• 소음진동
• /
• 제2권3호
• /
• pp.193-202
• /
• 1992

The unbalance response analysis is one of the essential area in the forced vibration analysis of rotor bearing systems because of it usefulness in balancing and diagnosis as well as identification of parameters involved in rotor bearing systems. However some unbalance responses are not measurable due to the fact that rotor bearing systems are often encapsulated by fixtures or safety protectors. In the present paper, an efficent estimation scheme for unmeasured unbalance responses in rotor bearing systems is developed. The fundamental fearture of the proposed method is characterized by the linear formulae to estimate the unbalance responses from the measured unbalance responses and the finite element auxilliary model equation which is constructed to be identical to the prototype excluding the uncertain parameters such as bearing coefficients. The identification formulae for bearing parameters are also derived by using the unbalance response and the finite elements auxiliary model. Simulation is provided to verify the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
• /
• pp.490-495
• /
• 1998

In this paper an asymmetric hydraulic actuator which consists of single acting cylinder and servo valve is modeled for a quarter car active suspension system. This model regards the force as an internal state rather than a control input. The control input of the model is the sum of oil flows that pass through the valve's orifices. The resulting dynamic equation in the state space ap-pears a feedback connection of a nominal linear time in-variant term with a nonlinear bounded uncertain block. Since this model makes it possible to eliminate the force control phase, analysis and controller design are made straightforward and simple. Well known LQR method is then applied. Simulation and test rig experiment show the effectiveness of this approach in modeling and control.

• Structural Engineering and Mechanics
• /
• 제28권4호
• /
• pp.373-386
• /
• 2008

In this study stochastic analysis of non-linear dynamical systems under ${\alpha}$-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of ${\alpha}$-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with ${\alpha}/2$- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function of the system under Gaussian white noise and the probability density function of the ${\alpha}/2$-stable random parameter. Some numerical applications have been reported assessing the reliability of the proposed formulation. Moreover a proper way to perform digital simulation of the sub-Gaussian ${\alpha}$-stable random process preventing dynamical systems from numerical overflows has been reported and discussed in detail.