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The aim of this paper is to present a fault detection algorithm (FDI) based on signal processing techniques developed for an inertial measurement unit (IMU) with minimal redundancy of fiber optic gyros. In this work the recursive median filter is applied in order to remove impulses (outliers) arising from data acquisition process and parity vector operations, improving the fault detection and isolation performance. The FDI algorithm is divided into two blocks: fault detection (FD) and fault isolation (FI). The FD part of the algorithm is used to guarantee the reliability of the isolation part and is based on parity vector analysis using X 2 -CUSUM algorithm. The FI part is performed using parity space projection of the energy subbands obtained from wavelet packet decomposition. This projection is an extension of clustering analysis based on singular value decomposition (SVD) and principal component analysis (PCA). The results of the FD and FI algorithms have shown the effectiveness of the proposed method, in which the FD algorithm is capable of indicating the low-level step bias fault with short delay and a high index of correct decisions of the FI algorithm also with low-level step bias fault.

The aim of this paper was to present a calibration procedure applied to an inertial measurement unit into account a technique based on least-square methods and wavelet denoising to perform the best estimateKeywords:

This paper deals with a performance comparison of the control algorithm for a variable-thrust solid-propellant rocket motor (VTSRM). To do this, we develop a simulation model of a VTSRM considering characteristic changes in the combustor and design control systems for pressure and thrust. We use three types of control algorithms for the pressure control: classical PID control, feedback linearization control, and fuzzy PID control, and two control algorithms for thrust control: classical PID control and fuzzy PID control. Finally, we compare the performance of each control system through a numerical simulation using step responses. Through this work, we check that feedback linearization is better in pressure control, and fuzzy PID control is more appropriate in thrust control. Especially using fuzzy PID control, we can get fast settling with a small undershoot even if the system is a nonminimum phase system.

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