• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.1
• /
• pp.239-245
• /
• 2019

RISC-V is a free and open ISA enabling a new era of processor innovation through open standard collaboration. Born in academia and research, RISC-V ISA delivers a new level of free, extensible software and hardware freedom on architecture, paving the way for the next 50 years of computing design and innovation. In this paper, according to the emergence of RISC-V architecture, we describe the RISC-V processor instruction set constituted by arithmetic logic, memory, branch, control, status register, environment call and break point instructions. Using ModelSim and Quartus-II, 38 instructions of RISC-V has been successfully simulated and synthesized.

• Transactions of the Korean hydrogen and new energy society
• /
• v.30 no.2
• /
• pp.155-162
• /
• 2019

The energy management technology for an independent fuel cell-battery hybrid system is developed for a household usage. To develop an efficient energy management technology, a simulation model is first developed. After the model is verified with experimental results, three energy management schemes are developed. Three control techniques are a fuzzy logic control (FLC), a state machine control (SMC), and a hybrid method of FLC and SMC. As the fuel cell-battery hybrid system is used for a house, battery state of charge (SOC) regulation is the most important factor for an energy management because SOC should be kept constant every day for continuous usage. Three management schemes are compared to see SOC, power split, and fuel cell power variations effects. Experimental results are also presented and the most favorable strategy is the state machine combined fuzzy control method.

• Journal of IKEEE
• /
• v.24 no.4
• /
• pp.1034-1038
• /
• 2020

In order to effectively process target recognition using radar, accurate signal information for the target is required. However, such a target signal is usually mixed with noise, and this part of the study is continuously carried out. Especially, image processing, target signal processing and target recognition for the target are examples. Since the field of target recognition is important from a military point of view, this paper carried out research on target recognition of aircraft using a tree-structured fuzzy neural networks. Fuzzy neural networks are learned by using reflected signal data for an aircraft to optimize the model, and then test data for the target are used for the optimized model to perform an experiment on target recognition. The effectiveness of the proposed method is verified by the simulation results.

• Advances in concrete construction
• /
• v.11 no.1
• /
• pp.1-9
• /
• 2021

This article discusses the issue of optimizing controller design issues, in which the artificial intelligence (AI) evolutionary bat (EB) optimization algorithm is combined with the fuzzy controller in the practical application of the building. The controller of the system design includes different sub-parts such as system initial condition parameters, EB optimal algorithm, fuzzy controller, stability analysis and sensor actuator. The advantage of the design is that for continuous systems with polytypic uncertainties, the integrated H2/H∞ robust output strategy with modified criterion is derived by asymptotically adjusting design parameters. Numerical verification of the time domain and the frequency domain shows that the novel system design provides precise prediction and control of the structural displacement response, which is necessary for the active control structure in the fuzzy model. Due to genetic algorithm (GA), we use a hierarchical conditions of the Hurwitz matrix test technique and the limits of average performance, Hierarchical Fitness Function Structure (HFFS). The dynamic fuzzy controller proposed in this paper is used to find the optimal control force required for active nonlinear control of building structures. This method has achieved successful results in closed system design from the example.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.27 no.4
• /
• pp.297-304
• /
• 2022

This study compares the performance of artificial intelligence (AI)-based maximum power point tracking (MPPT) methods under partial shading conditions in a photovoltaic generation system. Although many studies on AI-based MPPT have been conducted, few studies comparing the tracking performance of various AI-based global MPPT methods seem to exist in the literature. Therefore, this study compares four representative AI-based global MPPT methods including fuzzy logic control (FLC), particle swarm optimization (PSO), grey wolf optimization (GWO), and genetic algorithm (GA). Each method is theoretically analyzed in detail and compared through simulation studies with MATLAB/Simulink under the same conditions. Based on the results of performance comparison, PSO, GWO, and GA successfully tracked the global maximum power point. In particular, the tracking speed of GA was the fastest among the investigated methods under the given conditions.

