• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.10
• /
• pp.969-974
• /
• 2010

In this paper, we propose a fault-tolerant controller for compensating measurement noise of feedback sensor. Because control systems operate via feedback sensor's signal, the measurement noise in sensor's signal results in performance degradation or even system failure. Therefore, control systems often demand on compensating measurement noise. Our controller is equipped with a compensator in order to reject or reduce the effect of measurement noise in feedback information. Our proposed method is verified via simulation and experiment for a Ball and Beam system.

• Proceedings of the IEEK Conference
• /
• 2003.07c
• /
• pp.2783-2786
• /
• 2003

In this paper, the speed controller of permanent-magnet synchronous motor (PMSM) using the RBF neural (NN) disturbance observer is proposed. The suggested controller is designed using the input-output feedback linearization technique for the nominal model of PMSM and incorporates the RBF NN disturbance observer to compensate for the system uncertainties. Therefore the proposed algorithm is robust against the uncertainties of the system. Finally, the computer simulation is rallied out to verify the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
• /
• 2007.10a
• /
• pp.263-264
• /
• 2007

This paper presents a model predictive controller for tracking control of the wheeled mobile robots (WMRs) subject to nonholonomic constraint. The input-output feedback-linearization method and the mode transformation are used. The performance of the proposed control algorithm is verified via computer simulation. It is shown that the control strategy is feasible.

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

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

• Proceedings of the KIEE Conference
• /
• 1997.11a
• /
• pp.463-465
• /
• 1997

For fast response of the dc output voltage in PWM converter, the relationship of power balance of both the input and output should be introduced to the system modeling. Then, a nonlinear control theory using state feedback linearization is useful to control the system. By nonlinear control, the voltage response can be fast, so the size of the output filter capacitor can be reduced as long as the same response is kept. The validity of the proposed scheme is shown from the simulation results.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.6
• /
• pp.641-646
• /
• 2014

In this paper, we propose a controller for a ball and beam system which reduces the measurement error effect under AC and DC noise. The ball and beam system measures data through a sensor. If sensor noise is included in a controller via the feedback channel, the signal is distorted and the entire system cannot work normally. Therefore, some appropriate action for the measurement error effect is essential in the controller design. Our controller is equipped with a gain-scaling factor and a compensator to reduce the effect of measurement error in the feedback signal. Effectively, our proposed controller can reduce the AC and DC noise of a feedback sensor. We analyze the proposed controller by Laplace transform technique and illustrate the improved control performance via an experiment for a ball and beam system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.12
• /
• pp.967-972
• /
• 2001

In this paper, an adaptive robust nonlinear predictive controller is developed for the continuous time nonlinear systems whose control objective is composed of the system output and its desired value. The basic control law is derived from the continuous time prediction model and its feedback dynamcis shows another from if input and output linearization. In order to cope with the parameter uncertainty, robust control is incorporated into the basic control law and the asymptotic convergence of tracking error to a certain bounded region is guaranteed. For stability and performance improvement within the bounded region, an adaptive control is introduced. Simulation tests for the motion control of an underwater wall-ranging robot confirm the performance improvement and the robustness of this controller.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.16 no.4
• /
• pp.443-450
• /
• 2016

The linearization technique for low noise amplifier (LNA) has been implemented in standard $0.18-{\mu}m$ BiCMOS process. The MOS-BJT derivative superposition (MBDS) technique exploits a parallel LC tank in the emitter of bipolar transistor to reduce the second-order non-linear coefficient ($g_{m2}$) which limits the enhancement of linearity performance. Two feedback capacitances are used in parallel with the base-collector and gate-drain capacitances to adjust the phase of third-order non-linear coefficients of bipolar and MOS transistors to improve the linearity characteristics. The MBDS technique is also employed cascode configuration to further reduce the second-order nonlinear coefficient. The proposed LNA exhibits gain of 9.3 dB and noise figure (NF) of 2.3 dB at 2 GHz. The excellent IIP3 of 20 dBm and low-power power consumption of 5.14 mW at the power supply of 1 V are achieved. The input return loss ($S_{11}$) and output return loss ($S_{22}$) are kept below - 10 dB and -15 dB, respectively. The reverse isolation ($S_{12}$) is better than -50 dB.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.8
• /
• pp.1444-1448
• /
• 2010

The ball and beam system is one of the most popular models for studying control systems because of its nonlinearity and several control techniques have been proposed. Sliding mode control is a popular robust control method which rejects the external disturbance. In this paper, we propose a robust controller using the ${\epsilon}$-sliding surface. On the ${\epsilon}$-sliding surface, the system robustness and convergence can be manipulated via a use of ${\epsilon}$. We show the stability analysis and convergence analysis on the ${\epsilon}$-sliding surface. In addition, the experimental results show the validity of the proposed controller.