• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.326-329
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• 1995

PID control has been widely used for real control system Further, there are muchreasearches on control schemes of tuning PID gains. However, there is no results for discrete-time systems with unknown time-dealy and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown parameters and unknown tiem-delay system. A numerical simulation was presented to illuatrate the effectiveness of this method.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.205-211
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• 2002

Unknown inputs observer(UIO) which is achieved by the coordinate transformation method has the differential of system outputs in the observer and the equation for unknown inputs estimation. Generally, the differential of system outputs in the observer can be eliminated by defining a new variable. But it brings about the partition of the observer into two subsystems and need of an additional differential of system outputs still remained to estimate the unknown inputs. Therefore, the block pulse function expansions and its differential operation which is a newly derived in this paper are presented to alleviate such problems from an algebraic form.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.77-82
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• 2001

This paper deals with a fault detection algorithm for linear descriptor systems via unknown input PI observer. An unknown input PI observer is presented and its realization conditions is proposed by using the rank condition of system matrices. From the characteristics of unknown input PI observer, the states of system with unknown inputs are estimated and the occurrences of fault are detected, and its magnitudes are estimated easily by using integrated output estimation error under the step faults. Finally, a numerical example is given to verify the effectiveness of the proposed fault detection algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.452-452
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• 2000

This paper deals with a fault detection algorithm for linear descriptor systems via unknown input PI observer. An unknown input PI observer is presented and its realization conditions is proposed by using the rank condition of system matrices. From the characteristics of unknown input PI observer, the states of system with unknown inputs are estimated and the magnitude of failures are detected and isolated easily by using integrated output error under the step failures. Finally, a numerical example is given to verify the effectiveness of the proposed algorithm.

• Smart Structures and Systems
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• v.15 no.1
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• pp.57-80
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• 2015

Extended Kalman Filter (EKF) has been widely used for structural identification and damage detection. However, conventional EKF approaches require that external excitations are measured. Also, in the conventional EKF, unknown structural parameters are included as an augmented vector in forming the extended state vector. Hence the sizes of extended state vector and state equation are quite large, which suffers from not only large computational effort but also convergence problem for the identification of a large number of unknown parameters. Moreover, such approaches are not suitable for intelligent structural damage detection due to the limited computational power and storage capacities of smart sensors. In this paper, a two-stage and two-step algorithm is proposed for the identification of structural damage as well as unknown external excitations. In stage-one, structural state vector and unknown structural parameters are recursively estimated in a two-step Kalman estimator approach. Then, the unknown external excitations are estimated sequentially by least-squares estimation in stage-two. Therefore, the number of unknown variables to be estimated in each step is reduced and the identification of structural system and unknown excitation are conducted sequentially, which simplify the identification problem and reduces computational efforts significantly. Both numerical simulation examples and lab experimental tests are used to validate the proposed algorithm for the identification of structural damage as well as unknown excitations for structural health monitoring.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.170-174
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• 2014

In this paper, an unknown input estimation method via the optimal FIR smoother is proposed for linear discrete-time systems. The unknown inputs are represented by random walk processes and treated as auxiliary states in augmented state space models. In order to estimate augmented states which include unknown inputs, the optimal FIR smoother is applied to the augmented state space model. Since the optimal FIR smoother is unbiased and independent of any a priori information of the augmented state, the estimates of each unknown input are independent of the initial state and of other unknown inputs. Moreover, the proposed method can be applied to stochastic singular systems, since the optimal FIR smoother is derived without the assumption that the system matrix is nonsingular. A numerical example is given to show the performance of the proposed estimation method.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2086-2088
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• 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 the Korea Convergence Society
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• v.4 no.4
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• pp.41-48
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• 2013

Observer design for system with unknown input was carried out. First, Kalman filter was considered to estimate system state with White noise. With the results of Kalman filter design, state observer, controller properties, including controllability and observability, and the Kalman filter structure and algorithm were also studied. Kalman filter algorithm was applied to Position and velocity measurement based on Kalman filter with white noise, and it was constructed and achieved by programming based on Matlab programming. Finally, observer for system with unknown input was constructed with the help of Gershgorin's disc theorem. With the designed observer, system states was constructed and applied to system with unknown input. By simulation results, estimation performance was verified. In this project, state feedback control theory, observer theory and relevant design procedure, as well as Kalman filter design were understood and used in practical application.

• The KIPS Transactions:PartB
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• v.14B no.3 s.113
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• pp.231-240
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• 2007

In this paper, we propose an automatic extraction model for unknown translations and implement an unknown translation extraction system using the proposed model. The proposed model as a phrase-alignment model is incorporated with three models: a phrase-boundary model, a language model, and a translation model. Using the proposed model we implement the system for extracting unknown translations, which consists of three parts: construction of parallel corpora, alignment of Korean and English words, extraction of unknown translations. To evaluate the performance of the proposed system we have established the reference corpus for extracting unknown translation, which comprises of 2,220 parallel sentences including about 1,500 unknown translations. Through several experiments, we have observed that the proposed model is very useful for extracting unknown translations. In the future, researches on objective evaluation and establishment of parallel corpora with good quality should be performed and studies on improving the performance of unknown translation extraction should be kept up.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.193-193
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• 2000

This paper proposes a dynamic observer that is applicable to linear time-invariant systems subject to unknown input, The proposed method utilities Che output feedback control structure to design unknown input observer. We name it as the dynamic unknown input observer(UIO). The dynamic UIO can be designed easily over the usual static UIO, and the system response could be improved.