• 대한전기학회논문지
• /
• 제39권2호
• /
• pp.199-209
• /
• 1990

In this paper, a multivariable robust controller for a boiler-burbine system is designed by using a modified LQG/LTR method. From the known nonlinear dynamic model, a linearized model is obtained with the saturations at both input magnitude and input varying rate. The modeling error is analyzed at various operation points. A new dynamics augmentation method in the LQG/LTR method is suggested which can be applied to LQG/LTR method to reject the input and output disturbances and to follow reference inputs under modeling errors. The good performance of the designed controller is shown by simulations in various conditions.

• 품질경영학회지
• /
• 제25권4호
• /
• pp.88-98
• /
• 1997

For quality improvement, it is important to reduce variations of the quality characteristic. That can be achieved by the a, pp.ication of parameter design methodology to make the performance of the quality characteristic robust over the variety of noise conditions. Taguchi has used the signal-to-noise ratios for that purpose. For the static target characteristic and the dynamic characteristic problem, we propose a reasonable generalized SN ratio and p-value plot for identifying dispersion factors. The orginal idea of the p-value plot in from the gamma-plot in Lunani, Nair & Wasserman(1995). The graphic advantage of the p-value polt for identifying dispersion factors is illustrated through constructed examples.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2006년도 춘계학술대회논문집
• /
• pp.837-843
• /
• 2006

As environmental vibration requirements on precision equipment become more stringent, use of pneumatic isolators has become more popular and their performance is subsequently required to be further improved. Performance of passive pneumatic isolators is related to various design parameters in a complicated manner and, hence, is very limited especially in low frequency range by chamber volume. In this study, transmissibility behavior of the pneumatic isolators depending on frequency and dynamic amplitude are presented. Then, an active control technique, time delay control, which is adequate for a low frequency nonlinear system, is applied. A procedure of applying the time delay control law to a pneumatic isolator is presented and it's effectiveness in the transmissibility performance is shown. Comparison between passive and active pneumatic isolators is made based on simulation.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2001년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
• /
• pp.271-273
• /
• 2001

This paper presents a adaptive speed controller for field oriented controlled (FOC) permanent magnet synchronous motor (PMSM) drives. However, achieving FOC requires machine specific knowledge, and tracking of drifting motor parameters in order to maintain control. The proposed controller based on Minimum Controller Syntheses (MCS) algorithm does not require exact knowledge of motor parameters. This controller structure simplifies the design and implementation of the adaptive controller requiring less effort to synthesis than a standard MRAC system. Simulation results using Matlab/Simulink show that the proposed controller has good dynamic performances and it is insensitive to parameter variations.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2004년도 춘계학술대회
• /
• pp.733-738
• /
• 2004

This paper deals with feedback control of a hydraulic unit for direct yaw moment control, a method used to actively maintain the dynamic stability of an automobile. The uncertain parameters and complex structure naturally call for empirical modeling of the hydraulic unit, which readily results in a control-oriented model with high fidelity. The identified model is cross-validated against experimental data under various conditions, which helps to establish model uncertainty. Then, the $H_{\infty}$ optimization technique is employed to synthesize a controller with guaranteed robust stability and performance against the model uncertainty. The performance of the synthesized controller is verified using experimental results, which shows the viability of the proposed approach in a real-world application.

• 항공우주시스템공학회지
• /
• 제7권4호
• /
• pp.18-26
• /
• 2013

The technique of sliding mode control has been introduced and designed for jet engine controller. For designing the controller for controlled element, the state space model of the turbojet engine is derived in advance from the perturbation of non-linear engine dynamic equation at operation point. Based upon the jet engine model, the robust sliding mode controller is proposed associated with the optimum sliding mode function. The numerical simulation demonstrates that the designed sliding mode controller proves its effectiveness for the jet engine by showing superior control performances over the conventional PI controller with fast responses and robustness to disturbance.

• International Journal of Automotive Technology
• /
• 제7권1호
• /
• pp.91-99
• /
• 2006

The diesel Auxiliary Power Unit (APU) for vehicle applications is a complex nonlinear system. For the purpose of this paper presents a dynamic average model of the whole system in an entirely physical way, which accounts for the non-ideal behavior of the diode rectifier, the nonlinear phenomena of generator-rectifier set in an elegant way, and also the dynamics of the dc load and diesel engine. Simulation results show the accuracy of the model. Based on the average model, a simple PI control scheme is proposed for the multivariable system, which includes the steps of model linearization, separate PI controller design with robust tuning rules, stability verification of the overall system by considering it as an uncertain one. Finally it is tested on a detailed switching model and good performances are shown for both set-point following and disturbance rejection.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제50권4호
• /
• pp.184-191
• /
• 2001

This paper proposes a prefilter type velocity compensating control system using modified chaotic neural networks for the trajectory control of robotic manipulator. Since the structure of modified chaotic neural networks(MCNN) and neurons have highly nonlinear dynamic characteristics, MCNN can show the robust characteristics for controlling highly nonlinear dynamics like robotic manipulators. For its application, the trajectory controller of the three-axis robot manipulator is designed by MCNN. The MCNN controller acts as the compensator of the PD controller. Simulation results show that learning error decrease drastically via on-line learning and the performance is excellent. The MCNN controller showed much better control performance and shorter calculation time compared to the RNN controller, Another advantage of the proposed controller could by attached to conventional robot controller without hardware changes.

• 한국추진공학회:학술대회논문집
• /
• 한국추진공학회 2008년 영문 학술대회
• /
• pp.35-38
• /
• 2008

This paper develops an aero engine LPV mathematical model to exactly describe aero engine dynamic process characteristics, eliminate the effect of modeling error. Design FDF with eigenstructure assignment. The simulation results of turbofan engine control system sensor fault show that this method has good performance in focusing discrimination in fault signal with modeling eror, enhancing the robustness to unknown input, detecting accuracy is high and satisfiying real-time requirement.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
• /
• pp.227-233
• /
• 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.