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:
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.
Federated remote laboratories allow for the execution of experiments ex situ. The coordination of several laboratories can be used to perform concurrent experiments of combined space operations. However, the latency of the communications between facilities is critical to performing adequate real-time experiments. This paper presents an approach for conducting coordinated experiments between floating platforms at two remote laboratories. Two independently designed platforms, one at Luleå University of Technology and the other at La Sapienza University of Rome, were established for this purpose. A synchronization method based on the Simple Network Time Protocol was created, allowing the offset and delay between the agents to be measured.Both platforms exchange data about their measured time and pose through a UDP/IP protocol over the internet. This approach was validated with the execution of simulated operations. A first demonstrative experiment was also performed showing the possibility to realize leader/follower coordinated operations. The results of the simulations and experiments showed communication delays on the order of tens of milliseconds with no significant impact on the control performance. Consequently, the suggested protocol was proven to be adequate for conducting coordinated experiments in real time between remote laboratories.
The problem of fault detection and isolation (FDI) on inertial measurement units (IMUs) has received great attention in the last years, mainly with growing use of IMU strapdown platforms using fiber optic gyros (FOG) or micro electro mechanical systems (MEMSs). A way to solve this problem makes use of sensor redundancy and parity vector (PV) analysis. However, the actual sensor outputs can include some anomalies, as impulsive noise which can be associated with the sensors itself or data acquisition process, committing the elementary threshold criteria as commonly used. Therefore, to overcome this problem, in this work, it is proposed an algorithm based on median filter (MF) for prefiltering and chi-square cumulative sum (-CUSUM) only for fault detection (FD) applied to an IMU composed by four FOGs.
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.
The data fusion from multiple sensors is one of the areas and technologies of interest to national defense (Ministry of Defense of Brazil). Approximately 20 years ago, several methods of data fusion were introduced. Such methods are generally related to the defense sector, but data fusion can also be applied in other areas such as medical diagnostics, industry, etc. A simple way to explain its operation is to state that this technology combines information from several sensors in order to produce other, more accurate information.
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