• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.64.1-64
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• 2001

Errors in inertial navigation system(INS) can be divided into two major groups which are system related errors and modeling errors due to approximation and linearization. Measurement noise, calibration, and alignment errors make up the first group, whereas the uncertainties in the gravity vector fall in the second category and are important error source for high quality INS, especially during high altitude and and/or long time missions, when the gravity errors tent to build up. The quality of a medium to high accuracy INS depends on the knowledge of the local gravity field. In this paper, the feasibility of improving airborns INS by use of more accurate gravity model is studied. To make consistent comparisons, WGS-84 parameters are used and ...

• Journal of IKEEE
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• v.22 no.1
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• pp.110-120
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• 2018

In this paper, we apply the input-output linearization technique to tracking the follow-up trajectory r(t) in the ball-beam system. There exist system disturbance and various uncertainties, the conventional input-output linearization based control yields some noticeable errors in tracking performance. As a result, a new robust control technique for the uncertainty of the system was proposed and its improved performance verified through simulation and experimental results. So, more realistic system model is obtained with unmatched uncertainties and disturbance. Then, in order to improve the control performance, a new optimal bang-bang control input is additionally added.

• Journal of Power Electronics
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• v.11 no.5
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• pp.719-725
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• 2011

This paper describes a novel Direct Torque Control (DTC) method for adjustable speed Doubly-Fed Induction Machine (DFIM) drives which is supplied by a two-level Space Vector Modulation (SVM) voltage source inverter (DTC-SVM) in the rotor circuit. The inverter reference voltage vector is obtained by using input-output feedback linearization control and a DFIM model in the stator a-b axes reference frame with stator currents and rotor fluxes as state variables. Moreover, to make this nonlinear controller stable and robust to most varying electrical parameter uncertainties, a two layer recurrent Artificial Neural Network (ANN) is used to estimate a certain function which shows the machine lumped uncertainty. The overall system stability is proved by the Lyapunov theorem. It is shown that the torque and flux tracking errors as well as the updated weights of the ANN are uniformly ultimately bounded. Finally, effectiveness of the proposed control approach is shown by computer simulation results.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.689-696
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• 2000

In this paper we propose an eminent controller for wheeled mobile robots. This controller consists of an input-output linearization controller trying to stabilize the system and a neural network controller to compensate for uncertainties. The uncertainties are divided into two parts. First unstructured uncertainties include the elements related with system order such as friction disturbance. Second structure uncertainties are the incorrect system parameters A neural network structure of the proposed overall controller learns structural errors of the wheeled mobile robots with uncertainties and includes the neural network output. This controller learns quickly the model and has good tracking performance Simulation results show that the proposed controller is more efficient than analog controllers.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.267-274
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• 1999

This paper proposes an adaptive sliding mode control scheme for an autopilot design of Skid-to-Turn (STT) missiles. The feedback linearization controller eliminates nonlinear terms in STT dynamics and makes the entire system linear. But the modeling errors in dynamics and the external disturbances exert bad influence on the performance of the feedback linearization controller. To handle these uncertainties, an adaptive control scheme is developed, where a bound of the uncertainties is estimated by an adaptive law based on a sliding surface. The asymptotic output tracking is proved by using the Lyapunov stability theory. Simulations for STT missiles illustrate the validity of the proposed scheme.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.9
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• pp.811-819
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• 2004

A silica gel desiccant dehumidifier is studied theoretically in this paper adopting several linearization assumptions. The governing equations are linearized with the assumptions, and the exact solutions to the temperature and the humidity ratio are obtained. In spite of the assumptions, the theoretical results are found to agree well with those from the numerical analysis without any assumption. In typical operation ranges of the desiccant dehumidifier, the time-averaged errors in the process air temperature and humidity ratio are less than 4% and 7%, respectively, and the corresponding root-mean-square values are less than 5% and 15%, respectively The analytical solutions are expected to contribute to the fundamental understanding of the dehumidification and regeneration processes and the correlation analysis of the numerous parameters influencing the dehumidifier operation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.123-128
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• 1998

This paper proposes design of LFT-based fuzzy controllers for model-following, which are better than the previous input-output linearization controllers, which are not able to follow the model system states and which do not guarantee the stability of all states. The method proposed in this paper provides a LFT-based Takagi-Sugeno(T-S) fuzzy controller with guaranteed stability and model-following via the following steps: First, using LFT(Linear Fractional Transformation) and T-S fuzzy model, controllers, are obtained. Next, error dynamics are obtained for model-following, and errors go to 0(zero). Finally, a T-s fuzzy controller that can stabilizxe the system with the requirement on the control input satisfied is obtained by solving the LMIs with the MATLAB LMI Control Toolbox and a model-following controller is obtained. Simulations are performed for the LFT-based T-S fuzzy controller designed by the proposed method, which show better performance than the results of input-out ut linearization controller.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.7
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• pp.1102-1109
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• 2001

This paper presents the new architecture of an adaptive predistortion linearizer using the polynomial type predistorter. In the proposed linearizer, most of the processes, including the predistortion, are performed with a digital signal processor(DSP). The recursive least squares(RLS) algorithm is employed for the optimization process to minimize the errors between the predistorter and postdistorter output signals. Simulation results demonstrate that the adjacent channel power ratio(ACPR) is improved by greater than 40 dB at the band edge with linearization. The convergence and reconvergence performance of the linearizer is also satisfactory.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.3
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• pp.289-297
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• 2014

This paper proposed a novel high performance sensorless control scheme for IPMSM based on an extended nonlinear state observer. The gain-matrix of the observer has been derived by using state linearization method. Steady state errors in estimated rotor position and speed due to parameter inaccuracy have been analyzed, and an equivalent flux error is defined to represent the overall effect of parameter errors contributing to the wrong convergence of the estimated rotor speed as well as rotor position. Then, an online compensation strategy was proposed to limit the estimation errors in rotor position and speed. The effectiveness of the extended nonlinear state observer is validated through simulation and experimental test.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.136-144
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• 1999

This paper deals with the fault detection problem in uncertain linear multivariable systems and its application. A robust fault detection method presented by Kim et a. (1998) for MIMO (Multi Input/Multi Output) systems has been adopted and applied to the twin rotor MIMO experimental setup using industrial DSP. The system identification problem is formulated for the twin rotor MIMO system and its parameters are estimated using experimental data. Based on the estimated parameters, some fault detection simulations are performed using the robust fault detection method, which shows that the preformance is satisfied.