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intelligent flight control systems Evaluation for Loss-of-control Recovery and Prevention

JOURNAL OF GUIDANCE control AND DYNAMICS 2017年第4期40卷 890-904页

作者： Smaili, M. H. Breeman, J. Lombaerts, T. J. J. Mulder, J. A. Chu, Q. P. Stroosma, O. NLR Netherlands Aerosp Ctr Aerosp Operat Cockpit & Flight Operat POB 90502 NL-1006 BM Amsterdam Netherlands NLR Netherlands Aerosp Ctr Aerospace Syst Aircraft Syst POB 90502 NL-1006 BM Amsterdam Netherlands NASA Ames Res Ctr Mail Stop 269-1 Moffett Field CA 94035 USA Delft Univ Technol Control & Simulat Div Fac Aerosp Engn POB 5058 NL-2600 GB Delft Netherlands

Recent developments in the field of loss-of-control recovery and prevention included improved pilot training, cockpit automation, and fault-tolerant control. The flight Mechanics Action Group on Fault-Tolerant control of the Group for Aeronautical Research and Technology in Europe demonstrated the advantages of fault-tolerant "intelligent," flight control systems. The research enabled the improvement of the technology readiness level of these systems by evaluating one of them in realistic operational scenarios. The handling qualities results of a piloted flight simulator assessment with a damaged aircraft model showed that an online physical model identification approach contributed to improved pilot performance following potentially catastrophic structural and flight critical system failures. After the failures and subsequent control reconfiguration by the intelligent flight control system, airline and engineering test pilots experienced no difficulties in conducting a safe approach and landing.

关键词： intelligent flight control system Test Pilots Handling Qualities Aircraft Configurations Adaptive control Algorithm Full flight Simulator flight Trajectory Technology Readiness Level Fly By Wire control systems Digital flight Data Recorder

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Derivation of formation-flight guidance laws for unmanned air vehicles

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JOURNAL OF GUIDANCE control AND DYNAMICS 2005年第4期28卷 733-742页

作者： Segal, S Ben-Asher, JZ Weiss, H Technion Israel Inst Technol Fac Aerosp Engn IL-32000 Haifa Israel

A guidance-based approach to formation flight of unmanned air vehicles is presented. Most of the works related to formation flight deal with the control of the relative positions between the vehicles in the formation. In the proposed approach a pursuit law replaces the control law. A new rule of pursuit denoted as detective deviated pursuit is then developed based on known guidance rules. The proposed guidance law regulates the distances between vehicles and the heading angles with respect to the lines of sight. We show that the detective deviated pursuit rule can be applied to formation flight, where the formation geometry determines the guidance-law parameters. The work discusses the conditions for a stable formation flight in the case of a maneuvering leader and proposes a control scheme for implementation. The performance of the new guidance-based formation flight is evaluated via simulations.

关键词： Guidance Laws Air Vehicle Zero Lift Drag Coefficient Air Brakes Autopilot intelligent flight control system Suppression of Enemy Air Defense Aerial Refueling Aircraft Trajectory Aircraft Altitude

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Online parameter estimation techniques comparison within a fault tolerant flight control system

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JOURNAL OF GUIDANCE control AND DYNAMICS 2002年第3期25卷 528-537页

作者： Song, YK Campa, G Napolitano, M Seanor, B Perhinschi, MG Hankuk Aviat Univ Sch Aerosp & Mech Engn Kyonggi Do 412791 South Korea W Virginia Univ Dept Mech & Aerosp Engn Morgantown WV 26506 USA

The results of a study where two online parameter identification (PID) methods are compared for application within a fault tolerant flight control system are described. One of the PID techniques is time-domain based, whereas the second is featured in the frequency domain. The time-domain method was directly suitable for the online estimates of the dimensionless aircraft stability derivatives. The frequency-domain method was modified from its original formulation to provide direct estimates of the stability derivatives. This effort was conducted within the research activities of the NASA intelligent flight control system F-15 program. The comparison is performed through dynamic simulations with a specific procedure to model the aircraft aerodynamics following the occurrence of a battle damage/failure on a primary control surface. The two PID methods show similar performance in terms of accuracy of the estimates, convergence time, and robustness to noise. However, the frequency-domain-based method outperforms the time-domain-based method in terms of computational requirements for online real-time applications. The study has also emphasized the advantages of using ad hoe short preprogrammed maneuvers to provide enough excitation following the occurrence of the actuator failure to allow the parameter estimation process.

