Giampiero Campa
MathWorks, Technical Marketing, Department Member
This paper describes the results of an effort on the analysis of the performance of specific ‘pose estimation’ algorithms within a Machine Vision-based approach for the problem of aerial refuelling for unmanned aerial vehicles. The... more
This paper describes the results of an effort on the analysis of the performance of specific ‘pose estimation’ algorithms within a Machine Vision-based approach for the problem of aerial refuelling for unmanned aerial vehicles. The approach assumes the availability of a camera on the unmanned aircraft for acquiring images of the refuelling tanker; also, it assumes that a number of active or passive light sources – the ‘markers’ – are installed at specific known locations on the tanker. A sequence of machine vision algorithms on the on-board computer of the unmanned aircraft is tasked with the processing of the images of the tanker. Specifically, detection and labeling algorithms are used to detect and identify the markers and a ‘pose estimation’ algorithm is used to estimate the relative position and orientation between the two aircraft. Detailed closed-loop simulation studies have been performed to compare the performance of two ‘pose estimation’ algorithms within a simulation envi...
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ABSTRACT This work presents identification, control synthesis and simulation results for an YF-22 aircraft model designed, built, and instrumented at West Virginia University. The goal of the project is the experimental demonstration of... more
ABSTRACT This work presents identification, control synthesis and simulation results for an YF-22 aircraft model designed, built, and instrumented at West Virginia University. The goal of the project is the experimental demonstration of formation flight for a set of 3 of the above models. In the planned flight configuration, a pilot on the ground maintains controls of the leader aircraft while a wingman aircraft is required to maintain a pre-defined position and orientation with respect to the leader. The identification of both a linear model and a nonlinear model of the aircraft from flight data is discussed first. Then, the design of the control scheme is presented and discussed. Using the developed nonlinear model, the control laws for a maneuvered flight of the formation are then simulated with Simulink and displayed with the Virtual Reality Toolbox. Simulation studies have been performed to evaluate the effects of specific parameters and the system robustness to atmospheric turbulence. The results of this analysis have allowed the formulation of specific guidelines for the design of the electronic payload for formation flight.
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This paper gives details of the first flights of the German, Italian and Japanese jet-propelled aircraft and engines during the last war. Only gas turbine jet propulsion has been covered.
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ABSTRACT A critical aspect in the design of Semi‐Autonomous Aerial Refuelling (SAAR) control schemes for Unmanned Aerial Vehicles (UAVs) is the availability of accurate measurements of the relative UAV‐Tanker distance and attitude. In... more
ABSTRACT A critical aspect in the design of Semi‐Autonomous Aerial Refuelling (SAAR) control schemes for Unmanned Aerial Vehicles (UAVs) is the availability of accurate measurements of the relative UAV‐Tanker distance and attitude. In this effort, the attention was focused on the development of an accurate modelling of the SAAR manoeuvre and on the development of a Machine Vision‐based scheme for the estimation of the tanker‐UAV relative pose. The developed MV scheme is based on markers installed on the surface of the tanker, and performs specific tasks as Feature Extraction, Feature Matching, and tanker‐UAV relative Pose Estimation. The accuracy/robustness of the overall scheme was evaluated in the event of markers occlusion, in presence of inaccuracy in the positioning of the markers on the tanker aircraft, as a function of the level of attitude and GPS sensors' noise and as a function of the data Transmission Delay (TD) between aircrafts.
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Adaptive neural controllers are often criticised for the lack of clear and easy design methodologies that relate adaptive neural network (NN) design parameters to performance requirements. This study proposes a methodology for the design... more
Adaptive neural controllers are often criticised for the lack of clear and easy design methodologies that relate adaptive neural network (NN) design parameters to performance requirements. This study proposes a methodology for the design of an integrated linear-adaptive model reference controller that guarantees component-wise boundedness of the tracking error within an a priori specified compact domain. The approach is based on the design of a robust invariant ellipsoidal set where both the NN reconstruction error and the neuro-adaptive control are considered as bounded persistent uncertainties. We show that all the performance and control requirements for the closed-loop system can be expressed as linear matrix inequality constraints. This brings the advantage that feasibility and optimal design parameters can be effectively computed while solving a linear optimisation problem. An advantage of the method is that it allows a systematic and quantitative evaluation of the interplay between the design parameters and their impact on the requirements. This produces an integrated linear/neuro-adaptive performance-oriented design methodology. A numerical example is used to illustrate the approach.
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Research Interests: Mechanical Engineering, Applied Mathematics, Nonlinear dynamics, Modeling, Neural Network, and 15 moreNonlinear filters, Fault Detection and Isolation, Fault diagnosis, Data Collection, Measurement Error, FIR filter, Fault Isolation, Actuator, Nonlinear Filter, Numerical computation, Noise Measurement, Cost Function, Electrical And Electronic Engineering, Finite Impulse Response Filter, and measurement noise
... feature a linear inner loop controller and a NLDI (nonlinear dynamic inversion) based outer loopguidance controller, are ... Autonomous formation flight is an important research area in the aerospace community. ... The fourth section... more
... feature a linear inner loop controller and a NLDI (nonlinear dynamic inversion) based outer loopguidance controller, are ... Autonomous formation flight is an important research area in the aerospace community. ... The fourth section outlines the design of the formation control laws. ...
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A simulation environment for design and testing of aircraft adaptive fault-tolerant control systems. The Authors. MG Perhinschi, Department ...
