• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.11
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• pp.760-767
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• 2004

In this paper, we propose sufficient conditions under which nonlinear systems can be transformed into nonlinear observer canonical form in the extended state space by virtue of dynamic system extension. The proposed scheme weakens two major restrictions of observer error linearization technique. Once a nonlinear system is transformed into nonlinear observer canonical form using dynamic system extension, a state observer can be easily designed. Two illustrative examples are included in order to compare the proposed scheme and observer error linearization method.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.973-975
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• 1998

For a nonlinear feedback linearization-full order observer/sliding mode controller (NFL-FOO/SMC), the separation principle is derived, and the closed-loop stability is proved by a Lyapunov function candidate using an addition form of the sliding surface vector and the estimation error.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.985-987
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• 1998

This paper presents a stability proof for the nonlinear feedback linearization-full order observer-based sliding mode controller (NFL-FOO-based SMC). The closed-loop stability is proved by a Lyapunov function candidate using an addition form of the sliding surface vector and the estimation error.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.976-978
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• 1998

This paper presents the stability proof of a nonlinear feedback linearization-reduced order observer/sliding mode controller (NFL-ROO/SMC). The closed-loop stability is proved by a Lyapunov function candidate using an addition form of the sliding surface vector and the estimation error.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.979-981
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• 1998

This paper presents a stability proof for the nonlinear feedback linearization-observer/sliding mode model following controller (NFL-O/SMMFC). The separation principle is derived, and the closed-loop stability is proved by a Lyapunov function candidate using an addition form of the sliding surface vector and the estimation error.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.988-990
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• 1998

This paper presents the stability proof of a nonlinear feedback linearization-reduced order observer-based sliding mode controller (NFL-ROO-based SMC). The closed-loop stability is proved by a Lyapunov function candidate using an addition form of the sliding surface vector and the estimation error.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.991-993
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• 1998

This paper presents a stability proof for the nonlinear feedback linearization-observer-based sliding mode model following controller (NFL-O-based SMMFC). The closed-loop stability is proved by a Lyapunov function candidate using an addition form of the sliding surface vector and the estimation error.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.483-487
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• 1996

We consider the estimation of the position and orientation of 6 DOF motion bed (Stewart platform) from the measured cylinder length. The solution of forward kinematics is not solved yet as a useful realtime application tool because of the complity of the equation with multiple solutiple solutions. Hence we suggest an algorithm for the estimation of forward kinematics solution using Luenberger observer withnonlinear error correction term. The Luenberger observer withlinear model shows that the estimation error does not go to zero in steadystate due to the linearization error of the dynamic model. Hence the linear observer is modified using nonlinear measurement error equation and we prove thd practical stability of the estimation error dynamics of the proposed observer using lyapunov function.

• 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.

• 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