Structure modal optimization of a strapdown inertial navigation system for an electric helicopter using an adaptive surrogate model

The purpose of this research is to prove the eventuality of using a novel adaptive surrogate model for optimization problems. The adaptive surrogate model is based on iteration sampling and extended radial basis function (ERBF). This method improves the precision by a means that new sample points is placed in the blank area and all the sample points is uniformly distributed in the design region. The precision of the surrogate model is checked using standard error measure to determine whether updating the surrogate model or not. Since the prediction of modal frequencies require structure modal simulations. In order to decrease the number of computer simulations, a Multi-Island GA approach is combined with the adaptive surrogate model to find the optimum modal frequencies of a strapdown inertial navigation system for electric helicopters. The strapdown inertial navigation system is comprised of damping material, counterweight material and inertial navigation sensor. This is a multi-objective functions optimization problem since the modal frequencies are considered from mode 1 to mode 6 in this paper. Several weights of multi-objective functions are utilized to research the modal frequencies. The whole number of 15 sampling points is picked to build the primary surrogate model using Latin hypercube sampling (LHS). The results of adaptive surrogate model show that two new sampling points are needed to reform the precision of the surrogate model under the condition of 2 % confidence bounds. The structure modal optimization results show that the choice of the weights for the multi-objective functions has a major effect on the final optimum modal frequencies. Time- and frequency-domain analysis indicated that the optimum modal frequencies are far away from the excitation frequencies to avoid strapdown inertial navigation system resonance as far as possible

Degree-per-hour mode-matched micromachined silicon vibratory gyroscopes

The objective of this research dissertation is to design and implement two novel micromachined silicon vibratory gyroscopes, which attempt to incorporate all the necessary attributes of sub-deg/hr noise performance requirements in a single framework: large resonant mass, high drive-mode oscillation amplitudes, large device capacitance (coupled with optimized electronics), and high-Q resonant mode-matched operation. Mode-matching leverages the high-Q (mechanical gain) of the operating modes of the gyroscope and offers significant improvements in mechanical and electronic noise floor, sensitivity, and bias stability. The first micromachined silicon vibratory gyroscope presented in this work is the resonating star gyroscope (RSG): a novel Class-II shell-type structure which utilizes degenerate flexural modes. After an iterative cycle of design optimization, an RSG prototype was implemented using a multiple-shell approach on (111) SOI substrate. Experimental data indicates sub-5 deg/hr Allan deviation bias instability operating under a mode-matched operating Q of 30,000 at 23ºC (in vacuum). The second micromachined silicon vibratory gyroscope presented in this work is the mode-matched tuning fork gyroscope (M2-TFG): a novel Class-I tuning fork structure which utilizes in-plane non-degenerate resonant flexural modes. Operated under vacuum, the M2-TFG represents the first reported high-Q perfectly mode-matched operation in Class-I vibratory microgyroscope. Experimental results of device implemented on (100) SOI substrate demonstrates sub-deg/hr Allan deviation bias instability operating under a mode-matched operating Q of 50,000 at 23ºC. In an effort to increase capacitive aspect ratio, a new fabrication technology was developed that involved the selective deposition of doped-polysilicon inside the capacitive sensing gaps (SPD Process). By preserving the structural composition integrity of the flexural springs, it is possible to accurately predict the operating-mode frequencies while maintaining high-Q operation. Preliminary characterization of vacuum-packaged prototypes was performed. Initial results demonstrated high-Q mode-matched operation, excellent thermal stability, and sub-deg/hr Allan variance bias instability.Ph.D.Committee Chair: Dr. Farrokh Ayazi; Committee Member: Dr. Mark G. Allen; Committee Member: Dr. Oliver Brand; Committee Member: Dr. Paul A. Kohl; Committee Member: Dr. Thomas E. Michael

SIRU development. Volume 1: System development

A complete description of the development and initial evaluation of the Strapdown Inertial Reference Unit (SIRU) system is reported. System development documents the system mechanization with the analytic formulation for fault detection and isolation processing structure; the hardware redundancy design and the individual modularity features; the computational structure and facilities; and the initial subsystem evaluation results

Deep-Sea Model-Aided Navigation Accuracy for Autonomous Underwater Vehicles Using Online Calibrated Dynamic Models

