• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1989.10a
• /
• pp.46-50
• /
• 1989

Methods for the estimation of the coefficient matrices in the equation of motion for a linear multi-degree-of-freedom structure arc studied. For this purpose, the equation of motion is transformed into an auto-regressive and moving average with auxiliary input (ARMAX) model. The ARMAX parameters are evaluated using several methods of parameter estimation; such as toe least squares, the instrumental variable, the maximum likelihood and the limited Information maximum likelihood methods. Then the parameters of the equation of motion are recovered therefrom. Numerical example is given for a 3-story building model subjected to an earthquake exitation.

• Communications for Statistical Applications and Methods
• /
• v.19 no.5
• /
• pp.673-683
• /
• 2012

Cabral et al. (2012) defined a mixture model of multivariate skew t-distributions(STMM), and proposed the use of an ECME algorithm (a variation of a standard EM algorithm) to fit the model. Their estimation by the ECME algorithm is closely related to the estimation of the degree of freedoms in the STMM. With the ECME, their purpose is to escape from the calculation of a conditional expectation that is not provided by a closed form; however, their estimates are quite unstable during the procedure of the ECME algorithm. In this paper, we provide a conditional expectation as a closed form so that it can be easily calculated; in addition, we propose to use the ECM algorithm in order to stably fit the STMM.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1998.08a
• /
• pp.470-474
• /
• 1998

In this paper, to estimate the time-varying parameters of speech signal, we use the robust sequential estimator based on t-distribution and, for time-varying signal, introduce the forgetting factor. By using the RSE based on t-distribution with small degree of freedom, we can alleviate efficiently the effects of outliers to obtain the better performance of parameter estimation. Moreover, by the forgetting factor, the proposed algorithm can estimate the accurate parameters under the rapid variation of speech signal.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.2 no.3
• /
• pp.40-49
• /
• 1994

This paper describes the method to investigate combustion pressure in the cylinder without modifications of engine. Assuming engine dynamics as a single degree of freedom cylinder pressure is estimated using the variation of crank shaft speed. For this study pressure, crank shaft sped, and load are sampled by the crank angle. This study suggests the variation of crank shaft speed can be used as parameters of feedback engine control.

• The Journal of Korea Robotics Society
• /
• v.19 no.2
• /
• pp.139-148
• /
• 2024

In this paper, we propose a two-degree-of-freedom snake robot head system and an I-PID (Intelligent Proportional-Integral-Derivative)-based controller utilizing RBF (Radial Basis Function) neural network and adaptive robust terms as a control strategy to reduce rotation occurring in the snake robot head. This study proposes a two-degree-of-freedom snake robot head system to avoid complex snake robot dynamics. This system has a control system independent of the snake robot. Subsequently, it utilizes an I-PID controller to implement a control system that can effectively manage rotation at the snake robot head, the robot's nonlinearity, and disturbances. To compensate for the time delay estimation errors occurring in the I-PID control system, an RBF neural network is integrated. Additionally, an adaptive robust term is designed and integrated into the control system to enhance robustness and generate control inputs responsive to signal changes. The proposed controller satisfies stability according to Lyapunov's theory. The proposed control strategy was tested using a 9-degreeof-freedom snake robot. It demonstrates the capability to reduce rotation in Lateral undulation, Rectilinear, and Sidewinding locomotion.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.18 no.7
• /
• pp.1632-1642
• /
• 1994

The Stewart Platform is a six-degree-of-freedom in-parallel-actuated manipiulator mechanism. The kinematic behavior of parallel mechanisms shows inverse characteristics as compared that of serial mechanisms; i.e, the inverse kinematic problem of Stewart Platform is straightforward, but no closed form solution of the forward kinematic problem has been previously presented. Thus it is difficult to calculate the 6 DOF displacement of the platform from the measured lengths of the six actuators in real time. Here, a real-time estimation algorithm which solves the Stewart Platform kinematic problem is proposed and tested through computer simulations and experiments. The proposed algorithm shows stable convergence characteristics, no estimation errors in steady state and good estimation performance with higher sampling rate. In experiments it is shown that the estimation result is the same as that of simulation even in the presence of measurement noise.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.1
• /
• pp.15-23
• /
• 2007

In surveillance, monitoring, and target tracking operations, high-resolution images should be obtained even if the target is in a far distance. Frequent movements of vehicles such as boats degrade the image quality of onboard camera systems. Therefore, stabilizer mechanisms are required to stabilize the line of sight of boatboard camera systems against boat movements. This paper addresses design and implementation of a strapdown boatboard camera stabilizer. A two degree of freedom(DOF)(pan/tilt) robot performs the stabilization task. The main problem is divided into two subproblems dealing with attitude estimation and attitude control. It is assumed that exact estimate of the boat movement is available from an attitude estimation system. Estimates obtained in this way are carefully transformed to robot coordinate frame to provide desired trajectories, which should be tracked by the robot to compensate for the boat movements. Such a practical robotic system includes actuators with fast dynamics(electrical dynamics) and has more degrees of freedom than control inputs. Backstepping method is employed to deal with this problem by extending the control effectiveness.

• Structural Engineering and Mechanics
• /
• v.71 no.4
• /
• pp.377-390
• /
• 2019

A method for estimating the floor response spectra (FRS) of elastic structures under earthquake excitations is proposed. The method is established based on a previously proposed direct estimation method for single degree of freedom systems, which generally overestimates the FRS of a structure, particularly in the resonance period range. A modification factor is introduced to modify the original method; the modification factor is expressed as a function of the period ratio and is determined through regression analysis on time history analysis results. Both real and artificial ground motions are considered in the analysis, and it is found that the modification factors obtained from the real and artificial ground motions are significantly different. This suggests that the effect of ground motion should be considered in the estimation of FRS. The modified FRS estimation method is further applied to a 10-story building structure, and it is verified that the proposed method can lead to a good estimation of FRS of multi-story buildings.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.1
• /
• pp.38-44
• /
• 1998

The modified maximum likelihood estimation method is used to estimate the nondimensional aerodynamic derivatives of a single turbo-prop aircraft at a specified flight condition for the best deduction of the dynamic characteristics. In wind axes the six degree of freedom equations are algebraically linearized so that the linear state equation contains aerodynamic derivatives in a state-space form and is used in the maximum likelihood method. The simulated data added with the measurement noise is used as a flight test data which is necessary to the estimation of nondimensional aerodynamic derivatives. It is obtained by implementing the 6-DOF nonlinear flight simulation. In the flight simulation, the effects of several control input types, control deflection amplitudes, and the turbulence intensities on the statistical convergence criteria are also examined and quantitative analysis of the results is discussed.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2006.05a
• /
• pp.506-509
• /
• 2006

Extended Kalman Filter iterate the prediction and the filtering based on Initial state for the next time step. EKF method for the estimation of nonlinear parameters of a structural dynamic system is necessary that initial of state vector and error covariance matrix. Because those are unknown exactly, generally selected random values. That occasion observability problem appear because of unknown initial values. In this study, for the estimation of the nonlinear parameters, a simple one degree of Freedom example is carried out by Extended Kalman Filter. And initial value assumption for Parameter Estimation of Dynamic System are developed. The result of analysis is compared with calculated standard values.