• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.578-580
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• 1997

A new method of Fault Diagnosis in linear systems using unknown input observer design technique is presented. This method is based upon the fact that the structural uncertainties, actuator faults, and sensor faults of a linear system can be rewritten in unknown inputs. The proposed method can simultaneously estimate the state variables of an actual system, as well as the actuator and sensor faults.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.927-929
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• 1996

In this paper, we considers the problem of designing an observer for bilinear systems with unknown input. A sufficient condition for the asymptotic stability of the proposed observer is derived by means of delectability, invariant zeros, and stable subspace. In sufficient condition, the bound which guarantees the asymptotic stability was derived, which based on the Lyapunov stability. And Observer existing conditions are suggested in various cases. Through a simple example, we derived the observer structure and the bound which guarantees the asymptotic stability.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.3
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• pp.117-126
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• 2003

This paper proposes a real-time application of Walsh functions which is based on the on-line Walsh transformation and on-line Walsh function's differential operation. In the existing method of orthogonal functions, a major disadvantage is that process signals need to be recorded prior to obtaining their expansions. This paper proposes a novel method of Walsh transformation to overcome this shortcoming. And the proposed method apply to the unknown inputs observer(UIO) design for linear time-invariant dynamical systems

• 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

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1432-1435
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• 1997

This paper proposes a fault detection and isolation metho by combining the parameter estimation method[4] with the observer method[2] to use merits of both methods. To verify the performance of the method proposed some simulations applied to remotely piloted vehicle are performed.

• 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.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1149-1151
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• 1996

In the last several years, considerable attention has been focused on the problem of designing observers for linear systems with unknown inputs. Since UIO(unknown inputs observer) has the derivative of the outputs, it is very sensitive to measurement noises. Therefore this note propose an algebraic approach to UIO design to alleviate the prescribed problems. Since the proposed method has simple form to estimate state and unknown input and robustness to sensor noise, we believe that it is very attractive in practice.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.625-631
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• 2011

This paper presents a discrete-time output feedback consensus algorithm for Multi-Agent Systems (MAS). Under the assumption that an agent is aware of the relative state information about its neighbors, a state feedback consensus algorithm is designed based on Linear Matrix Inequality (LMI) method. In general, however, it is possible to obtain its relative output information rather than the relative state information. To reconcile this problem, an Unknown Input Observer (UIO) is employed in this paper. To this end, first it is shown that the relative state information can be estimated using the UIO and the measured relative output information. Then a certainty-equivalence type output feedback consensus algorithm is proposed by combining the LMI-based state feedback consensus algorithm with the UIO. Finally, simulation results are given to illustrate that the proposed method successfully achieves the state consensus.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1300-1305
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• 1990

A VSS observer-based sliding mode control is described for continuous-time systems with uncertain nonlinear elements, in which the Euclidean norm of unknown element is bounded by a known value. For a case of complete state information, we first derive a sliding mode controller consisting of three parts: a linear state feedback control, an equivalent input and a min-niax control. It is then shown that the present attractiveness condition is simpler than that for a case without using the concept of equivalent input. We next design a VSS observer as a completely dual form to the sliding mode controller. Finally, we discuss a cas of incomplete state information by applying the VSS observer.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2611-2613
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• 2000

This paper deals with a novel approach to unknown inputs observer(UIO) design for linear time-invariant dynamical systems using a fast Walsh transform and Walsh function's differential operation. Generally, UIO has a derivation of system outputs which is not available from the measurement directly. And it is an obstacle to estimate the unknown inputs properly when unexpected measurement noises are presented. Therefore, this paper propose an algebraic approach to eliminate such problems by using a Walsh function's differential operation.