• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.57-64
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• 2015

In this paper, a model reference adaptive control (MRAC) scheme is applied for the precise and robust motion control of a pneumatic system with load variation. The reference model for MRAC is designed systematically using linear quadratic Gaussian control with loop transfer recovery (LQG/LTR). The sigmoid function of inverse velocity is used to compensate for the nonlinear friction force between the sliding parts. The experimental results show that MRAC effectively overcame the limit of the PID controller when there was unknown disturbance, including abrupt load variation and model uncertainty in the pneumatic control system.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.9
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• pp.71-81
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• 2001

This paper analyzes the effectiveness of minimizing vibration and sound transmission on/through a thin rectangular plate by both feedback control and hybrid control which combines adaptive feedforward control with a feedback loop. An experimental system identification technique using the matrix-fractional curve-fitting of the frequency response data is introduced for complex shaped structures. This identification technique reduces the model order o the MIMO(Multi-Input Multi-Output) system which simplifies the practical implementation. The adaptive feedforward control uses a Multiple filtered-x LMS(Least Mean Square) algorithm and the feedback control uses a multivariable digital LQG(Linear Quadratic Gaussian) algorithm. Experimental results show that an effective reduction of sound transmission is achieved by the hybrid control scheme when both vibration and noise measurement signals are incorporated in the controller.

• Journal of Mechanical Science and Technology
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• v.19 no.2
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• pp.540-548
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• 2005

This paper concerns the application and demonstration of sliding mode observer for aeroelastic system, which is robust to model uncertainty including mass and stiffness of the system and various disturbances. The performance of a sliding mode observer is compared with that of a conventional Kalman filter to demonstrate robustness and disturbance decoupling characteristics. Aeroelastic instability may occur when an elastic structure is moving even in subcritical flow speed region. Simulation results using sliding mode observer are presented to control aeroelastic response of flapped wing system due to various external excitations as well as model uncertainty and sinusoidal disturbances in subcritical incompressible flow region.

• Journal of KSNVE
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• v.6 no.6
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• pp.791-800
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• 1996

Linear LQG controller has been investigated to control flexible link manipulators. The performance and complexity of these depend largely on the model upon which the controller is designed. In this study, the flexible modes of the link manipulator are considered to have uncertain parameters, which can be represented by random variable and these parameters are reflected on the weighting of performance. In this method, the exact modelling for the flexible modes is not necessary. The order of the resulting controller is much lower than the one based on a full model. Through numerical study, it is shown that the performance and the stability-robustness of the proposed controller reaches reasonably the one based on the full model.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.1-4
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• 1995

We propose a new design method for a generalized predictive control (GPC) system based on the parametrization of two-degree-of freedom control systems. The objective is to design the GPC system which guarantees the stability of the control system for a perturbed plant. The design procedure of our proposed method consists of three steps. First, we design a basic controller for a nominal plant using the LQG method and parametrize a whole control system. Next, we identify the deviation between the perturbed plant and the nominal one using a closed-loop identification method and design a free parameter of parametrization to stabilize the closed-loop system. Finally, we design a feedforward controller so as to incorporate GPC technique into our controller structure. A numerical example is presented to show the effectiveness of our proposed method.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.263-272
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• 2000

In this paper we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastcic approximation method it is regarded as a stochastic recursive filter algorithm. In addition we provide a filtering and control condition for a stochastic nonlinear system called the perfect filtering condition in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable and the proposed neural controller is more efficient than the conventional LQG controller and the canonical LQ-Neural controller.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2005.03a
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• pp.388-395
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• 2005

This paper presents cost-effectiveness evaluation of semi-active control system for cable-stayed bridge under earthquake excitation. Bi-state control method with Linear Quadratic Gaussian(LQG) optimal controller is used for generic semi-active dampers. Cost-effectiveness of the structural control system is investigated by using the life-cycle cost(LCC) concept. The evaluation results show that the efficiency of semi-active control system is increased when the damage cost due to the failure of bridge system or the bridge importance is enlarged. It was also found that the damper cost had little influence on the cost-effectiveness of semi-active control system if it was relatively small to the initial construction cost.

• Proceedings of the KSR Conference
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• 2006.11a
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• pp.145-159
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• 2006

This paper describes the development of a clustering based fuzzy controller of an electromagnetic suspension vehicle using gain scheduling method and Kalman filter for a simplified single magnet system. Electromagnetic suspension vehicle systems are highly nonlinear and essentially unstable systems For achieving the levitation control of the DC electromagnetic suspension system, we considered a fuzzy system modeling method based on clustering algorithm which a set of input/output data is collected from the well defined Linear Quadratic Gaussian(LQG) controller. Simulation results show that the proposed clustering based fuzzy controller methodology robustly yields uniform performance with adequate gap response over the mass variation range.

• Journal of KSNVE
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• v.9 no.1
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• pp.33-41
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• 1999

This paper presents a method of actively controlling the interior noise by a trim panel with hybrid feedforward-feedback control loop. The control technique is designed to minimize the vibration of panel whose motion is limited to that of a piston (out-of-plane motion). The hybrid controller consists of an adaptive feedforward controller in conjunction with a linear quadratic Gaussian (LQG) feedback controller. In order to maintain control performance of both persistent and transient disturbances, the feedback loop speeds up the adaptation rate of feedforward controller by improving damping capacity of secondary plant related with the adaptation rule. Numerical simulation and experimental result indicate that the hybrid controller is a more effective method for reducing the vibration of the panel (and therefore the interior noise) compared to using feedforward controller.