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Aircraft Dynamics Model Augmentation for RPAS Navigation and Guidance

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2018年第3-4期91卷 709-723页

作者： Cappello, Francesco Bijjahalli, Suraj Ramasamy, Subramanian Sabatini, Roberto Sch Engn Aerosp & Aviat Discipline Melbourne Vic 3000 Australia

An Aircraft Dynamics Model (ADM) augmentation scheme for Remotely Piloted Aircraft System (RPAS) navigation and guidance is presented. The proposed ADM virtual sensor is employed in the RPAS navigation system to enhance continuity and accuracy of positioning data in case of Global Navigation Satellite System (GNSS) data degradations/losses, and to improve attitude estimation by vision based sensors and Micro-Electromechanical System Inertial Measurement Unit (MEMS-IMU) sensors. The ADM virtual sensor is essentially a knowledge-based module that predicts RPAS flight dynamics (aircraft trajectory and attitude motion) by employing a rigid body 6-Degree of Freedom (6-DoF) model. Two possible schemes are studied for integration of the ADM module in the aircraft navigation system employing an Extended Kalman Filter (EKF) and an Unscented Kalman Filter (UKF). Additionally, the synergy between the navigation systems and an Avionics-based Integrity Augmentation (ABIA) module is examined and a sensor-switching framework is proposed to maintain the Required Navigation Performance (RNP) in the event of single and multiple sensor degradations. The ADM performance is assessed through simulation of an RPAS in representative fight operations. Sensitivity analysis of the errors caused by perturbations in the input parameters of the aircraft dynamics is performed to demonstrate the robustness of the proposed approach. Results confirm that the ADM virtual sensor provides improved performance in terms of data accuracy/continuity, and an extension of solution validity time, especially when pre-filtered and employed in conjunction with a UKF.

关键词： Remotely piloted aircraft system Aerospace navigation Aircraft dynamics model Virtual sensor knowledge-based module Integrity augmentataion Multi-sensor data fusion

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INTELLIGENT TOOL SELECTION FOR MACHINING CYLINDRICAL COMPONENTS .1. LOGIC OF THE knowledge-based module

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE 1995年第3期209卷 173-182页

作者： MAROPOULOS, PG GILL, PAT School of Engineering University of Durham

This paper presents the logic of a knowledge-based system for turning tool selection. The selection philosophy is based on machining performance and the system uses information regarding fools and cutting data from 'approved' operations which have been proved on machine tools following a specific testing procedure. For any new operation, rules are used to identify its level of similarity to previously performed, approved operations. The similarity criteria are based on metal cutting theory Land practical engineering knowledge and incorporate considerations in relation to the component and cutting profile geometry, material type and operation type as well as tool and insert characteristics. The goal is to identify similar approved operations, retrieve the corresponding tool and cutting data and sort them in order of preference. A key function of the system is that according to the level of similarity, the retrieved information is either used as it is or is automatically modified to suit the new operation. The main benefits from using the system are improved engineering consistency in the decision making for selecting tools and cutting conditions, improved utilization of tools and definition of efficient machining conditions.

关键词： LOGIC knowledge-based module INTELLIGENT CUTTING TOOL SELECTION ITS KBS

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