• Journal of Sensor Science and Technology
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• v.28 no.4
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• pp.216-220
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• 2019

In this paper, we propose a finite memory filter (estimator) for discrete-time stochastic linear systems with delays in state and measurement. A novel filtering algorithm is designed based on finite memory strategies, to achieve high estimation accuracy and stability under parametric uncertainties. The new finite memory filter uses a set of recent observations with appropriately chosen initial horizon conditions. The key contribution is the derivation of Lyapunov-like equations for finite memory mean and covariance of system state with an arbitrary number of time delays. A numerical example demonstrates that the proposed algorithm is more robust and accurate than the Kalman filter against dynamic model uncertainties.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.366-370
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• 2005

The construction environment is dynamic in nature and is characterized by various degrees of uncertainties. The uncertainties such as lack of coordination, non availability of resources, condition of temporary structures and varying weather conditions have a significant impact on estimating the duration of activities. These are subjective, vague and imprecisely defined and are expressed in subjective measures rather than mathematical terms. Conventionally, various quantitative techniques such as CPM and PERT have emerged in construction industry. These techniques cannot solve the above problems and rely on human experts which may not always be possible. In such situations Artificial Intelligence tools such as fuzzy sets and neural networks handle such variables and provide global strategies. The present paper evaluates the effect of qualitative factors to identify the activity duration using new intelligent approach. The results are compared with conventional methods for effective project management. A case study is considered to demonstrate the applicability of fuzzy logic for project scheduling.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.929-934
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• 2005

The complex and dynamic job nature and the ever-changing working environment of construction projects inevitably present uncertainties to construction operations. Identification, evaluation and control of uncertainties constitute main elements of risk management and critical tasks of project management in construction. This paper is focused on application of a simplified discrete-event simulation approach in management of schedule-overrun risks, each being the combination of the occurrence probability of an uncertain interruptive factor and its potential consequence in terms of time delay. A case study observed from a concreting operation in Hong Kong is converted into a simulation model and analyzed with an in-house-developed simulation package for demonstrating how the proposed approach can be implemented to manage multiple schedule-overrun risks on construction projects.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.227-233
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• 1996

The Inverted Pendulum has been one of most popular nonlinear dynamic systems for the exploration of control techniques. This paper presents a new linear optimal control techniques and nonlinear neural network learning methods. The multiayered neural networks are used to add nonlinear effects on the linear optimal regulator(LQR). The new regulator can compensate nonlinear system uncertainties that are not considered in the LQR design, and can tolerated a wider range of uncertainties than the LQR alone. The new regulator has two neural networks for modeling and control. The neural network for modeling is used to obtain a more accurate model than the given mathematical equations. The neural network for control is used to overcome deficiencies by adding corrections to the linear coefficients of the LQR and by adding nonlinear effects on the LQR. Computer simulations are performed to show the applicability and a more robust regulator than the LQR alone.

• Journal of Industrial Technology
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• v.24 no.A
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• pp.215-226
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• 2004

A dynamic reliability model which can take into account the time history of loading sequences may be applied to the analyses of the hydraulic stability of armor units on rubble-mound breakwaters. All the parameters related to the stability of structures have been considered to be constants in the deterministic model until now. Thus, it is impossible to study the effects of some uncertainties of the related random variables on the stability of structures. In this paper, the dynamic reliability model can be developed by POT(Peak Over Threshold) method in order to take into account the time history of loading sequences and to investigate the temporal behaviors of stability of structure with its loading history. Finally, it is confirmed that the results of dynamic reliability model agree with straight- forwardly those of AFDA(Approximate Full Distribution Approach) of the static reliability model for the same input conditions. In addition, the temporal behaviors of probability of failure can be studied by the dynamic reliability model developed to analyze the hydraulic stability of armor units on rubble-mound breakwaters. Therefore, the present results may be useful for the management of repair and maintenance over the whole life cycle of structure.

• Steel and Composite Structures
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• v.20 no.2
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• pp.317-335
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• 2016

Concentrically braced steel frames (CBFs) can be optimised during the seismic design process by using lateral loading distributions derived from the concept of uniform damage distribution. However, it is not known how such structures are affected by uncertainties. This study aims to quantify and manage the effects of structural and ground-motion uncertainty on the seismic performance of optimum and conventionally designed CBFs. Extensive nonlinear dynamic analyses are performed on 5, 10 and 15-storey frames to investigate the effects of storey shear-strength and damping ratio uncertainties by using the Monte Carlo simulation method. For typical uncertainties in conventional steel frames, optimum design frames always exhibit considerably less inter-storey drift and cumulative damage compared to frames designed based on IBC-2012. However, it is noted that optimum structures are in general more sensitive to the random variation of storey shear-strength. It is shown that up to 50% variation in damping ratio does not affect the seismic performance of the optimum design frames compared to their code-based counterparts. Finally, the results indicate that the ground-motion uncertainty can be efficiently managed by optimizing CBFs based on the average of a set of synthetic earthquakes representing a design spectrum. Compared to code-based design structures, CBFs designed with the proposed average patterns exhibit up to 54% less maximum inter-storey drift and 73% less cumulative damage under design earthquakes. It is concluded that the optimisation procedure presented is reliable and should improve the seismic performance of CBFs.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.508-513
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• 2003

This paper is concerned with a mixed control with aerodynamic fin and side thrusters applied to an agile missile using two-time scale dynamic inversion and linear time-varying control technique. The nonlinear dynamic inversion method with the weighting function allocates the desired control inputs (aerodynamic fin and side thrusters) to track a reference trajectory, and the time-varying control technique guarantees the robustness for the uncertainties. Closed-loop stability is achieved by the assignment of the extended-mean of these linear time-varying eigenvalues to the left half complex plane. The proposed schemes are validated by nonlinear simulations.

• Journal of the Korean Mathematical Society
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• v.48 no.4
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• pp.775-795
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• 2011

The disturbance attenuation problem for a class of discretetime switched linear systems with exponential uncertainties via switched state feedback and switched dynamic output feedback is investigated, respectively. By using Taylor series approximation and convex polytope technique, exponentially uncertain discrete-time switched linear system is transformed into an equivalent switched polytopic model with additive norm bounded uncertainty. For such equivalent switched model, one designs its switching strategy and associated state feedback controllers and dynamic output feedback controllers so that whole switched model is asymptotical stabilization with H-in nity disturbance attenuation base on switched Lyapunov function and LMI approach. Finally, two numerical examples are presented to illustrate our results.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.65-68
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• 1996

Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. The TMS32OC31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the, network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time, control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1871-1876
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• 2005

In this paper, We present a new nonlinear adaptive control law using a disturbance accommodating control (DAC) observer for a Japanese automatic landing flight experiment vehicle called ALFLEX. A future spaceplane must have ability to deal with greater fluctuations in the stability and control derivatives of flight dynamics, because its flight region is much wider than that of conventional aircraft. In our previous studies, digital adaptive flight control systems have been developed based on a linear-parameter-varying (LPV) model depending on dynamic pressure, and obtained good simulation results. However, under previous control laws, it is difficult to accommodate uncertainties represented by disturbance and nonlinearity, and to design a stable flight control system. Therefore, in this study, we attempted to design a nonlinear adaptive control law using the DAC Observer and inverse dynamic methods. A good tracking property of the obtained system was confirmed in numerical simulation.