• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2399-2410
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• 2017

In this paper, a linear matrix inequality-based sampled-data fuzzy observer design method is proposed based on the exact discretization approach. In the proposed design technique, a numerically relaxed observer design condition is obtained by using the discrete-time fuzzy Lyapunov function. Unlike the existing studies, the designed observer is robust to the uncertain premise variable because the fuzzy observer is designed under the imperfect premise matching condition, in which the membership functions of the system and observer are mismatched. In addition, we apply the proposed method to the state estimation problem of the attitude and heading reference system (AHRS). To do this, we derive a Takagi-Sugeno fuzzy model for the AHRS system, and validate the proposed method through the hardware experiment.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.905-906
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• 2006

In this paper, we propose an attractive novel numerical int egration method that is largely devoid of ill conditioning and is suitable for any nonlinear problem. Since the method is exact for linear problems, it is especially precise for quasilinear problems, which are frequently encountered in the real world. The method is based on a new approach to the computat ion of a matrix exponential. It does not require excessive computational resources and lends itself to a short and robust piece of software that can be easily inserted into large simulation packages.