关键词： intelligent flight control system Aerodynamic Characteristics Stabilator control Surfaces Frequency Domain MATLAB Singular Value Decomposition Longitudinal control Mathematical Models Neural Networks

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Nonlinear Reconfiguring flight control Based on Online Physical Model Identification

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JOURNAL OF GUIDANCE control AND DYNAMICS 2009年第3期32卷 727-748页

作者： Lombaerts, T. J. J. Huisman, H. O. Chu, Q. P. Mulder, J. A. Joosten, D. A. Delft Univ Technol Control & Simulat Div Fac Aerosp Engn NL-2600 GB Delft Netherlands Delft Univ Technol Delft Ctr Syst & Control NL-2600 GB Delft Netherlands

This paper presents a study on fault tolerant flight control of a benchmark aircraft model. Reconfiguring control is implemented by making use of adaptive nonlinear dynamic inversion for manual and autopilot control. The weakness of classical nonlinear dynamic inversion, its sensitivity to modeling errors, is circumvented here by making use of a real-time identified physical model of the damaged aircraft. With help of the Boeing 747 benchmark simulation model, including the realistic component as well as the structural failure modes, it is possible to analyze the damage accommodation capabilities of the considered approach. In failure conditions, the damaged aircraft model is identified by the so-called two-step method in real time and this model is applied subsequently to the model-based adaptive nonlinear dynamic inversion routine in a modular structure, which allows flight control reconfigurations online. After discussing the modular adaptive controller setup, reconfiguration test results are shown for damaged aircraft models using a desktop computer as well as the moving base Simulation, Motion, and Navigation Research flight Simulator of Delft University. These results indicate satisfactory failure handling capabilities of this fault tolerant control setup, for component as well as structural failures.

关键词： intelligent flight control system Autopilot Transport Aircraft Nonlinear Dynamic Inversion Model Predictive control Structural Failure flight Simulators control Surfaces Test Pilots True Airspeed

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intelligent adaptive control of a tailless advanced fighter aircraft under wing damage

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JOURNAL OF GUIDANCE control AND DYNAMICS 2000年第5期23卷 876-884页

作者： Boskovic, JD Mehra, RK Sci Syst Co Inc Woburn MA 01801 USA

In this paper we propose an intelligent adaptive reconfigurable control scheme for a Tailless Advanced Fighter Aircraft (TAFA) in the presence of wing damage. The scheme consists of failure detection using multiple observers, multiple reference models for changing the desired performance on-line in the case of damage, on-line estimation of the percentage-of-damage parameter, and the corresponding adaptive reconfigurable controller augmented with an output error feedback term. The overall scheme results in fast and accurate failure detection and identification and control reconfiguration and is demonstrated analytically to be stable in the sense that ail signals are bounded and the output error converges to zero asymptotically even in the case of 100% wing damage. The properties of the proposed intelligent adaptive controller are evaluated through numerical simulations on a TAFA model in the presence of large noise, actuator dynamics, position and rate limits on the control effecters, and 100% wing damage, and the proposed approach results in excellent overall performance.