In this work, the accuracy of inertial-based navigation systems for autonomous underwater vehicles (AUVs) in typical mapping and exploration missions up to 5000m depth is examined. The benefit of using an additional AUV motion model in the navigation is surveyed. Underwater navigation requires acoustic positioning sensors. In this work, so-called Ultra-Short-Baseline (USBL) devices were used allowing the AUV to localize itself relative to an opposite device attached to a (surface) vehicle. Despite their easy use, the devices\u27 absolute positioning accuracy decreases proportional to range. This makes underwater navigation a sophisticated estimation task requiring integration of multiple sensors for inertial, orientation, velocity and position measurements. First, error models for the necessary sensors are derived. The emphasis is on the USBL devices due to their key role in navigation - besides a velocity sensor based on the Doppler effect. The USBL model is based on theoretical considerations and conclusions from experimental data. The error models and the navigation algorithms are evaluated on real-world data collected during field experiments in shallow sea. The results of this evaluation are used to parametrize an AUV motion model. Usually, such a model is used only for model-based motion control and planning. In this work, however, besides serving as a simulation reference model, it is used as a tool to improve navigation accuracy by providing virtual measurements to the navigation algorithm (model-aided navigation). The benefit of model-aided navigation is evaluated through Monte Carlo simulation in a deep-sea exploration mission. The final and main contributions of this work are twofold. First, the basic expected navigation accuracy for a typical deep-sea mission with USBL and an ensemble of high-quality navigation sensors is evaluated. Secondly, the same setting is examined using model-aided navigation. The model-aiding is activated after the AUV gets close to sea-bottom. This reflects the case where the motion model is identified online which is only feasible if the velocity sensor is close to the ground (e.g. 100m or closer). The results indicate that, ideally, deep-sea navigation via USBL can be achieved with an accuracy in range of 3-15m w.r.t. the expected root-mean-square error. This also depends on the reference vehicle\u27s position at the surface. In case the actual estimation certainty is already below a certain threshold (ca. <4m), the simulations reveal that the model-aided scheme can improve the navigation accuracy w.r.t. position by 3-12%

Species identification and molecular phylogenetics of processed sea cucumbers from Malaysian market based on 12s mitochondrial rRNA gene

Extensive processing of sea cucumber causes body deformation of the marine organism, hence causing difficulties in species identification of processed sea cucumbers. Due to the copresence of cases of unlabelled or mislabelled sea cucumber products in Malaysian markets and worldwide, a study was conducted to determine the species identities of processed sea cucumbers from selected Malaysian markets using non-protein-coding 12S mitochondrial rRNA gene. Phylogenetic analyses based on the distance-based Neighbour Joining method, and the character-based methods i.e. the Maximum Parsimony method, Maximum Likelihood method, and the Bayesian Analysis method of 81 ingroup sequences representing 63 processed sea cucumber specimens, 13 fresh and processed reference samples for species identification, and five fresh additional specimens from Teluk Nipah Beach, Pangkor Archipelago and Manukan Island, Sabah suggested the presence of three main clusters i.e. a gamat family cluster consisting of family Stichopodidae (Stichopus horrens, Stichopus vastus, and Thelenota anax) and two clusters of timun laut family comprising family Holothuriidae (Holothuria (Mertensiothuria) leucospilota, Holothuria (Metriatyla)scabra, Holothuria (Metriatyla) lessoni, Holothuria (Halodeima) atra, and Holothuria (Halodeima) edulis) and family Caudinidae (Acaudina molpadioides). The outcomes of this study also highlighted the availability of 40 new 12S mitochondrial rRNA gene sequences deposited in the GenBank that can be utilised by the enforcement agencies to monitor and overcome the issues of species substitution and product mislabelling of processed sea cucumber products in Malaysian markets

Navigation Using Inertial Sensors

This tutorial provides an introduction to navigation using inertial sensors, explaining the underlying principles. Topics covered include accelerometer and gyro technology and their characteristics, strapdown inertial navigation, attitude determination, integration and alignment, zero updates, motion constraints, pedestrian dead reckoning using step detection, and fault detection

Low-cost inertial navigation for moderate-g missions

A low cost inertial navigation system (INS) concept is described for flight missions characterized by moderate accelerations and limited attitude variations. These missions involve general aviation aircraft, helicopters, or remotely piloted vehicles. The significance of the moderate acceleration and limited attitude is reviewed with respect to platform mechanization and instrumentation. A hybrid mechanization, partially gimballed and partially strapdown, is presented. The INS is implemented by an unbalanced two axis gimbal system and controlled by a two degree of freedom gyro. The INS provides locally level two axis acceleration information along with pitch and roll measurements. Heading information is provided by a second gyro mounted in the inner gimbal. The system error model is equivalent to that of a conventional platform with a tilt error determined by the integral of the gyro drift rate and an equivalent accelerometer type errors are also cancelled. Rapid gyro-compassing, implemented with opened gimbal control loops, and a strapdown procedure provides calibration of gyro drift rate biases

Parameter Identification Method for SINS Initial Alignment under Inertial Frame

The performance of a strapdown inertial navigation system (SINS) largely depends on the accuracy and rapidness of the initial alignment. The conventional alignment method with parameter identification has been already applied widely, but it needs to calculate the gyroscope drifts through two-position method; then the time of initial alignment is greatly prolonged. For this issue, a novel self-alignment algorithm by parameter identification method under inertial frame for SINS is proposed in this paper. Firstly, this coarse alignment method using the gravity in the inertial frame as a reference is discussed to overcome the limit of dynamic disturbance on a rocking base and fulfill the requirement for the fine alignment. Secondly, the fine alignment method by parameter identification under inertial frame is formulated. The theoretical analysis results show that the fine alignment model is fully self-aligned with no external reference information and the gyrodrifts can be estimated in real time. The simulation results demonstrate that the proposed method can achieve rapid and highly accurate initial alignment for SINS