• International Journal of Control, Automation, and Systems
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• 제6권2호
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• pp.149-159
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• 2008

This paper considers the problem of adaptive fault-tolerant guaranteed cost controller design via dynamic output feedback for a class of linear time-delay systems against actuator faults. A new variable gain controller is established, whose gains are tuned by the designed adaptive laws. More relaxed sufficient conditions are derived in terms of linear matrix inequalities (LMIs), compared with the corresponding fault-tolerant controller with fixed gains. A real application example about river pollution process is presented to show the effectiveness of the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.735-737
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• 1995

Linear pulse motor(LPM) has been used in a wide range of application due to many advantages for the precision position and speed control system for the bidirectional linear motion. In this study, the hybrid, single-side type LPM was designed and examined for characteristics of position detection. Precision position detection signals could be sensed by synchrnous rectifier method from the LPM stator scale. Experimental results show that the position precisions are good enough to perform the LPM position control.

• International Journal of Control, Automation, and Systems
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• 제5권3호
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• pp.324-328
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• 2007

An analytical framework for fuzzy modeling and control of nonlinear systems using a set of linear models is presented. Fuzzy clustering is applied on the aerodynamic coefficients of a missile to obtain an optimal number of rules in a Tagaki-Sugeno fuzzy rule-set. Next, the obtained membership functions and rule-sets are applied to a set of linear optimal controllers towards extraction of a global controller. Reported simulations demonstrate the performance, stability, and robustness of the controller.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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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.

• 한국안전학회지
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• 제24권4호
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• pp.11-16
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• 2009

This research investigates contact angle of Linear Guide Way through a experimental result and theoretical analysis. Since last ten years, most of researchers who concerned with the precision machinery and semiconductor device production etc. so the researches about Linear Guide Way have been unnoticed. The precision machinery and semiconductor device production system has the principle which transfers the mechanical moving to accuracy position control. The Linear Guide Way system has the principle which transfers mechanical moving to accuracy position control is very important to improve performance of the precision machinery and semiconductor device production system. So, In this research, in order to improvement for producing Linear Guide Way, bearing loading analysis and contact angle change through Linear Guide Way theoretical analysis and bearing modeling. Through this study, we may expect that there will be more improvement for producing Linear Guide Way.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회A
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• pp.915-920
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• 2007

A new optimal state feedback and disturbance feedforward control design in the sense of minimizing $L_{2}-gain$ from disturbance to control output is proposed for disturbance attenuation of systems with bounded control input and measurable disturbance. The controller is derived in the framework of linear matrix inequality(LMI) optimization. A gain scheduled state feedback and disturbance feedforward control design is also suggested to improve disturbance attenuation performance. The control gains are scheduled according to the proximity to the origin of the state of the plant and the magnitude of disturbance. This procedure yields a stable linear time varying control structure that allows higher gain and hence higher performance controller as the state and the disturbance move closer to the origin. The main results give sufficient conditions for the satisfaction of a parameter-dependent performance measure, without violating the bounded control input condition.

• 한국정밀공학회지
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• 제24권11호
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• pp.59-65
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• 2007

A new optimal state feedback and disturbance feedforward control design in the sense of minimizing $L_2$-gain from disturbance to control output is proposed for disturbance attenuation of systems with bounded control input and measurable disturbance. The controller is derived in the framework of linear matrix inequality(LMI) optimization. A gain scheduled state feedback and disturbance feedforward control design is also suggested to improve disturbance attenuation performance. The control gains are scheduled according to the proximity to the origin of the state of the plant and the magnitude of disturbance. This procedure yields a stable linear time varying control structure that allows higher gain and hence higher performance controller as the state and the disturbance move closer to the origin. The main results give sufficient conditions for the satisfaction of a parameter-dependent performance measure, without violating the bounded control input condition.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1000-1003
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• 1996

Nonlinear unified predictive control(UPC) algorithm was applied to the temperature control of a batch polymerization reactor for polymethylmethacrylate(PMMA). Before the polymerization reaction is initiated, the parameters of the process model are determined by the recursive least squares(RLS) method. During the reaction, nonlinearities due to generation of heat of reaction and variation of heat transfer coefficients are predicted through the nonlinear model developed. These nonlinearities are added to the process output from the linear process model. And then, the predicted process output is used to calculate the control output sequence. The performance of nonlinear control algorithm was verified by simulation and compared with that of the linear unified predictive control algorithm. In the experiment of a batch PMMA polymerization, nonlinear unified predictive control was implemented to regulate the temperature of the reactor, and the validity of the nonlinear model was verified through the experimental results. The performance of the nonlinear controller turned out to be superior to that of the linear controller for tracking abrupt changes in setpoint.

• 제어로봇시스템학회논문지
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• 제20권8호
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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.

• 대한기계학회논문집A
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• 제31권1호
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• pp.18-25
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• 2007

Linear motor is easily affected by load disturbance, force ripple, friction, and parameter variations because there is no mechanical transmission to reduce the effects of model uncertainties and external disturbance. These nonlinear effects have been reduced for high-speed/high-accuracy position control either through the better motor design or via the better control algorithm that can compensate the nonlinear effects. In this paper, a nonlinear adaptive control algorithm is designed and applied for the position control of permanent magnet linear synchronous motor. In order to estimate and compensate the nonlinear effects such as friction and force ripple, the estimation and the nonlinear adaptive control laws are derived based on the virtual control input and a suitable Lyapunov function. The proposed controller is evaluated through the computer simulations. The control algorithm is also implemented to a DSP board and interfaced to the PMLSM for verifying the realtime control performance.