关键词： Tailless Advanced Fighter Aircraft Closed Loop system Actuators Numerical Simulation intelligent flight control system Aircraft Dynamics control Surfaces Numerical Modeling Output Feedback Neural Networks

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Evaluation of a Fault-Tolerant Scheme in a Six-Degree-of-Freedom Motion flight Simulator

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JOURNAL OF AEROSPACE COMPUTING INFORMATION AND COMMUNICATION 2010年第2期7卷 47-67页

作者： Sagoo, Girish K. Gururajan, Srikanth Seanor, Brad Napolitano, Marcello R. Perhinschi, Mario G. Gu, Yu Campa, Giampiero W Virginia Univ Morgantown WV 26506 USA

This paper discusses the evaluation of a neurally augmented fault-tolerant flight control scheme for a high-performance military aircraft featuring an adaptive actuator and sensor failure detection, isolation, and identification algorithm in a motion-based flight simulator. The design of the fault-tolerant control scheme is based on a nonlinear dynamic inversion scheme with a neural network-based augmentation for reducing the dynamic inversion errors associated with the occurrence of an actuator failure while a set of online learning neural observers is used for dealing with specific sensor failures. The failure detection, isolation, and identification scheme is based on an adaptive threshold technique for estimating failure bounds associated with both actuator and sensor failures. Also, an 'ad- hoc' parameter is proposed here for the novel task of evaluating the pilot workload in compensating for both actuator and sensor failures onboard the aircraft. A general outcome of the effort is a demonstration of the importance of realistic motion-based simulation environments for evaluation of this specific class of flight control laws. The study also demonstrated the importance of the neural augmentation for failure accommodation purposes and the effectiveness of the proposed adaptive threshold technique for failure identification purposes.

关键词： flight Simulator systems Sensors Actuators Pilot Neural Networks intelligent flight control system High Performance Military Aircraft Six Degree of Freedom Nonlinear Dynamic Inversion flight control Law

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Deep Reinforcement Learning Approach for Integrated Updraft Mapping and Exploitation

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JOURNAL OF GUIDANCE control AND DYNAMICS 2023年第10期46卷 1997-2004页

作者： Notter, Stefan Gall, Christian Mueller, Gregor Ahmad, Aamir Fichter, Walter Univ Stuttgart Inst Flight Mech & Controls D-70569 Stuttgart Germany Univ Stuttgart D-70569 Stuttgart Germany Univ Stuttgart AIAA D-70569 Stuttgart Germany

SOARING aircraft can cover large distances without consuming fossil fuel or electric power by harvesting atmospheric energy. While large transport aircraft have long been taking advantage of upper winds to reduce their energy demand, small aerial vehicles capable of wing-borne flight can harvest energy by exploiting thermal updrafts in the lower atmosphere. The majority of these aerial vehicles use all-electric propulsion systems nowadays. However, the range and endurance of electrically propelled aircraft are limited. Consequently, a significant amount of work has gone into developing guidance and control strategies to exploit thermal updrafts in the last decades. To autonomously exploit a thermal, one has to locate an updraft *** classify previously published approaches for the problem of mapping thermal updrafts into model-free methods and methods that employ a thermal updraft observation model.

关键词： Reinforcement Learning Artificial Neural Network flight Testing Guidance, Navigation, and control systems Robotics intelligent flight control system Aerospace Engineering Autonomous Soaring Autonomous Aerial Vehicle

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Limited Authority Adaptive control Architectures with Dynamic Inversion or Explicit Model Following

Limited Authority Adaptive Control Architectures with Dynami...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Lewis, Jeffrey A. Johnson, Eric N. Penn State Univ University Pk PA 16802 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Aerospace adaptive control has exploited a variety of control techniques since its initial debut in the pursuit of robustness and fault tolerance. This variety of both taxonomy and approaches can create a system of systems which may make generalizations difficult. This paper contributes to the understanding of adaptive systems by synthesizing connected literature to explore the interactions of a baseline adaptive control architecture and trace its development. Comparable performance is shown with explicit model following (EMF) and dynamic inversion (DI) in series feedback with adaptive and linear controller. Articles were included in the review which led to the development of an architecture with dynamic inverse, control allocation, saturation, explicit model following, and adaptive element or demonstrated their interaction effects. A Lyapunov based stability proof was conducted to show stability of the EMF architecture with limited authority pseudocontrol hedge. Robust and limited authority cases were demonstrated by simulation. DI in series and EMF adaptive control architectures were found to have comparable performance under both conditions. Both techniques serve a similar purpose. While dynamic inversion has a clearer implementation and stability proof, many existing rotorcraft use explicit model following for its advantages;integrating EMF with adaptive control produces a viable alternative.

