTT, RTTVAR, and RTO using dynamic factors instead of fixed values. Also, the backoff mechanism has dynamic factors to estimate the RTO value on retransmissions. This dynamic adaptation helps to improve CoAP performance and reduce retransmissions. The results show ACCB has significantly higher goodput (49.5%, 436.5%, 312.7%), packet delivery ratio (10.1%, 56%, 23.3%), and transmission rate (37.7%, 265%, 175.3%); compare to CoAP, CoCoA+ and AdCoCoA respectively in linear scenario. The results show ACCB has significantly higher goodput (60.5%, 482%,202.1%), packet delivery ratio (7.6%, 60.6%, 26%), and transmission rate (40.9%, 284%, 146.45%); compare to CoAP, CoCoA+ and AdCoCoA respectively in random walk scenario. ACCB has similar retransmission index compare to CoAp, CoCoA+ and AdCoCoA respectively in both the scenarios.

• Smart Structures and Systems
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• v.23 no.1
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• pp.1-14
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• 2019

Control algorithms are the most important aspects in successful control of structures against earthquakes. In recent years, intelligent control methods rather than classical control methods have been more considered by researchers, due to some specific capabilities such as handling nonlinear and complex systems, adaptability, and robustness to errors and uncertainties. However, due to lack of learning ability of fuzzy controller, it is used in combination with a genetic algorithm, which in turn suffers from some problems like premature convergence around an incorrect target. Therefore in this research, the introduction and design of the Fuzzy Cooperative Coevolution (Fuzzy CoCo) controller and Adaptive Neural-Fuzzy Inference System (ANFIS) have been innovatively presented for semi-active seismic control. In this research, in order to improve the seismic behavior of structures, a semi-active control of building using Magneto Rheological (MR) damper is proposed to determine input voltage of Magneto Rheological (MR) dampers using ANFIS and Fuzzy CoCo. Genetic Algorithm (GA) is used to optimize the performance of controllers. In this paper, the design of controllers is based on the reduction of the Park-Ang damage index. In order to assess the effectiveness of the designed control system, its function is numerically studied on a 9-story benchmark building, and is compared to those of a Wavelet Neural Network (WNN), fuzzy logic controller optimized by genetic algorithm (GAFLC), Linear Quadratic Gaussian (LQG) and Clipped Optimal Control (COC) systems in terms of seismic performance. The results showed desirable performance of the ANFIS and Fuzzy CoCo controllers in considerably reducing the structure responses under different earthquakes; for instance ANFIS and Fuzzy CoCo controllers showed respectively 38 and 46% reductions in peak inter-story drift ($J_1$) compared to the LQG controller; 30 and 39% reductions in $J_1$ compared to the COC controller and 3 and 16% reductions in $J_1$ compared to the GAFLC controller. When compared to other controllers, one can conclude that Fuzzy CoCo controller performs better.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.4
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• pp.543-552
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• 1996

The goal of this paper is to developed a DSP based power analyzing and control system by 3-Dimensional (3-D) space current co-ordinates. A developed system is made up of 486-PC and DSP (Digital Signal Processor) board, Active Power Filter, Non-linear thyristor load, and Power analyzing and control program for Windows. Power is analyzed using signal processing techniques based on the correlation between voltage and current waveforms. Since power analysis algorithm is performed by DSP, power analysis is achieved in real-time even under highly dynamic nonlinear loading conditions. Combining control algorithm with power analysis algorithm is performed by DSP, power analysis is achieved in real-time even under highly dynamic nonlinear loading conditions. Combining control algorithm with power analysis algorithm, flexibility of the proposed system which has both power analysis mode and control mode, is greatly enhanced. Non-active power generated while speed of induction motor is controlled by modulating firing angle of thyristor converter, is compensated by Active Power Filter for verifying a developed system. Power analysis results, before/after compensation, are numerically obtained and evaluated. From these results, various graphic screens for time/frequency/3-D current co-ordinate system are displayed on PC. By real-time analysis of power using a developed system, power quality is evaluated, and compared with that of conventional current co-ordinate system. (author). refs., figs. tabs.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.36 no.5
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• pp.187-194
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• 2020

