• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1754-1760
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• 2011

In this paper, a systematic design of a robust nonlinear multivariable variable structure controller based on state dependent nonlinear form is presented for the control of MIMO uncertain affine nonlinear systems with mismatched uncertainties and matched disturbance. After a MIMO uncertain affine nonlinear system is represented in the form of state dependent nonlinear system, a systematic design of a robust nonlinear variable structure controller is presented. To be linear in the closed loop resultant dynamics, the linear sliding surface is applied. A corresponding diagonalized control input is proposed to satisfy the closed loop global exponential stability and the existence condition of the sliding mode on the linear sliding surface, which will be investigated in Theorem 1. Through a design example and simulation study, the usefulness of the proposed controller is verified.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1414-1417
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• 2003

In this paper, sliding mode controller for discrete-time nonlinear systems with uncertainties and disturbances are proposed. The concept of time-delay control (TDC) which consists of estimating the uncertain dynamics of the system through past observations of the system response is used. The proposed controller guarantees that the closed-loop system states are globally uniformly ultimately bounded (GUUB). It is also shown that the closed-loop system states are globally uniformly asymptotically stable (GUAS) if uncertainties are constant.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.460-460
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• 2000

Until now various model matching systems have been proposed for linear system, but very little has been done for nonlinear system In this paper, a design method of discrete time flight control system using nonlinear model matching is proposed. This method is based on Hirschorn's algorithm and facilitates easy determination of the control law using the relationship, between the output and the input, which is obtained by the time shift of the output. Also as a result, this method is the extension of the linear model matching control system proposed by Wolovich, in which the control law is obtained by left-multiplying the output by the interactor matrix. At the end of paper, the proposed control system is applied to CCV flight control system of an aircraft and the feasibility of the proposed approach is shown by the numerical simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.692-695
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• 1997

Nonlinear robust attitude controller for 3-axis stabilized spacecraft is designed. Robust stability analysis for nonlinear spacecraft system with disturbance is conducted. External disturbances and parametric uncertainties decrease Spacecraft's attitude pointing accuracy. Sliding Mode Control(SMC) provides stability of system in the face of these disturbances and uncertainties. The concept of quadratic boundedness and quadratic stability are applied to the robust analysis for the nonlinear spacecraft system subject to bounded disturbance torques. Numerical simulation is conducted to compare the analysis result and actual nonlinear simulation. The simulation show that analysis result is valid.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.185-188
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• 1997

In this paper, we execute identification, linearization, and control of a nonlinear system using recurrent neural networks. In general nonlinear control system become complex because of nonlinearity and uncertainty. And though we compose nonlinear control system based on the model, it is difficult to get good control ability. So we identify the nonlinear control system using the recurrent neural networks and execute feedback linearization of identified model, In this process we choose the optional linear system, and the system which will have to be feedback linearized if trained to follow the linearity between input and output of the system we choose. We the feedback linearized system by applying standard linear control strategy and simulation. And we evaluate the effectiveness by comparing the result which is linearized theoretically.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.186-189
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• 2001

In a precise control system, the Lu-Gre friction model has often been used to describe the nonlinear friction. For the XY table system with this friction model, we identified the friction parameters and designed nonlinear observer. The nonlinear friction effects could be removed within appropriate position tracking errors and control inputs through experiments. Also, we designed the nonmodel-based SMC system to compensate the nonlinear friction. Through experiments, it is shown that this method has the similar performance compared with the nonlinear observer system and is useful when friction parameters are hard to identify except the problem of input chattering.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1728-1729
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• 2007

This paper presents an adaptive neural dynamic surface control (DSC) approach with $H_{\infty}$ tracking performance for a full dynamics of a nonlinear flight system. It is assumed in this paper that model uncertainties such as structured and unstrutured uncertainties and external disturbances influence the nonlinear aircraft model. In our control system, self recurrent wavelet neural networks (SRWNNs) are used to compensate model uncertainties of the nonlinear flight system, and an adaptive DSC technique is extended for disturbance attenuation of the nonlinear flight system. From Lyapunov stability theorem, it is shown that $H_{\infty}$ performance from external disturbances can be obtained. Finally, we perform the simulation for the nonlinear six-degree-of-freedom F-16 aircraft model to confirm the effectiveness of the proposed control system.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.445-450
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• 1998

In this paper, a robust nonlinear prediction-type controller (RNPC) is developed for the continuous time nonlinear system whose control objective is composed of system output and its desired value. The basic control law of RNPC is derived such that the future response of the system is first predicted by appropriate functional expansions and the control law minimizing the difference between the predicted and desired responses is then calculated. RNPC which involves two controls, i.e., the auxiliary and robust controls into the basic control, shows the stable closed loop dynamics of nonlinear system of any relative degree and provides the robustness to the nonlinear system with parameter/modeling uncertainty. Simulation tests for the position control of a two-link rigid body manipulator confirm the performance improvement and the robustness of RNPC.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.189-195
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• 2000

The mathematical solutions of the stability convergence are important problems in system control. In this paper such problems are analyzed and resolved for system control using multilayer neural networks. We describe an algorithm to control an unknown nonlinear system with a disturbance, using a multilayer neural network. We include a disturbance among the modeling error, and the weight update rules of multilayer neural network are derived to satisfy Lyapunov stability. The overall control system is based upon the feedback linearization method. The weights of the neural network used to approximate a nonlinear function are updated by rules derived in this paper . The proposed control algorithm is verified through computer simulation. That is as the weights of neural network are updated at every sampling time, we show that the output error become finite within a relatively short time.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.263-263
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• 2000

Electromagnetic Suspension(EMS) System produces no noise, friction and heat through non-contacting operation Therefore, the applicable device using EMS system has a lot of attraction in case of the high-speed and non-contacting transmission EMS with nonlinear properties requires a precise airgap position control and stable kinematics characteristics under the disturbances, In this study, the nonlinear system was linearized by a Nonlinear Feedback Lineariztion(NFL) method. The NFL method requires that the modelling should be exact, and the state variables should be measured and a rapidly operating controller be necessary on account of a heavy data calculating In the experiments. the ideal control characteristics of the NFL was acquired through simulation at first. then the characteristics of the actual system were compared with those of simulation. In addition, the results by NFL were examined and analysed considering the characteristics of the PID control. The Control by NFL shows much stable control characteristics than the PID control. Whereas, the steady state errors occur for various disturbances. hence a robust control design is remained for a further study.