关键词： Model Reference Adaptive control Rotorcrafts Fault Tolerance Feedback Linearization flight Testing Flying Wires intelligent flight control system Nonlinear systems Aerospace system Angle of Attack

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Design and Evaluation of Advanced intelligent flight controllers

Design and Evaluation of Advanced Intelligent Flight Control...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Milz, Daniel Looye, Gertjan DLR German Aerosp Ctr Inst Syst Dynam & Control D-82234 Wessling Germany German Aerosp Ctr Inst Syst Dynam & Control Dept Aircraft Syst Dynam Wessling Germany

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Reinforcement learning based methods could be feasible of solving adaptive optimal control problems for nonlinear dynamical systems. This work presents a proof of concept for applying reinforcement learning based methods to robust and adaptive flight control tasks. Aframework for designing and examining these methods is introduced by means of the open research civil aircraft model (RCAM) and optimality criteria. A state-of-the-art robust flight controller - the incremental nonlinear dynamic inversion (INDI) controller - serves as a reference controller. Two intelligent control methods are introduced and examined. The deep deterministic policy gradient (DDPG) controller is selected as a promising actor critic reinforcement learning method that currently gains much attraction in the field of robotics. In addition, an adaptive version of a proportional-integral-derivative (PID) controller, the PID neural network (PIDNN) controller, is selected as the second method. The results show that all controllers are able to control the aircraft model. Moreover, the PIDNN controller exhibits improved reference tracking if a good initial guess of its weights is available. In turn, the DDPG algorithm is able to control the nonlinear aircraft model while minimizing a multi-objective value function. This work provides insight into the usability of selected intelligent controllers as flight control functions as well as a comparison to state-of-the-art flight control functions.

关键词： Proportional Integral Derivative Reinforcement Learning intelligent flight control system Bang Bang control Neural Networks Nonlinear Dynamic Inversion Cargo Aircraft Robotics Ailerons flight Testing

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Intent inference with path prediction

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JOURNAL OF GUIDANCE control AND DYNAMICS 2006年第2期29卷 225-236页

作者： Krozel, J Andrisani, D Metron Aviat Inc Herndon VA 20170 USA Purdue Univ W Lafayette IN 47906 USA

In today's air-traffic management system, the intent of an aircraft is revealed in its flight plan and a pilot's adherence to published navigation routes. In a future free-flight environment, aircraft might be allowed to fly any route they choose. Intent will likely be broadcast in the form of trajectory change points (TCPs), for instance, up to four TCPs in an automatic dependent surveillance-broadcast message. However, if broadcast TCPs do not accurately represent intent, do not exist, or do not get received, then a nearby aircraft or ground-monitoring system has a need to infer the pilot's intent in real time. In this paper, a method of inferring intent, which is based on artificial intelligence models and a process for best fitting all intent model to observed aircraft motion, is investigated. Horizontal, vertical, and speed dimensions are first investigated independently, and then combined, including sequences of actions, to fully explain the three-dimensional guidance and navigation plan of an aircraft. Finally, the inferred intent is used as a basis to predict a path front the current location of the aircraft into the future.

关键词： flight Planning Automatic Dependent Surveillance Broadcast Artificial Intelligence Enhanced Traffic Management system Pilot Special Use Airspace Air Route Traffic control Center Kalman Filter intelligent flight control system Standard Terminal Arrival Route

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