This study presents the energy-saving sequential control algorithm to handle indoor CO₂ and PM2.5 for the improvement of the air quality of school classrooms. To solve indoor air quality (IAQ) problems, air cleaning and ventilation systems are mainly used for school classrooms. Although air cleaning is able to collect PM2.5, it is difficult to remove harmful gas substances. The ventilation system is suitable to tackle CO and CO₂, the volume ventilation, however, is relatively small. In this paper, to remove CO₂ and PM2.5, the pollutant balance equation for improving indoor air quality is reviewed. The sequential control algorithm of the ventilation and air cleaning system with four levels of criteria is introduced for the effective removal of pollutants. The proposed sequential control algorithm confirms that indoor CO₂ and PM2.5 can be properly controlled below the standard value. In addition, the sequential operation of air cleaning and ventilation systems has shown significant improvement in IAQ compared to the independent ventilation system operation. Particularly, such systems are efficient when outdoor PM2.5 is high.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.341-346
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• 2004

Nowadays, versatile robots are developed around the world. Novel algorithms are needed for controlling such robots. A 2-Layer fuzzy controller can deal with many inputs as well as many outputs, and its overall structure is much simpler than that of a general fuzzy controller. The main problem encountered in fuzzy control is the design of the fuzzy controller. In this paper, the fuzzy controller is designed by the schema co-evolutionary algorithm. This algorithm can quickly and easily find a global solution. Therefore, the schema co-evolutionary algorithm is used to design a 2-layer fuzzy controller in this study. We apply it to a mobile robot and verify the efficacy of the 2-layer fuzzy controller and the schema co-evolutionary algorithm through the experiments.

• Proceedings of the SAREK Conference
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• 2005.11a
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• pp.480-485
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• 2005

In the respect of the environmental protection viewpoint, the $CO_2$ may be regarded as one of the most attractive alternative refrigerants for an automotive air-conditioning system. Control methods for a $CO_2$ system should be newly developed, because properties of $CO_2$ are different compared with those of classical refrigerants. Especially, high-side pressure of a $CO_2$ system should be controlled for the effective operation of the system. In this study, intelligent control algorithms for a $CO_2$ system were developed ‘ These are a high-side pressure control algorithm and an indoor air temperature control algorithm. These algorithms were analysised by using dynamic models of a $CO_2$ system.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.2 no.1
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• pp.95-110
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• 1998

Evolutionary Algorithms (EAs) are population-based optimization methods based on the principle of Darwinian natural selection. The representative methodology in EAs is genetic algorithm (GA) proposed by J. H. Holland, and the theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. In the meaning of these foundational concepts, simple genetic algorithm (SGA) allocate more trials to the schemata whose average fitness remains above average. 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 co-evolve in contrast with traditional single population evolutionary algorithm. In this paper we show why the co-evolutionary algorithm works better than SGA in terms of an extended schema theorem. And predator-prey co-evolution and symbiotic co-evolution, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. And the experimental results show a co-evolutionary algorithm works well in optimization problems even though in deceptive functions.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.393-398
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• 2008

In order to protect the environment from the refrigerant pollution, the $CO_2$ may be regarded as one of the most attractive alternative refrigerants for an automotive air-conditioning system. Control methods for a $CO_2$ system should be different because of the unique property of a $CO_2$ as a refrigerant. Especially, the high-side pressure of a $CO_2$ system should be controlled for the efficient operation. The high-side pressure algorithm being composed of the pressure setpoint algorithm and the pressure setpoint reset algorithm was developed. The pressure setpoint algorithm, by using a least square method, was developed. The pressure setpoint reset algorithm, by using a fuzzy logic and by using a proportional logic, was also developed and compared. Simulation results showed that a proportional logic was more practical than a fuzzy logic for the pressure setpoint reset algorithm.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.244-245
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• 2013

This paper proposes a control algorithm for permanent magnet synchronous generator with a back-to-back three-level neutral-point clamped voltage source converter in a medium-voltage offshore wind power system under unbalanced grid conditions. The proposed control algorithm particularly compensates for the unbalanced grid voltage at the point of common coupling in a collector bus of offshore wind power system. This control algorithm has been formulated based on the symmetrical components in positive and negative rotating synchronous reference frames under generalized unbalanced operating conditions. Instantaneous active and reactive power are described in terms of symmetrical components of measured grid input voltages and currents. Negative sequential component of ac input current is injected to the point of common coupling in the proposed control strategy. The amplitude of negative sequential component is calculated to minimize the negative sequential component of grid voltage under the limitation of current capability in a voltage source converter. The proposed control algorithm makes it possible to provide a balanced voltage at the point of common coupling resulting in the generated power of high quality from offshore wind power system under unbalanced network conditions.