• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.4
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• pp.71-80
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• 2006

Strapdown Inertial navigation systems consist of an inertial sensor assembly(ISA), electronic modules to process sensor data, and a navigation computer to calculate attitude, velocity and position. In the ISA, most gryoscopes such as RLGs and FOGs, have digital output, but typical accelerometers use current as an analog output. For a high precision inertial navigation system, sufficient stability and resolution of the accelerometer board converting the analog accelerometer output into digital data needs to be guaranteed. To achieve this precision, the asymmetric error and A/D reset scale error of the accelerometer board must be properly compensated. If the relation between the acceleration error and the errors of boards are exactly known, the compensation and estimation techniques for the errors may be well developed. However, the A/D Reset scale error consists of a pulse-train type term with a period inversely proportional to an input acceleration additional to a proportional term, which makes it difficult to estimate. In this paper, the effects on the acceleration output for auto-pilot situations and the effects of A/D reset scale errors during horizontal alignment are qualitatively analyzed. The result can be applied to the development of the real-time compensation technique for A/D reset scale error and the derivation of the design parameters for accelerometer board.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.192-200
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• 2012

Purpose: Aerial application of chemicals with an agricultural helicopter allows for precise and timely spraying and reduces working labor and pollution. An attitude controller for an agricultural helicopter would be helpful to aerial application operator. The objectives of this paper are to determine the transfer function models and to estimate the handling qualities of a bare-airframe model helicopter. Methods: Transfer functions of a model unmanned helicopter were estimated by using NAVFIT and DERIVID modules of the $CIFER^{(R)}$ program to the time history data of frequency sweep flight tests. Control inputs of the transfer functions were elevator, aileron, rudder and collective pitch stick positions and the outputs were resulting on-axis movements of the fuselage. Results: Minimum realization of the transfer functions for pitch rate output to elevator control input and roll rate output to aileron control input produced second order transfer functions with undamped natural frequencies around 3.0 Hz and damping ratios of 0.139 and 0.530, respectively. The equivalent time delays of the transfer functions ranged from 0.16 to 0.44 second. Sensitivity analysis of the proposed parameters allowed derivation of minimal realization of the transfer functions. Conclusions: Handling quality of the model helicopter was addressed based on the eigenvalues of the transfer functions, corresponding undamped natural frequencies with damping ratios. The equivalent time delays of the lateral-directional motion ranged from 0.16 to 0.44 second, longer than the 0.1 to 0.15 second requirement for well-controlled typical manned aerial vehicles.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1743-1750
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• 2003

DC motor requires a rotor speed sensor for accurate speed control. The speed sensors such as resolvers and encoders are used as a speed detector, but they increase cost and size of the motor and restrict the industrial drive applications. So in these days, many papers have reported in the sensorless operation of DC motor〔3­5〕. This paper presents a new sensorless strategy using neural networks〔6­8〕. Neural network has three layers which are input layer, hidden layer and output layer. The optimal neural network structure was tracked down by trial and error, and it was found that 4­16­1 neural network structure has given suitable results for the instantaneous rotor speed. Also, learning method is very important in neural network. Supervised learning methods〔8〕 are typically used to train the neural network for learning the input/output pattern presented. The back­propagation technique adjusts the neural network weights during training. The rotor speed is gained by weights and four inputs to the neural network. The experimental results were found satisfactory in both the independency on machine parameters and the insensitivity to the load condition.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.1
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• pp.52-58
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• 2005

Among various modern control theories, PID control has been well used for several decades. PID algorithms need some tuning methods which are used for selecting PID parameters. But in some cases various kinds of performance indices are used instead of well-known tuning rules, and so variable type of performance index must be tested so that controllers, output characteristics and disturbance rejection property meet some specifications. In this paper, linear conbinational type of performance index using error signal, time, control input and robustness is used to the PID control of air conditioning system. By use of the 2 DOF PID parmeters minimizing perfromacne index controllers, output characteristics and robustness properties are analyzed. Simulations are done by use of MATLAB with Simulink.

• Journal of Convergence Society for SMB
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• v.4 no.2
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• pp.25-31
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• 2014

Sliding mode design and analysis for nonlinear system was carried out. A designer will determine the parameters to know about the performance and robustness of the system dynamics. To investigate the characteristics of sliding mode control, an inverted pendulum model is applied by the sliding mode control and the state concerned is output. Comparison is made by evaluating different initial conditions, sliding numerical components for sliding surface, and input gain, the dynamic of output will be investigated to conclude the generality. Control approaches have their limitations and sliding mode control is no exception. The chattering problem is its main negative effect to overcome. This effect is displayed and in this project chattering problem is suppressed by a modified discontinuous controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.175-181
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• 2009

In this paper, it is suggested that the selection method of parameter of Power System Stabilizer(PSS) with robustness in low frequency oscillation for Static VAR Compensator(SVC) using a self tuning fuzzy controller for a synchronous generator excitation and SVC system. The proposed parameter self tuning algorithm of fuzzy controller is based on the steepest decent method using two direction vectors which make error between inference values of fuzzy controller and output values of the specially selected PSS reduce steepestly. Using input-output data pair obtained from PSS, the parameters in antecedent part and in consequent part of fuzzy inference rules are learned and tuned automatically using the proposed steepest decent method.

