• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1188-1194
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• 1997

In this paper, we design output feedback nonlinear dynamic control law by using state feedback nonlinear dynamic compensator and PI observer and show that the controller can stabilize globally and asymptotically a class of nonlinear systems with mismatched uncertainties. We also show that it is possible for a nonlinear system to use the output of PI observer in place of state variables in case that the nonlinear dynamic control law is used, similarly as in the linear system. The effectiveness of the proposed control law is demonstrated by a numerical simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1184-1184
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• 1997

In this paper, we design output feedback nonlinear dynamic control law by using state feedback nonlinear dynamic compensator and PI observer and show that the controller can stabilized globally and asymptotically a class of nonlinear systems with mismatched uncertainties. We also show that it is possible for a nonlinear system to use the output of PI observer in place of state variables in case that the nonlinear dynamic control law is used, similarly as in the linear system. The effectiveness of the proposed control law is demonstrated by a numerical simulation.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.307-310
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• 2006

We consider the problem of constructing observers for nonlinear systems with unknown inputs. It is shown that under some conditions, there exists an observer estimating the states of nonlinear systems with unknown inputs. Nonlinear observer design method using observer error linearization and the design technique of unknown input observer(UIO) for linear systems are used to derive conditions. Some illustrative examples are included. In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller.The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.451-457
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• 2015

In this paper, we consider the observer design problem that truly reflects the nonlinear stiffness of the manipulators. The two key ideas of our design are that (a) estimation error dynamics of the manipulator equipped with accelerometer dose not dependent on nonlinearities at the link part, when the measured signals are the motor position and the output of the accelerometer and (b) the nonlinear stiffness is indeed a Lipschitz function. In order to effectively compensate the nonlinear stiffness, the gain of the proposed observer is carefully chosen from the ARE(algebraic Riccati equations) which depend on Lipschitz constant. Comparative simulation result verifies the effectiveness of the proposed solution.

• Journal of IKEEE
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• v.22 no.1
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• pp.121-126
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• 2018

This paper addresses the consensus problem for nonlinear multi-agent systems using observer based controller. In order to solve this problem, the high gain approach is combined with the previous low gain controller. Also, it is shown that the proposed observer based controller can always guarantee the consensus of nonlinear systems with lower triangular nonlinearity.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.116-122
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• 2001

A novel approach based on WaveARX neural network observer is proposed far the fault detect of a class of nonlinear systems which consist of known linear part and unknown nonlinear part. A linear observer is first designed, then a nonlinear compensation term in the nonlinear observer is estimated by using a deconvolution method. The WaveARX network is used to model the obtained compensation term. At last, the residual fur fault detection is generated based on the analysis of the upper bound approximate error. Simulation results have shown the feasibility and effectiveness of the method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.816-822
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• 2014

The estimation of the angular rate of a satellite has been discussed. A nonlinear observer has been proposed based on the state-dependent Riccati equation method. A sufficient stability condition for the convergence of estimation error has been presented. This condition is related to a state-dependent algebraic Riccati equation. It has been derived by transforming nonlinear error dynamics into a Lipschitz nonlinearity. An observer gain is obtained from this condition. Numerical simulations are presented to verify the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.666-671
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• 2017

A disturbance-observer-based adaptive neural tracker design problem is investigated for a class of perturbed uncertain non-affine nonlinear systems with unknown control direction. A nonlinear disturbance observer (NDO) design methodology using neural networks is presented to construct a tracking control scheme with the attenuation effect of an external disturbance. Compared with previous control results using NDO for nonlinear systems in non-affine form, the major contribution of this paper is to design a NDO-based adaptive tracker without the sign information of the control coefficient. The stability of the closed-loop system is analyzed in the sense of Lyapunov stability.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.237-239
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• 2004

이 논문에서는 Nonlinear Observer Backstepping 출력 궤환 제어에 의한 비선형 전력계통안정화장치(NPSS)를 개발하였다. 이 기법은 출력단자의 측정만으로 매우 강한 전력계통의 고유한 특징인 강한 비선형을 처리할 수 있는 바람직한 제어기를 구성할 수가 있다. 첫 번째로 비선형 관측기를 통하여 측정할 수 없는 부분의 상태들을 대신할 수 있는 출력 궤환 관측기를 구성하는 것이다. 두 번째로 이렇게 구성된 관측기에 매번 상태를 반영할 수 있는 backstepping 제어기를 적응하는 것이다. 시뮬레이션을 통한 제안된 제어기의 효과는 비 제어시, 기존의 Lead-Lag PSS, 그리고 제안된 Nonlinear Observer backstepping 출력 궤환 제어에 기준한 비선형 PSS를 비교 검토하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.533-536
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• 2014

In this paper, a near optimal decentralized observer-controller design method is proposed for ramp metering systems based on SDRE (State Dependent Riccati Equation) approach. The optimal nonlinear observer gain is parameterized in terms of the solution matrix of an SDRE. This paper gives a simple algorithm to compute the near optimal observer gain. The optimal control design problem is also considered. Finally, numerical simulation results are given to illuminate the effectiveness and practicality of the proposed design method.