• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.93-101
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• 2022

Bioheavy oil, which is expanding its range of use as an alternative fuel to reduce environmental pollutant emissions, has a lot of difficulty in combustion due to its low emission of pollutants such as nitrogen oxide (NOx) and sulfur oxide (SOx), while its low dissipation and high oxygen content in fuel. many studies have been conducted on change in characteristics by mixing rate combustion characteristics and combustion reactions, but there have been no specific and effective studies on the composition of control system, optimization of control, development of logic for mixing and burning, minimizing environmental pollutantants discharge. In this study, we intend to consider systemmatic and empirical considerations on the composition, logic development, solve the problem of manual switching of bioler master due to excessive oxygen content and tuning of the control system for optimal combustion of bioheavy oil.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.71-80
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• 2013

According to design specifications for structural safety, a bridge in initial design step has been modelled to have larger self-weight, external loads and less stiffness than those of real one in service. Thereby measured buffeting responses of existing bridge show different distributions from those of the design model in design step. In order to obtain accurate buffeting responses of the in-site bridge, the analysis model needs to be modified by considering the measured natural frequencies. Until now, a Manual Tuning Method (MTM) has been widely used to obtain the Measurement-based Model(MBM) that has equal natural frequencies to the real bridge. However, since state variables can be selected randomly and its result is not apt to converge exact rapidly, MTM takes a lot of effort and elapsed time. This study presents Buffeting Response Correction Method (BRCM) to obtain more exact buffeting response above MTM. The BRCM is based on the idea the commonly used frequency domain buffeting analysis does not need all structural properties except mode shapes, natural frequencies and damping ratio. BRCM is used to improve each modal buffeting responses of the design model by substituting measured natural frequencies. The measured natural frequencies are determined from acceleration time-history in ordinary vibration of the real bridge. As illustrated examples, simple beam is applied to compare the results of BRCM with those of a assumed MBM by numerical simulation. Buffeting responses of BRCM are shown to be appropriate for those of in-site bridge and the difference is less than 3% between the responses of BRCM and MTM. Therefore, BRCM can calculate easily and conveniently the buffeting responses and improve effectively maintenance and management of in-site bridge than MTM.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.8
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• pp.108-114
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• 2003

This research describes a image-processing technique for the scratch detecting algorithm for ITO coated glass. We use the modified logical thresholding method (called adaptive logical thresholding method) for binarization of gray-scale glass image. This method is useful to the algorithm for detecting the scratch of ITO coated glass automatically without need of any prior information of manual fine-tuning of parameters.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.849-851
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• 2002

This research describes a image-processing technique for the scratch detecting algorithm for ITO coated glass. We use the modified logical thresholding method for binarization of gray-scale glass image. This method is useful to the algorithm for detecting the scratch of ITO coated glass automatically without need of any prior information of manual fine-tuning of parameters.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.76-85
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• 2022

One of the most fundamental challenges when designing controllers for dynamic systems is the adjustment of controller parameters. Usually the system model is used to get the initial controller, but eventually the controller parameters must be manually adjusted in the real system to achieve the best performance. To avoid this manual tuning step, data-driven methods such as machine learning were used. Recently, reinforcement learning became one alternative of this problem to be considered as an agent learns policies in large state space with trial-and-error Markov Decision Process (MDP) which is widely used in the field of robotics. However, on initial training step, as an agent tries to explore to the new state space with random action and acts directly on the controller parameters in real systems, MDP can lead the system safety-critical system failures. Therefore, the issue of 'safe exploration' became important. In this paper we meet 'safe exploration' condition with Control Barrier Function (CBF) which converts direct constraints on the state space to the implicit constraint of the control inputs. Given an initial low-performance controller, it automatically optimizes the parameters of the control law while ensuring safety by the CBF so that the agent can learn how to predict and control unknown and often stochastic environments. Simulation results on a quadrotor UAV indicate that the proposed method can safely optimize controller parameters quickly and automatically.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.9
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• pp.1462-1469
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• 1997

This study presents a genetic algorithm-based method for optimizing control parameters in fluid power systems. Genetic algorithms are general-purpose optimization methods based on natural evolution and genetics. A genetic algorithm seeks control parameters maximizing a measure that evaluates system performance. Five control gains of the PID-PD cascade controller fr an electrohydraulic speed control system with a variable displacement hydraulic motor are optimized using a genetic algorithm in the experiment. Optimized gains are confirmed by inspecting the fitness distribution which represents system performance in gain spaces. It is shown that optimization of the five gains by manual tuning should be a task of great difficulty and that a genetic algorithm is an efficient scheme giving economy of time and in labor in optimizing control parameters of fluid power systems.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.371-376
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• 2003

In general, the electronic forklift driven by DC motor drive system is used in the industrial field. Classically, the DC motor is controlled by speed control using proportion control method, by output torque following the load on the plane like a manual operation. But in the industrial field, the electronic forklift is demanded the robust drive mode. Some cases of the mode, there are trouble in torque and speed control following slope capacity. The control is sensitive concerning with slope angle and output speed, various control method is studied for stability of speed control. We apply speed controller for the self-tuning using DSP(TMS320F240) as main controller for high speed processor, embody dynamic characteristic of control compared the PI control to the fuzzy control.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.849-854
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• 2007

This paper describes design and tuning of a full-range Adaptive Cruise Control (ACC) with collision avoidance. The control scheme is designed to control the vehicle so that it would feel natural to the human driver and passengers during normal safe driving situations and to avoid rear-end collision in vehicle following situations. In this study, driving situations are determined using a non-dimensional warning index and time-to-collision (TTC). A confusion matrix method based on natural driving data sets was used to tune control parameters in the proposed ACC System. An ECU-Brake Hardware-in-the-loop Simulation (HiLS) was developed and used for an evaluation of ACC System. The ECU-Brake HiLS results for alternative driving situation are compared to manual driving data measured on actual traffic way. The ACC/CA control logic implemented in an ECU was tested using the ECU-Brake HiLS in a real vehicle environment.

• Proceedings of the KIPE Conference
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• 2012.11a
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• pp.105-106
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• 2012

A feedback control algorithm for the input voltage control of boost converter is proposed in this paper. The proposed control system is mathematically formulated such that the state feedback gains. The control algorithm does not rely on manual tuning procedures neither use complex adaptive techniques. For the verification of the proposed control algorithm, simulation results of the proposed algorithm using PSIM 9.0 are given.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2552-2556
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• 2005

In general, the forklift driven by DC motor drive system is used in the industrial field. Classically, the DC motor is controlled by current control using proportion control method, by output torque following the load on the plane like a manual operation. But in the industrial field, the forklift is demanded the robust drive mode. Some cases of the mode, there aretrouble in torque control following slope capacity. The control is sensitive concerning about slope angle and output speed, various control method is studied for stability of speed control. In this paper, I apply current control for the self-tuning using the fuzzy controller to obtain robust, stable speed control and use stable, high efficiency control using DSP as main controller for high speed processor, embody dynamic characteristic of control compared the PI controller to the fuzzy controller.