• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.281-287
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• 2002

This paper investigates on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several inde-pendent, but interacting processes running on two separate stations. By using this NCS, the network-induced delay is analyzed to find the cause and effect of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controller's performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice far NCS due to its robustness against parameter uncertainty.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.684_685
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• 2009

A digital sampling algorithm that uses a two high resolution integrating Voltmeters which are synchronized by Phase Lock Loop (PLL) time clock for accurately measuring the parameters, active and reactive power, for sinusoidal power measurements is presented. The PLL technique provides high precision measurements, root mean square (rms), phase and complex voltage ratio, of the AC signal. The system has been designed to be used at the Korean Research Institute of Standards and Science (KRISS) as a reference power standard for electrical power calibrations. The test results have shown that the accuracy of the measurements is better than $10 {\mu}W/VA$ and the level of uncertainty is valid for the power factor range zero to 1 for both lead and lag conditions. The system is fully automated and allows power measurements and calibration of high precision wattmeters and power calibrators at the main power frequencies 50 and 60 Hz.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.2
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• pp.163-172
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• 2010

A robust positioning control system has been studied using a friction parameter observer and a recurrent fuzzy neural network based on the sliding model. To estimate a nonlinear friction parameters of the LuGre friction model, a dual friction model-based observer is introduced. In addition, an approximating method for a system uncertainty has been developed using a recurrent fuzzy neural network technique to improve positioning performance. Experimental results have been presented to validate the performance of a proposed intelligent compensation scheme.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.72-78
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• 2006

The paper proposes reference model error feedback control scheme for motion control system with hard non-linear components as like saturation and dead-zone in plant input part. Additionally, the plant has the system uncertainty effected by plant model parameter deviation and disturbance. The control algorithm uses the reference model to apply additional feedback loop with the error between reference model output and actual output effected by disturbance and non-linear components. And the stability evaluation based on Popov stability and controller design method are formulated to be performed. The effectiveness of the proposed scheme is examined by simulations. The results are proven by reasonable performances following reference model responses with good disturbance rejection performance without over-tuning of controller.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.2
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• pp.63-70
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• 2020

Many organizations apply reactive safety management to prevent the same or similar types of accidents by through investigation and analysis of the accident cases. Although research on investigation techniques has contributed a lot to the objective results of safety accidents and the preparation of countermeasures, many accident investigation techniques currently in use treat accidents from a linear perspective, revealing limitations in reflecting current systems dominated by complexity and uncertainty. In order to overcome these limitations, this study will review recent studies and concepts from a system safety perspective and predict future research trends through a case analysis of aviation accident. The models used in the analysis are STAMP, HFACS, and FRAM, and the characteristics of each technique are presented so that analysts who perform related tasks in the field can refer to them.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.351-359
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• 2007

In this study, a hierarchical switching control scheme based on robust control theory is proposed for tracking control of vehicle longitudinal acceleration in the presence of large uncertainties. A model set consisting of four multiplicative-uncertainty models is set up, and its corresponding controller set is designed by the LMI approach, which can ensures the robust performance of the closed loop system under arbitray switching. Based on the model set and the controller set, a switching index function by estimating the system gain of the uncertainties between the plant and the nominal model is designed to determine when and which controller should be switched into the closed loop. After theoretical analyses, experiments have also been carried out to validate the proposed control algorithm. The results show that the control system has good performance of robust stability and tracking ability in the presence of large uncertainties. The response time is smaller than 1.5s and the max tracking error is about $0.05\;m/S^2$ with the step input.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1624-1632
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• 2009

In this study, we introduce the design methodology of an optimized Interval Type-2 fuzzy controller. The fixed MF design of type-1 based FLC leads to the difficulty of rule-based control design for representing the linguistically uncertain expression. In the Type-2 FLC as the expanded type of Type-1 FLC, we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. Type-2 FLC has a robust characteristic in the unknown system with unspecific noise when compared with Type-1 FLC. Through computer simulation as well as practical experiment, we compare their performance by applying both the optimized Type-1 and Type-2 fuzzy cascade controllers to ball and beam system. To evaluate each controller performance, we consider controller characteristic parameters such as maximum overshoot, delay time, rise time, settling time and steady-state error.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.767-779
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• 2017

Automated mission planning for unmanned aerial vehicles (UAVs) is difficult because of the propagation of several sources of error into the solution, as for any large scale autonomous system. To ensure reliable system performance, we quantify all sources of error and their propagation through a mission planner for operation of UAVs in an obstacle rich environment we developed in prior work. In this sequel to that work, we show that the mission planner developed before can be made robust to errors arising from the mapping, sensing, actuation, and environmental disturbances through creating systematic buffers around obstacles using the calculations of uncertainty propagation. This robustness makes the mission planner truly autonomous and scalable to many UAVs without human intervention. We illustrate with simulation results for trajectory generation of multiple UAVs in a surveillance problem in an urban environment while optimizing for either maximal flight time or minimal fuel consumption. Our solution methods are suitable for any well-mapped region, and the final collision free paths are obtained through offline sub-optimal solution of an mTSP (multiple traveling salesman problem).

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1834-1835
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• 2006

A robust adaptive position control algorithm is proposed for servomotor drive system with uncertainties and load disturbance. The proposed controller is comprised of a nominal controller and a robust control. The nominal controller is designed in the condition without all the external load disturbance, nonlinear friction and unpredicted uncertainties. The robust controller containing lumped uncertainty approximator using fuzzy-neural network(FNN) is designed to dispel the effect of uncertainties and load disturbance. The interconnection weight of the FNN can be online tuned in the sense of the Lyapunov stability theorem thus asymptotic stability of the proposed control system can be guaranteed. Finally, simulation results verify that the proposed control algorithm can achieve favorable tracking performance for the induction servomotor drive system.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2780-2782
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• 2005

In this paper, we present a mobile robot localization solution by using a Ubiquitous Vision System (UVS). The collective information gathered by multiple cameras that are strategically placed has many advantages. For example, aggregation of information from multiple viewpoints reduces the uncertainty about the robots' positions. We construct UVS as a multi-agent system by regarding each vision sensor as one vision agent (VA). Each VA performs target segmentation by color and motion information as well as visual tracking for multiple objects. Our modified identified contractnet (ICN) protocol is used for communication between VAs to coordinate multitask. This protocol raises scalability and modularity of thesystem because of independent number of VAs and needless calibration. Furthermore, the handover between VAs by using ICN is seamless. Experimental results show the robustness of the solution with respect to a widespread area. The performance in indoor environments shows the feasibility of the proposed solution in real-time.