• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.8
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• pp.1251-1258
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• 2003

This paper presents a nonlinear robust approach to the slip control problem for a torque converter bypass clutch in a passenger car. The proposed nonlinear robust controller builds upon only the measurements avail-able from inexpensive sensors that are already installed in passenger cars for control. The issue of torque estimation problems for the implementation of the proposed controller is addressed. The stability of the internal dynamics is investigated, upon which a nonlinear robust controller is designed using input-output feedback linearization and Lyapunov redesign technique. The performance of the designed controller is validated by simulation studies.

• 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.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.693-696
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• 2005

We propose a robust adaptive fuzzy controller for the transient stability and voltage regulation of a single-machine inflnite bus power system. The proposed control scheme is based on the input-output linearization to eliminate the system nonlinearities. To deal with uncertainties due to a parameter variation or a fault, we introduce fuzzy systems with universal function approximating capability which estimate the uncertainties on-line.

• Journal of Power Electronics
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• v.14 no.5
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• pp.989-999
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• 2014

High-performance Current Source Inverter (CSI)-fed, variable speed alternating current drives are prepared for various industrial applications. CSI-fed Induction Motor (IM) drives are managed by using different control methods. Noteworthy methods include scalar Control (V/f), Input-Output Linearization (IOL) control, Field-Oriented Control (FOC), and Direct Torque Control (DTC). The objective of this work is to compare the dynamic performance of the aforementioned drive control methods for CSI-fed IM drives. The dynamic performance results of the proposed drives are individually analyzed through sensitivity tests. The tests selected for the comparison are step changes in the reference speed and torque of the motor drive. The operation and performance of different vector control methods are verified through simulations with MATLAB/Simulink and experimental results.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.58-61
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• 1996

For a class of single-input single-output continuous-time nonlinear systems, a multilayer neural network-based controller that feedback-linearizes the system is presented. Control action is used to achieve tracking performance for a state-feedback linearizable but unknown nonlinear system. The multilayer neural network(NN) is used to approximate nonlinear continuous function to any desired degree of accuracy. The weight-update rule of multilayer neural network is derived to satisfy Lyapunov stability. It is shown that all the signals in the closed-loop system are uniformly bounded. Initialization of the network weights is straightforward.

• Journal of Power Electronics
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• v.10 no.6
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• pp.694-701
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• 2010

In this paper an effective direct torque control (DTC) and stator flux control is developed for a quasi six-phase induction motor (QIM) drive with sinusoidally distributed windings. Combining sliding-mode (SM) control and adaptive input-output feedback linearization, a nonlinear controller is designed in the stationary reference frame, which is capable of tracking control of the stator flux and torque independently. The motor controllers are designed in order to track a desired second order linear reference model in spite of motor resistances mismatching. The effectiveness and capability of the proposed method is shown by practical results obtained for a QIM supplied from a voltage source inverter (VSI).

• Advances in aircraft and spacecraft science
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• v.6 no.5
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• pp.371-389
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• 2019

The implementation of a robust $H_{\infty}$ Control, which is numerically efficient for uncertain nonlinear dynamics, on longitudinal and lateral autopilots is realised for a quarter scale Piper J3-Cub model accepted as an unmanned aerial vehicle (UAV) under the condition of sensor noise and disturbance effects. The stability and control coefficients of the UAV are evaluated through XFLR5 software, which utilises a vortex lattice method at a predefined flight condition. After that, the longitudinal trim point is computed, and the linearization process is performed at this trim point. The "${\mu}$-Synthesis"-based robust $H_{\infty}$ control algorithm for roll, pitch and yaw displacement autopilots are developed for both longitudinal and lateral linearised nonlinear dynamics. Controller performances, closed-loop frequency responses, nominal and perturbed system responses are obtained under the conditions of disturbance and sensor noise. The simulation results indicate that the proposed control scheme achieves robust performance and guarantees stability under exogenous disturbance and measurement noise effects and model uncertainty.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2142-2153
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• 2014

Linearization of transducer characteristic plays a vital role in electronic instrumentation because all transducers have outputs nonlinearly related to the physical variables they sense. If the transducer output is nonlinear, it will produce a whole assortment of problems. Transducers rarely possess a perfectly linear transfer characteristic, but always have some degree of non-linearity over their range of operation. Attempts have been made by many researchers to increase the range of linearity of transducers. This paper presents a method to compensate nonlinearity of Linear Variable Displacement Transducer (LVDT) based on Extreme Learning Machine (ELM) method, Differential Evolution (DE) algorithm and Artificial Neural Network (ANN) trained by Genetic Algorithm (GA). Because of the mechanism structure, LVDT often exhibit inherent nonlinear input-output characteristics. The best approximation capability of optimized ANN technique is beneficial to this. The use of this proposed method is demonstrated through computer simulation with the experimental data of two different LVDTs. The results reveal that the proposed method compensated the presence of nonlinearity in the displacement transducer with very low training time, lowest Mean Square Error (MSE) value and better linearity. This research work involves less computational complexity and it behaves a good performance for nonlinearity compensation for LVDT and has good application prospect.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.11
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• pp.9-21
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• 2009

This paper proposes the alternative observer and controller design scheme based on T-S fuzzy model. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given unknown nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. The proposed controller is based on a simple output feedback method. Therefore, it solves the singularity problem, without any additional algorithm, which occurs in the inverse dynamics based on the feedback linearization method. The adaptive fuzzy scheme estimates the parameters and the feedback gain comprising the fuzzy model representing the observation system. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observer and controller, they are applied to an inverted pendulum on a cart.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.3
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• pp.306-312
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• 2019

This paper investigates to design a controller for maritime autonomous surface ship (MASS) by means of adaptive super-twisting algorithm (ASTA). A input-out feedback linearization method is considered for multi-input multi-output (MIMO) system. Sliding Mode Controller (SMC) is suitable for MASS subject to ocean environments due to its robustness against parameter uncertainties and disturbances. However, conventional SMC has inherent disadvantages so-called, chattering phenomenon, which resulted from the high frequency of switching terms. Chattering may cause harmful failure of actuators such as propeller and rudder of ships. The main contribution of this work is to address an appropriate controller for MASS, simultaneously controls surge and yaw motion in severe step inputs. Proposed control mechanism well provides convergence bewildered by external disturbances in the middle of steady-state responses as well as chattering attenuation. Also, the adaptive algorithm is contributed to reducing non-overestimated value of control gains. Control inputs of surge and yaw motion are displayed by smoother curves without excessive control activities of actuators. Finally, no overshoot can be seen in transient responses.