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Through microscopic visualization experiments, a process generally known as depth filtration was shown to be caused by surface pores. Moreover, the existence of a soot cake layer was an important advantage for filtration performance because it could trap most of the particulates. We proposed an ideal diesel particulate filter (DPF), in which a silicon carbide (SiC) nanoparticle membrane (made from a mixture of 80 nm and 500 nm powders) instead of a soot cake was sintered on the DPF wall surface; this improved the filtration performance at the beginning of the trapping process and reduced energy consumption during the regeneration process. The proposed filter was called a diesel particulate membrane filter (DPMF). A diesel fuel lamp was used in the trapping process to verify the trapping and oxidation mechanisms of ultrafine particulate matter. Thus, the filtration performance of the membrane filters was shown to be better than that of conventional DPFs.

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.