ICA Based Vibration Detection of Unknown Systems and Its Active Suppression via Online Learning

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The objective of this research lies in introducing Independent Component Analysis(ICA), a new framework of methods for multivariable analysis, to identification or design of control systems. At this moment, frequency domain approaches are mainly adopted in ICA for dynamical systems. In control systems, however, it is more desirable if we can process in time domain. In view of this, the basic idea of this research is 1)to confine ourselves to the vector AR model, 2)expand the discrete-time signal to time series, 3)express the input-output relations in terms of algebraic equation with fixed elements (which is extended state space representation), and then 4)apply ICA in a transparent way.We first completed this basic idea as an algorithm and proposed it as a blind system identification technique. Then we verified the effectiveness of the proposed method by means of both theoretical analysis and numerical simulation. The result was presented in domestic and international conferences, and then in a journal paper.We further apply this method to two practical issues, namely detection of structure change and rejection of unknown disturbance. Concerning detection of change, we fabricated an experimental system with flexible structure and performed detection of a change due to a virtual fault. The result was successful and we presented it in domestic and international conferences. We have also submitted a paper to a journal.Concerning disturbance rejection, we verified the effectiveness by means of simulation and the result was presented in domestic and international conferences. Now we are preparing a paper for a journal. However, we have not yes succeeded in on-line suppression of vibration, which was mentioned in our original research plan. This is due to lack of a real-time performance in our method. It is our current research theme to overcome this difficulty.