564 research outputs found

    Low-cost RPAS navigation and guidance system using Square Root Unscented Kalman Filter

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    Multi-Sensor Data Fusion (MSDF) techniques involving satellite and inertial-based sensors are widely adopted to improve the navigation solution of a number of mission- and safety-critical tasks. Such integrated Navigation and Guidance Systems (NGS) currently do not meet the required level of performance in all flight phases of small Remotely Piloted Aircraft Systems (RPAS). In this paper an innovative Square Root-Unscented Kalman Filter (SR-UKF) based NGS is presented and compared with a conventional UKF governed design. The presented system architectures adopt state-of-the-art information fusion approach based on a number of low-cost sensors including; Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical System (MEMS) based Inertial Measurement Unit (IMU) and Vision Based Navigation (VBN) sensors. Additionally, an Aircraft Dynamics Model (ADM), which is essentially a knowledge based module, is employed to compensate for the MEMS-IMU sensor shortcomings in high-dynamics attitude determination tasks. The ADM acts as a virtual sensor and its measurements are processed with non-linear estimation in order to increase the operational validity time. An improvement in the ADM navigation state vector (i.e., position, velocity and attitude) measurements is obtained, thanks to the accurate modeling of aircraft dynamics and advanced processing techniques. An innovative SR-UKF based VBN-IMU-GNSS-ADM (SR-U-VIGA) architecture design was implemented and compared with a typical UKF design (U-VIGA) in a small RPAS (AEROSONDE) integration arrangement exploring a representative cross-section of the operational flight envelope. The comparison of position and attitude data shows that the SR-U-VIGA and U-VIGA NGS fulfill the relevant RNP criteria, including precision approach tasks

    Low-cost navigation and guidance systems for unmanned aerial vehicles - part 2: Attitude determination and control

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    This paper presents the second part of the research activity performed by Cranfield University to assess the potential of low-cost navigation sensors for Unmanned Aerial Vehicles (UAVs). This part focuses on carrier-phase Global Navigation Satellite Systems (GNSS) for attitude determination and control of small to medium size UAVs. Recursive optimal estimation algorithms were developed for combining multiple attitude measurements obtained from different observation points (i.e., antenna locations), and their efficiencies were tested in various dynamic conditions. The proposed algorithms converged rapidly and produced the required output even during high dynamics manoeuvres. Results of theoretical performance analysis and simulation activities are presented in this paper, with emphasis on the advantages of the GNSS interferometric approach in UAV applications (i.e., low cost, high data-rate, low volume/weight, low signal processing requirements, etc.). The simulation activities focussed on the AEROSONDE UAV platform and considered the possible augmentation provided by interferometric GNSS techniques to a low-cost and low-weight/volume integrated navigation system (presented in the first part of this series) which employed a Vision-Based Navigation (VBN) system, a Micro-Electro-Mechanical Sensor (MEMS) based Inertial Measurement Unit (IMU) and code-range GNSS (i.e., GPS and GALILEO) for position and velocity computations. The integrated VBN-IMU-GNSS (VIG) system was augmented using the inteferometric GNSS Attitude Determination (GAD) sensor data and a comparison of the performance achieved with the VIG and VIG/GAD integrated Navigation and Guidance Systems (NGS) is presented in this paper. Finally, the data provided by these NGS are used to optimise the design of a hybrid controller employing Fuzzy Logic and Proportional-Integral-Derivative (PID) techniques for the AEROSONDE UAV

    Model-Less Fuzzy Logic Control for the NASA Modeling and Control for Agile Aircraft Development Program

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    The NASA Modeling and Control for Agile Aircraft Development (MCAAD) program seeks to develop new ways to control unknown aircraft to make the aircraft development cycle more efficient. More specifically, there is a desire to control an aircraft with an unknown mathematical model using only first principles of flight. In other words, rather than using a rigorously developed mathematical model combined with wind-tunnel tests, a controller is sought which would allow one to bypass the development of a rigorous mathematical model and enter wind-tunnel testing more directly. This paper presents the design of a fuzzy PID controller, governed by a fuzzy supervisory system which incorporates knowledge of first principles of flight, to control a model-less aircraft\u27s pitch dynamics in a free-to-pitch wind-tunnel environment. This hybrid structure is implemented using a PID controller constructed from independent fuzzy inference systems and augmented in real time by a supervisory system also constructed of independent fuzzy inference systems. Experimental results of the pitch control performance and real-time adaptivity capabilities are presented for both aerodynamically stable and unstable aircraft models

    An Hinf based robust altitude hold flight control system for a tactical UAV

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    In this paper altitude hold control system based on robust Hinf controller is considered. Tactical UAV is used as a platform for design. Simulations, which illustrate performance of the altitude control system are performed for various atmospheric disturbances, including turbulence and wind gusts

    A survey on fractional order control techniques for unmanned aerial and ground vehicles

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    In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

    Flight Control System Design Optimisation via Genetic Programming

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