• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.377-384
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• 2007

This paper studies on the relation between linearization methods and controller gains in the looper ILQ(lnverse Linear Quadratic optimal control) system for hot strip finishing mills. Firstly, two linear models arc respectively derived by a linearization method using Taylor's series expansion and a static state feedback linearization method, respectively, and the linear models are compared with the nonlinear model. Secondly, the looper servo controllers are respectively designed on the basis of two linearization models. Finally, the relation between the performances of two ILQ servo controllers and the linearization methods, and the structures and control gains of two controllers are evaluated by a computer simulation.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.4
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• pp.108-118
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• 2006

The purpose of this study is to investigate the effectiveness of a LQG Hybrid controller to suppress the earthquake disturbance for the building structure. The ground acceleration of N-S component of El-Centro earthquake was scaled to confirm that the building behaved within the elastic range. The tuned mass damper(TMD) on the top floor regulated by LQG algorithm was designed to control the floor displacements. The displacement responses of the hybrid control were compared with those obtained from an active control along with a passive control. The results showed that the LQG hybrid control used approximately 50% less input forces than an active control to satisfy the performance criteria.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.8
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• pp.1680-1689
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• 2002

This paper studies on the design of a looper control system for hot strip mill finisher using ILQ(Inverse Linear Quadratic optimal control) control method. The loopers are placed between each rolling stands and looper control plays an important role in regulating strip tension. The strip tension is controlled by raising and lowering the looper and by changing the speed of main work rolls. Firstly, it is shown from a nonlinear dynamic simulation that the strip tension is more influenced by difference of rolling speed than that of the looper angle. Secondly, a servo controller of the looper is designed using ILQ control method of which the characteristics and algorithms are simply introduced. Finally, the performances of the ILQ servo controller are compared with those of the LQI servo controller from computer simulation. In result, it is shown that the proposed ILQ servo controller has the better performances and robustness far parameter perturbations and disturbances than those of LQI controller.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.49 no.2
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• pp.153-160
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• 2013

Control allocation is an important part of a system. It implements the function that map the desired command forces from the controller into the commands of the different actuators. In this paper, the authors present an approach for solving constrained control allocation problem in vessel system by using multi-parametric quadratic programming (mp-QP) algorithm. The goal of mp-QP algorithm applied in this study is to compute a solution to minimize a quadratic performance index subject to linear equality and inequality constraints. The solution can be pre-computed off-line in the explicit form of a piecewise linear (PWL) function of the generalized forces and constrains. The efficiency of mp-QP approach is evaluated through a dynamic positioning simulation for a vessel by using four tugboats with constraints about limited pushing forces and found to work well.

• Structural Engineering and Mechanics
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• v.65 no.6
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• pp.721-730
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• 2018

This paper aims to inspect the effectiveness of the Simple Adaptive Control Method (SACM) to control the response of asymmetric buildings with rotationally non-linear behavior under seismic loads. SACM is a direct control method and was previously used to improve the performance of linear and non-linear structures. In most of these studies, the modeled structures were two-dimensional shear buildings. In reality, the building plans might be asymmetric, which cause the buildings to experience torsional motions under earthquake excitation. In this study, SACM is used to improve the performance of asymmetric buildings, and unlike conventional linear models, the non-linear inertial coupling terms are considered in the equations of motion. SACM performance is compared with the Linear Quadratic Regulator (LQR) algorithm. Moreover, the LQR algorithm is modified, so that it is appropriate for rotationally non-linear buildings. Active tuned mass dampers are used to improve the performance of the modeled buildings. The results show that SACM is successful in reducing the response of asymmetric buildings with rotationally non-linear behavior under earthquake excitation. Furthermore, the results of the SACM were very close to those of the LQR algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.828-834
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• 2014

This paper presents a comparison among three types of approaches to an ARC (Active Roll Control) with an AARB(Active Anti-Roll Bar) for a vehicle system. Lateral acceleration and road profile are considered as disturbance. The ARC is designed with an LQ SOF (Linear Quadratic Static Output Feedback) control, $H_{\infty}$ control and SMC (Sliding Mode Control). These approaches are compared in terms of rollover prevention and ride comfort. For comparison, Bode plot analysis based on linear model and frequency response analysis based on CarSim simulation are performed.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.845-858
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• 2008

In this paper, we consider a terminal, linear control system with delay, subject to unknown but bounded disturbances. For this system, we consider the problem of constructing a worst-case optimal feedback control policy, which can be corrected at fixed, intermediate time instants. The policy should guarantee that for all admissible uncertainties the system states are in prescribed neighborhoods of predefined system states, at all fixed, intermediate time instants, and in the neighborhood of a given state at a terminal time instant, and the value of the cost function is the best guaranteed value. Simple explicit rules(which can be easily implemented on-line) for constructing the optimal control policy in the original control problem are derived.

• Smart Structures and Systems
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• v.10 no.1
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• pp.15-31
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• 2012

This study proposes an active control method to suppress beam-rotating machinery system vibrations. The present control method is a combination of the fuzzy input estimation method (FIEM) and linear quadratic Gaussian problem (LQG) algorithms. The FIEM can estimate the unknown input and optimal states by measuring the dynamic displacement, the optimal estimated states into the feedback control; thereby obtaining the optimal control force for a random linear system. Active vibration control of a beam-rotating machinery system is performed to verify the feasibility and effectiveness of the proposed algorithm. The simulation results demonstrate that the proposed method can suppress vibrations in a beam-machine system more efficiently than the conventional LQG method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2548-2551
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• 2005

In this paper, a robust receding horizon finite impulse response(FIR) filter is proposed for a class of linear discrete time systems with uncertainty satisfying an integral quadratic constraint. The robust state estimation problem involves constructing the set of all possible states at the current time consistent with given system input, output measurements and the integral quadratic constraint.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.432-435
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• 1995

In this paper a new approach to obtain the solution of the linear-quadratic Gaussian control problem for singularly perturbed discrete-time stochastic systems is proposed. The alogorithm proposed is based on exploring the previous results that the exact solution of the global discrete algebraic Riccati equations is found in terms of the reduced-order pure-slow and pure-fast nonsymmetric continuous-time algebraic Riccati equations and, in addition, the optimal global Kalman filter is decomposed into pure-slow and pure-fast local optimal filters both driven by the system measurements and the system optimal control input. It is shown that the optimal linear-quadratic Gaussian control problem for singularly perturbed linear discrete systems takes the complete decomposition and parallelism between pure-slow and pure-fast filters and controllers.