• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.728-731
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• 1997

This paper discusses approximation modelling of discrete-time linear time-varying system(LTVS). The wavelet transform is considered as a tool for representing and approximating a LTVS. The joint time-frequency properties of wave analysis are appropriate for describing the LTVS. Simulation results is included to illustrate the potential application of the technique.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.473-478
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• 1992

This paper aims to investigate the navigation control of a mobile robot in a confined environment. Steering angle becomes control variable which is computed from the fuzzy control rules. The identification method proposed in this paper presents the fuzzy control rules obtained through modelling of. the driving actions of human operator. The feasibility of the proposed method is evaluated through the application of the identified fuzzy controls rules to the navigation control of a mobile robot which follows the center of a corridor.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.342-348
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• 2017

Precursor analysis is widely used in the nuclear industry to judge the significance of events relevant to safety. However, in case of events that may damage equipment through effects that are not ordinary functional dependencies, the analysis may not always fully appreciate the potential for further evolution of the event. For fires, which are one class of such events, this paper discusses modelling challenges that need to be overcome when performing a probabilistic precursor analysis. The events used to analyze are selected from the Organisation for Economic Cooperation and Development (OECD) Fire Incidents Records Exchange (FIRE) Database.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.395-400
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• 2015

Obtaining the parameters for PID controllers based on limit cycle information for the process in a relay controlled feedback loop has become an accepted practical procedure. If the form of the plant transfer function is known, exact expressions for the limit cycle frequency and amplitude can be derived so that their measurements, assumed error free, can be used to calculate the true parameter value. In the literature, parameter estimation for an assumed form of the plant transfer function has generally been considered for disturbance free cases, except a recently published work of the author. In this paper additional simulation results are reported on exact parameter estimation from relay autotuning under static load disturbances.

• Smart Structures and Systems
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• v.14 no.4
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• pp.643-658
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• 2014

This paper presents the design, modelling and, simulation and experimental results of a shape memory alloy (SMA) actuator based critical motion control application. Dynamic performance of SMA and its ability in replacing servo motor is studied for which the famous open loop unstable balancing ball and beam system direct driven by antagonistic SMA is designed and developed. Simulation uses the mathematical model of ball and beam structure derived from the first principles and model estimated for the SMA actuator by system identification. A PID based cascade control system consisting of two loops is designed and control of ball trajectory for various target positions with settling time as control parameter is verified experimentally. The results demonstrate the performance of SMA for a complicated i.e., under actuated, highly nonlinear unstable system, and thereby it's dynamic behaviour. Control strategies bring out the effectiveness of the actuator and its possible application to much more complex applications such as in aerospace control and robotics.

• Speech Sciences
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• v.9 no.2
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• pp.1-11
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• 2002

This paper aims to provide a guideline for modelling speaker identification and speaker verification by comparing voice similarities between brothers. Five pairs of brothers who are believed to have similar voices participated in this experiment. Before conducted in the experiment, perceptual tests were measured if the voices were similar between brothers. The words were measured in both isolation and context, and the subjects were asked to read five times with about three seconds of interval between readings. Recordings were made at natural speed in a quiet room. The data were analyzed in pitch and formant frequencies using CSL (Computerized Speech Lab), PCQuirer and MDVP (Multi -dimensional Voice Program). It was found that data of the initial vowels are much more similar and homogeneous than those of vowels in other position. The acoustic data showed that voice similarities are strikingly high in both pitch and formant frequencies. It was also found that the correlation coefficient was not significant between parameters above.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.214-217
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• 1993

This paper presents a new identification method which utilizes fuzzy inference in parameter identification. The proposed system has an additional control loop where a real plant is replaced by a plant model. The control system to be designed is to satisfy the following specifications: 1) It has zero steady-state error. 2) It has adequate damping characteristics. 3) 1),2) satisfied, it has a shortest rise-time. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. This method is effective in auto-tuning because the response of the closed loop is verified. The proposed method is tested in simulation for several plants with first- order lags and dead-times. The results show that the proposed method is effective in practical use.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.224-226
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• 1993

Multi-layered neural networks offer an exciting alternative for modelling complex non-liner systems. This paper investigates the identification of continuous time nonliner system using neural networks with a single hidden layer. The digital low - pass filter are introduced to avoid direct approximation of system derivatives from sampled data. Using a pre-designed digital low pass filter, an approximated discrete-time estimation model is constructed easily. A continuous approximation liner model is first estimated from sampled input-out signals. Then the modeling error due to the nonlinearity is decreased by a compensator using neural network. Simulation results are given to demonstrate the effective of the proposed method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.3
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• pp.258-265
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• 2017

This paper validates a system identification method using mathematical optimization using sea trial measurement data as a benchmark. A fast time simulation tool, SIMOPT, and a Rheinmetall Defence mathematical model have been adopted to conduct initial hydrodynamic coefficient estimation and simulate ship modelling. Calibration for the environmental effect of sea trial measurement and sensitivity analysis have been carried out to enable a simple and efficient optimization process. The optimization process consists of three steps, and each step controls different coefficients according to the corresponding manoeuvre. Optimization result of Step 1, an optimization for coefficient on x-axis, was similar compared to values applying an empirical regression formulae by Clarke and Norrbin, which is used for SIMOPT. Results of Steps 2 and 3, which are for linear coefficients and nonlinear coefficients, respectively, was differ from the calculation results of the method by Clarke and Norrbin. A comparison for ship trajectory of simulation results from the benchmark and optimization results indicated that the suggested stepwise optimization method enables a coefficient tuning in a mathematical way.

• Steel and Composite Structures
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• v.20 no.6
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• pp.1345-1368
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• 2016

This paper presents the probabilistic-based assessment of composite steel-concrete structures through an innovative framework. This framework combines model identification and reliability assessment procedures. The paper starts by describing current structural assessment algorithms and the most relevant uncertainty sources. The developed model identification algorithm is then presented. During this procedure, the model parameters are automatically adjusted, so that the numerical results best fit the experimental data. Modelling and measurement errors are respectively incorporated in this algorithm. The reliability assessment procedure aims to assess the structure performance, considering randomness in model parameters. Since monitoring and characterization tests are common measures to control and acquire information about those parameters, a Bayesian inference procedure is incorporated to update the reliability assessment. The framework is then tested with a set of composite steel-concrete beams, which behavior is complex. The experimental tests, as well as the developed numerical model and the obtained results from the proposed framework, are respectively present.