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ABSTRACT
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Research Interests: Aerospace Engineering, Radial Basis Function, Resource Allocation, Neural Networks, Fault Detection, and 15 moreOnline Learning, Neural Network, Fault Tolerance, Proceedings, Kalman Filter, Sensors, Redundancy, Resource Management, Multilayer Perceptron, Flight Control, Backpropagation, West Virginia, Experimental Data, Backpropagation Algorithm, and multi layer perceptron
... paper presents experimental results for a research program using research UAVs built and ... A detailed mathematical model was obtained using parameter identification techniques from previously ... From this data, a Simulink(r) based... more
... paper presents experimental results for a research program using research UAVs built and ... A detailed mathematical model was obtained using parameter identification techniques from previously ... From this data, a Simulink(r) based simulation environment was developed and ...
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ABSTRACT This paper describes the design of a fault tolerant scheme for coping with both sensor and actuator failures within a flight control system. The failure detection and identification scheme is based on the use of neural estimators... more
ABSTRACT This paper describes the design of a fault tolerant scheme for coping with both sensor and actuator failures within a flight control system. The failure detection and identification scheme is based on the use of neural estimators interfaced with correlation functions of the aircraft angular rates. Particular emphasis is placed on the differentiation between sensor and actuator failures. The failure types considered are actuator blockage along with partial/total loss of aerodynamic efficiency of the control surface and angular rate sensor step-type failure. The design of the accommodating control laws for actuator failures is based upon a non-linear dynamic inversion approach with neural network augmentation. The accommodation of sensor failures is performed by replacing the failed sensor output with neural estimates computed as part of the detection and identification process. The performance of the scheme is evaluated using the non-linear simulator for the NASA Intelligent Flight Control System F-15 aircraft developed at West Virginia University. The simulation results confirm the capabilities of the scheme to handle both sensor and actuator failures of different types over a large range of magnitudes.
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In this paper, a library of adaptive neural networks to be used within the Simulink® environment is presented. The library has been developed by the authors with the intent of giving to the Simulink user an easy access to a variety of... more
In this paper, a library of adaptive neural networks to be used within the Simulink® environment is presented. The library has been developed by the authors with the intent of giving to the Simulink user an easy access to a variety of adaptive approximators. The neural networks contained in the library are ready to be used and interchanged within the
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Research Interests: Aerodynamics, Robust control, Stability, Control Systems, Fault Tolerance, and 13 moreParameter estimation, Identification, Frequency-domain analysis, Real Time Systems, State Space, Parameter Identification, Real Time, Mathematical Model, Fourier transform, Real Time system, Time Domain, Fourier Transforms, and Frequency Domain
This paper describes the results of a study focused on enhancing the performance of a non linear dynamic inversion scheme augmented with a neural network to cancell the dynamic inversion error. The approach is based on adding a... more
This paper describes the results of a study focused on enhancing the performance of a non linear dynamic inversion scheme augmented with a neural network to cancell the dynamic inversion error. The approach is based on adding a pre-trained neural network providing the values of the aerodynamic stability and control derivatives required by the dynamic inversion calculations, as the aircraft
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This paper describes the results of a study comparing the performance of two different approaches for the fault tolerant flight control system of the NASA IFCS F-15 aircraft. The first approach is based on the use of LQRbased control laws... more
This paper describes the results of a study comparing the performance of two different approaches for the fault tolerant flight control system of the NASA IFCS F-15 aircraft. The first approach is based on the use of LQRbased control laws featuring on-line real time solution of the Riccati equations coupled with a real-time frequency domain-based parameter estimation approach for selected
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This paper presents an Adaptive Neural Network (ANN) based tool for the modeling, simulation and analysis of aircraft Sensor Failure, Detection, Identification and Accommodation (SFDIA) problem. The tool is based on a SFDIA scheme in... more
This paper presents an Adaptive Neural Network (ANN) based tool for the modeling, simulation and analysis of aircraft Sensor Failure, Detection, Identification and Accommodation (SFDIA) problem. The tool is based on a SFDIA scheme in which learning NNs are used as on-line non-linear approximators of the analytically redundant portion of the system dynamics. This can provide validation capability to measurement
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ABSTRACT While adaptive control has been used in numerous applications, the ability to obtain a predictable transient and steady state closed-loop performance is still a challenging problem from the verification and validation standpoint.... more
ABSTRACT While adaptive control has been used in numerous applications, the ability to obtain a predictable transient and steady state closed-loop performance is still a challenging problem from the verification and validation standpoint. To that end, we considered a recently developed robust adaptive control methodology called, low-frequency learning adaptive control, and utilize a set theoretic analysis to show that the transitory performance of this approach can be expressed, analyzed, and optimized via a convex optimization problem based on linear matrix inequalities. This key feature of the analysis framework allows one to tune the adaptive control design parameters rigorously so that the tracking error components of the closed-loop nonlinear system evolve in a priori specified region of the state space. Numerical examples are provided to demonstrate the efficacy of the proposed verification and validation architecture.
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... Machine Vision based Aerial Refueling for UAVs Giampiero Campa ^* , Marco Mammarella ~* , Marcello R. Napolitano @* , ... 1 Introduction One of the biggest current limitations of UnmannedAerial Vehicles (UAVs) is their lack of... more
... Machine Vision based Aerial Refueling for UAVs Giampiero Campa ^* , Marco Mammarella ~* , Marcello R. Napolitano @* , ... 1 Introduction One of the biggest current limitations of UnmannedAerial Vehicles (UAVs) is their lack of autonomous aerial refueling (AAR) capabilities. ...
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This paper describes the results of an on-going effort at West Virginia University (WVU) and University of Perugia (Italy) focused on the analysis and design of control and modeling tools for autonomous refueling for UAVs. This effort... more
This paper describes the results of an on-going effort at West Virginia University (WVU) and University of Perugia (Italy) focused on the analysis and design of control and modeling tools for autonomous refueling for UAVs. This effort starts from the design of a simulation environment modeling ...