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State-space solutions of H∞ controller have been well developed. Hence to a real structure control design, the first step is to get a state space model of the structure. There are analytical and experimental dynamic modeling methods. As we know, it is hard to obtain an accurate model for a flexible and complex structure by FEM(Finite Element Method). Then the experimental modeling methods are used. In this paper, we use frequency domain modal analysis technique based on system FRF(Frequency Response Function) data and ERA(Eigensystem Realization Algorithm) time domain method based on system impulse response data to establish state-space model in order to design H∞ control law for the purpose of vibration suppression. The robust control implementation is exerted on a testbed (truck cab model device) with three degrees of freedom. The validity of experimental state-space modeling is testified and the obvious vibration control performances are achieved.

‘Three kinds of new simultaneous optimum design methods of plural dynamic absorbers are proposed. These methods allow the optimum tuning in many natural modes of multiple degrees of freedom structures or a continuous bodies simultaneously to effectively suppress vibration. Changes of natural modes and natural frequencies of the main structure due to added mass effect of dynamic absorbers can be taken into account in the design. Validity and usefulness of the proposed methods are verified by both a computer simulation and by experiments.

In this paper, a new method which directly identifies characteristic matrices (the mass, damping and stiffness matrices) of the mechanical structure using measured forces input and responses data is proposed. This algorithm is based upon the Maximum Likelihood Estimation, so that the accuracy of identified matrices is stable to experimental errors (random errors). After a theoretical formulation is performed, two examples are provided to illustrate and validate this algorithm. One is analytical example which identifies analytically generated data with random noises, and the other experimentarly identified engine/mount system of automobiles.

This paper concerns the Direct System Identification Method (hereafter referred to as DSIM) which allows accurate and quick determination of two groups of properties which exercise dominant effects on low frequency vibration of a vehicle body. The first group is the rigid body properties of an engine. The second group is the properties of each engine mount. Under the assumption that the engine/mount system is a rigid body, this paper makes theoretical discussion for using the DSIM to induce the parameters of an engine/mount system, and makes improvements for better correlation with experiments. Also mentioned is a comparison of this study with the experimental results and verification of consistency on those parameters obtained from DSIM to predict the accurate vehicle characteristics, along with the role this method will play in upgrading the technology of prediction analysis.