• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.11
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• pp.505-513
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• 2001

This paper presents the new three-level optimal control scheme for the large scale nonlinear systems, which is based on fast walsh transform. It is well known that optimization for nonlinear systems leads to the resolution of a nonlinear two point boundary value problem which always requires a numerical iterative technique for their solution. However, Three-level costate coordination can avoid two point boundary condition in subsystem. But this method also has the defect that must solve high order differential equation in intermediate level. The proposed method makes use of fast walsh transform, therefore, is simple in computation because of solving algebra equation instead of differential equation.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.

• Smart Structures and Systems
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• v.31 no.1
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• pp.69-78
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• 2023

The purpose of this paper is to develop a scalable grey predictive controller with unavoidable random delays. Grey prediction is proposed to solve problems caused by incorrect parameter selection and to eliminate the effects of dynamic coupling between degrees of freedom (DOFs) in nonlinear systems. To address the stability problem, this study develops an improved gray-predictive adaptive fuzzy controller, which can not only solve the implementation problem by determining the stability of the system, but also apply the Linear Matrix Inequality (LMI) law to calculate Fuzzy change parameters. Fuzzy logic controllers manipulate robotic systems to improve their control performance. The stability is proved using Lyapunov stability theorem. In this article, the authors compare different controllers and the proposed predictive controller can significantly reduce the vibration of offshore platforms while keeping the required control force within an ideal small range. This paper presents a robust fuzzy control design that uses a model-based approach to overcome the effects of modeling errors. To guarantee the asymptotic stability of large nonlinear systems with multiple lags, the stability criterion is derived from the direct Lyapunov method. Based on this criterion and a distributed control system, a set of model-based fuzzy controllers is synthesized to stabilize large-scale nonlinear systems with multiple delays.

• Advances in aircraft and spacecraft science
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• v.9 no.6
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• pp.553-569
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• 2022

In this article, we propose a criterion for ensuring the asymptotic stability of large multiple delays, based on the direct Lyapunov method. Based on this criterion and distributed control scheme, the controllers are synthesized by the PDC to stabilize these large-scale systems with multiple delays. And we focus on the results which shows the high effective by the proposed theory utilized for damage propagation for aircraft structural analysis of composite materials. Finally, the numerical simulations confirmed the effectiveness of the method.

• Smart Structures and Systems
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• v.4 no.5
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• pp.667-684
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• 2008

Numerous devices exist for reducing or eliminating seismic damage to structures. These include passive dampers, semi-active dampers, and active control devices. The performance of structural systems with these devices has often been evaluated using numerical simulations. Experiments on structural systems with these devices, particularly at large-scale, are lacking. This paper describes a real-time hybrid testing facility that has been developed at the Lehigh University NEES Equipment Site. The facility enables real-time large-scale experiments to be performed on structural systems with rate-dependent devices, thereby permitting a more complete evaluation of the seismic performance of the devices and their effectiveness in seismic hazard reduction. The hardware and integrated control architecture for hybrid testing developed at the facility are presented. An application involving the use of passive elastomeric dampers in a three story moment resisting frame subjected to earthquake ground motions is presented. The experiment focused on a test structure consisting of the damper and diagonal bracing, which was coupled to a nonlinear analytical model of the remaining part of the structure (i.e., the moment resisting frame). A tracking indictor is used to track the actuator ability to achieve the command displacement during a test, enabling the quality of the test results to be assessed. An extension of the testbed to the real-time hybrid testing of smart structures with semi-active dampers is described.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.226-228
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• 2007

This paper proposes Nonlinear Interior Point Method (NIPM) including discrete control variables optimal power flow formulations. The algorithm utilizes the robustness in terms of starting point and fast convergence for large scale power system of NIPM and an introduction of rounding penalty function which is augmented in the Lagrangian function to handle discrete control variables. The derived formulation shows a simplified approach to deal with discrete control problems which is implementable in real large scale systems.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.694-695
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• 2011

The recent concerns over the threat of global climate change and the requirements of national reduction of $CO_2$ emission have led to the diversification of energy resources and a large scale integration of renewable resources. In these circumstances, the policy decision currently made by the government sector includes several programs to promote the equipment of large scale generating assets to use wind energy. However, the power systems and wind farms need such innovative operation scheme schemes that maintain an adequate level of system security for continuing growth of renewable resources. This paper presents a method for determining optimal operating points for wind farms by making use of a nonlinear interior point method.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.277-288
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• 2014

This article reviews various state estimation methods for nonlinear systems, particularly with a perspective of a process control engineer. Nonlinear state estimation methods can be classified into the following two categories: stochastic approaches and deterministic approaches. The current review compares the Bayesian approach, which is mainly a stochastic approach, and the MHE (Moving Horizon Estimation) approach, which is mainly a deterministic approach. Though both methods are reviewed, emphasis is given to the latter as it is particularly well-suited to highly nonlinear systems with slow sampling rates, which are common in chemical process applications. Recent developments in underlying theories and supporting numerical algorithms for MHE are reviewed. Thanks to these developments, applications to large-scale and complex chemical processes are beginning to show up but they are still limited at this point owing to the high numerical complexity of the method.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.185-189
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• 1987

An analysis and design of large-scale linear multivariable systems often requires to be block triangularized form for good sensitivity of the systems when their poles and zeros are varied. But the decomposition algorithms presented up to now need a procedure of permutation, rescaling and a solution of nonlinear algebraic equations, which are usually burden. To avoid these problem, in this paper we develop a newly alternative block triangular decomposition algorithm which used the generalized matrix sign function on the Z-plane. Also, the decomposition algorithm demonstrated using the fifth order linear model of a distillation tower system.

• Smart Structures and Systems
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• v.26 no.3
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• pp.373-390
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• 2020

Hybrid simulation (HS) is a versatile tool for structural performance evaluation under dynamic loads. Although real structural responses are often multiple-directional owing to an eccentric mass/stiffness of the structure and/or excitations not along structural major axes, few HS in this field takes into account structural responses in multiple directions. Multi-directional loading is more challenging than uni-directional loading as there is a nonlinear transformation between actuator and specimen coordinate systems, increasing the difficulty of suppressing loading error. Moreover, redundant actuators may exist in multi-directional hybrid simulations of large-scale structures, which requires the loading strategy to contain ineffective loading of multiple actuators. To address these issues, lately a new strategy was conceived for accurate reproduction of desired displacements in bi-directional hybrid simulations (BHS), which is characterized in two features, i.e., iterative displacement command updating based on the Jacobian matrix considering nonlinear geometric relationships, and force-based control for compensating ineffective forces of redundant actuators. This paper performs performance validation and application of this new mixed loading strategy. In particular, virtual BHS considering linear and nonlinear specimen models, and the diversity of actuator properties were carried out. A validation test was implemented with a steel frame specimen. A real application of this strategy to BHS on a full-scale 2-story frame specimen was performed. Studies showed that this strategy exhibited excellent tracking performance for the measured displacements of the control point and remarkable compensation for ineffective forces of the redundant actuator. This strategy was demonstrated to be capable of accurately and effectively reproducing the desired displacements in large-scale BHS.