• Structural Engineering and Mechanics
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• v.55 no.1
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• pp.229-244
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• 2015

H-infinity norm relates to the maximum in the frequency response function and H-infinity control method focuses on the case that the vibration is excited at the fundamental frequency, while 2-norm relates to the output energy of systems with the input of pulses or white noises and 2-norm control method weighs the overall vibration performance of systems. The trade-off between the performance in frequency-domain and that in time-domain may be achieved by integrating two indices in the mixed vibration control method. Based on the linear fractional state space representation in the modal space for a piezoelectric flexible structure with uncertain modal parameters and un-modeled residual high-frequency modes, a mixed dynamic output feedback control design method is proposed to suppress the structural vibration. Using the linear matrix inequality (LMI) technique, the initial populations are generated by the designing of robust control laws with different H-infinity performance indices before the robust 2-norm performance index of the closed-loop system is included in the fitness function of optimization. A flexible beam structure with a piezoelectric sensor and a piezoelectric actuator are used as the subject for numerical studies. Compared with the velocity feedback control method, the numerical simulation results show the effectiveness of the proposed method.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.4
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• pp.11-19
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• 2011

PADDIMOD2 was deloped to estimate nonpoint source pollution from paddy rice fields. The PADDIMOD2 was enhanced to estimate runoff and pollutant load during non-growing as well as growing season and to be easily used for public by development of Excel based system. Nutrient concentration and hydrology were based on Dirac delta function and continuous source function, and tank model for growing season and Event Mean Concentrations (EMCs) and SCS-Curve Number method for non-growing season. The PADDIMOD2 consists of three main component (input data, parameters data, and output data) by including eight Excel spread sheets. As a result of model application, total precipitation and irrigation were 1,051.7 mm and 439.2 mm, respectivley and surface runoff and water loss including infiltration and evapotranspiration were 463.0 mm and 947.9 mm, respectively. Annual nutrient loadings of T-N and T-P from study area were 6.7 kg/$km^2$/day and 0.5 kg/$km^2$/day, respectively. Development of PADDIMOD2 was focused on minimizing input data and maximizing user friendly system and is expected to be useful tool to evaluate various non-structure BMPs and estimate unit load from paddy rice fields for application at Korean TMDL.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.999-1007
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• 2006

The Backpropagation learning algorithm is known to have slow and false convergence aroused from plateau and local minima. Many substitutes for backpropagation announced so far appear to pay some trade-off for convergence speed and stability of convergence according to parameters. Here, a new algorithm is proposed, which avoids some of those problems associated with the conventional backpropagation problems, especially with local minima, and gives relatively stable and fast convergence with low storage requirement. This is the separate learning algorithm in which the upper connections, hidden-to-output, and the lower connections, input-to-hidden, separately trained. This algorithm requires less computational work than the conventional backpropagation and other improved algorithms. It is shown in various classification problems to be relatively reliable on the overall performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2352-2360
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• 2011

In this paper, we introduce a comprehensive design methodology of Radial Basis Function Neural Networks (RBFNN) that is based on mechanism of clustering and optimization algorithm. We can divide some clusters based on similarity of input dataset by using clustering algorithm. As a result, the number of clusters is equal to the number of nodes in the hidden layer. Moreover, the centers of each cluster are used into the centers of each receptive field in the hidden layer. In this study, we have applied Fuzzy-C Means(FCM) and K-Means(KM) clustering algorithm, respectively and compared between them. The weight connections of model are expanded into the type of polynomial functions such as linear and quadratic. In this reason, the output of model consists of relation between input and output. In order to get the optimal structure and better performance, Particle Swarm Optimization(PSO) is used. We can obtain optimized parameters such as both the number of clusters and the polynomial order of weights connection through structural optimization as well as the widths of receptive fields through parametric optimization. To evaluate the performance of proposed model, NXT equipment offered by National Instrument(NI) is exploited. The situation awareness system-related intelligent model was built up by the experimental dataset of distance information measured between object and diverse sensor such as sound sensor, light sensor, and ultrasonic sensor of NXT equipment.