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

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.11
• /
• pp.928-934
• /
• 2002

A natural way to cope with fault tolerant control (FTC) problems is to modify the control parameters according to an online identification of the system parameters when a fault occurs. However. due to not only difficulties Inherent to the online multivariable identification in closed-loop systems, such as modeling errors, noise or the lack of excitation signals, but also long time requirement to identify the post-fault system and implemeutation of control problems during the identification process, we propose an alternative approach based on the observer-based fault detection and isolation (FDI) and model reference adaptive control (MRAC). The proposed robust fault diagnosis method is based on a bank of observers. We also propose a model reference adaptive control with changeable reference models according to the occurred faults. Simulation results of a flight control example show the validity and applicability of the proposed algorithms.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.296-298
• /
• 1993

In this paper, a new design procedure is proposed for constructing the observer for linear discrete-time systems with unknown inputs. An existence condition for the suggested observer is also presented. The observer design procedure does not use any transformation technique, augmentation technique and has a clear physical meaning, so it is easy to understand and to design the observer. It directly estimates the unknown inputs from that outputs only, so it is different from other pre-works in which the reconstruction of the unknown inputs arc performed with the additional output derivatives.

• Proceedings of the KIEE Conference
• /
• 2005.07d
• /
• pp.2543-2545
• /
• 2005

It is well known that the orthogonal function is a very useful to estimate an unknown inputs in the linear dynamic systems for its recursive algebraic algorithm. At this aspects, derivative operation(matrix) of orthogonal functions(walsh, block pulse and haar) are introduced and shown how it can useful to design an UIO(unknown inputs observer) design.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2086-2088
• /
• 2002

This paper deals with an algebraic approach for unknown inputs observer by using Haar functions. In the algebraic UIO(unknown input observer) design procedure, coordinate transformation method is adopted to derive the reduced order dynamic system which is decoupled unknown inputs and Haar function and its integral operational matrix is applied to avoid additional differentiation of system outputs.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.3
• /
• pp.207-214
• /
• 2010

This paper proposes about decentralized control approach based Leader-Follower formation control using LOS (Line of Sight) algorithm and unknown input observer. The position of robots which is a basic information in multi-robot or single robot motion control is determined by localization algorithm fusing UPS (Ultrasonic Position System) and kinematics model. For formation control, a decentralized control approach individually installing a local controller in leader and follower robot is adopted. Leader robot is controlled to track a specified trajectory by LOS algorithm, and the other robots follow the leader by local controller based on tracking platoon level function, self-sensing data and estimated information from unknown input observer. The performance of proposed method is proven through the formation experiment of two vehicle models.

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

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1149-1151
• /
• 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
• /
• v.39 no.1
• /
• pp.36-48
• /
• 1990

A new control method for robust position control of brushless dc motor is presented. The model of brushless dc motor is approximately linearized by field-orentation method, and it is shown that augmented state variable feedback can be applied to this system. In addition, robustness is obtained without any change of overall system response. Load disturbance is detected by 0-observer of unknown and inaccessible input, and is compensated by feedforward which has fast response. Overall system is controlled by using the MC68000 microprocessor, and the performance of the proposed control algorithm is verified by the results of simulation and experiment.

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