• International conference on construction engineering and project management
• /
• 2013.01a
• /
• pp.304-307
• /
• 2013

Various programs have been developed to predict the energy consumption of a building as a result of recent increased social interest in the environmental friendliness of construction as measured by energy efficiency. The goal of environmental-friendliness, which is achieved by predicting the energy consumption of a building, can be realized in the design stage by applying a variety of technologies, planning factors and planning systems. However, most energy analyzing engines are only suitable for use in the advanced stages of design because of the large amount of design information that must be entered. Thus, because the simulation programs currently used are not suitable for use in the early stages of design, this study suggests a prediction logic that provides an overview of the energy consumption of a building according to its size, scope, and purpose by analyzing statistics collected by government agencies.

• Steel and Composite Structures
• /
• v.49 no.4
• /
• pp.407-417
• /
• 2023

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. 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. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• Journal of Energy Engineering
• /
• v.25 no.1
• /
• pp.113-121
• /
• 2016

Polymer electrolyte membrane fuel cell(PEMFC) requires cooling system to maintain the proper operating temperature(about $65^{\circ}C{\sim}75^{\circ}C$) because the efficiency and power are affected by operating temperature. In order to retain the operating temperature of PEMFC, cooling system and coolant control logic are needed. Hardware-in-the-loop simulation(HILS) is one of effective methods to study and evaluate control algorithm. In this paper, the HILS system was designed to study the coolant control algorithm. The models of HILS system consisted of PEMFC, heat exchanger, and external environment associated with temperature. The hardwares in HILS system are 3-way valves, pumps, and a heat exchanger. The priority control and the control target temperature were investigated to improve the control performance using HILS. The 3-way valve in $1^{st}$ cooling circuit was selected as priority control target. The under limit value of $2^{nd}$ 3-way valve set as a function of PEMFC power and $2^{nd}$ circuit coolant temperature to correct temperature control performance. As a result, the temperature of PEMFC is stably controlled.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.38 no.12
• /
• pp.1217-1222
• /
• 2010

This paper describes the Model-Based Development(MBD) process behind the flight control software of a close-range unmanned aerial vehicle(KUS-9). An integrated development environment was created using a commercial tool(MATLAB $Simulink^{(R)}$), which was utilized to design models for linear/nonlinear simulation, flight control law, operational logic and HILS(Hardware In the Loop Simulation) system. Software requirements were validated through flight simulations and peer reviews during the design process, whereas the models were verified through the application of a DO-178B verification tool. The integrity of automatically generated C code was verified by using a separate S/W testing tool. The finished software product was embedded on two different types of hardware and real-time operating system(uC/OS-II, VxWorks) to perform HILS and flight tests. The key findings of this study are that MBD Technology enables the development of a reusable and an extensible software product and auto-code generation technology allows the production of a highly reliable flight control software under a compressed time schedule.

• Journal of IKEEE
• /
• v.15 no.4
• /
• pp.354-362
• /
• 2011

One of the unsolved problems in Artificial Neural Networks is related to the capacity of a neural network. This paper presents a CoreNet which has a multi-leveled input and a multi-leveled output as a 2-layered artificial neural network. I have suggested an equation for calculating the capacity of the CoreNet, which has a p-leveled input and a q-leveled output, as $a_{p,q}=\frac{1}{2}p(p-1)q^2-\frac{1}{2}(p-2)(3p-1)q+(p-1)(p-2)$. With an odd value of p and an even value of q, (p-1)(p-2)(q-2)/2 needs to be subtracted further from the above equation. The simulation model 1(3)-1(6) has 3 levels of an input and 6 levels of an output with no hidden layer. The simulation result of this model gives, out of 216 possible functions, 80 convergences for the number of implementable function using the cot(x) input leveling method. I have also shown that, from the simulation result, the two diverged functions become implementable by precalculating the weight values. The simulation result and the precalculation of the weight values give the same result as the above equation in the total number of implementable functions.