The problem of damage detection and identification is of interest for many aerospace and aeronautical engineering systems. However, relevant literature mostly focuses on subsystems and parts, rather than full airframes. In structural dynamics, modal parameters, such as natural frequencies and mode shapes, from any structure are the main building blocks of vibration-based damage detection. However, traditional comparisons of these parameters are often ambiguous in large systems, complicating damage detection and assessment. The modified total modal assurance criterion (MTMAC), an index well-known in the field of finite element model updating, is extended to address this challenge and is proposed as an index for damage identification and severity assessment. To support the requirement for precise and robust modal identification of Structural Health Monitoring (SHM), the improved Loewner Framework (iLF), known for its reliability and computational performance, is pioneeringly employed within SHM. Since the MTMAC is proposed solely as a damage identification and severity assessment index, the coordinate modal assurance criterion (COMAC), also a well-established tool, but for damage localisation using mode shapes, is used for completeness. The iLF SHM capabilities are validated through comparisons with traditional methods, including least-squares complex exponential (LSCE) and stochastic subspace identification with canonical variate analysis (SSI-CVA) on a numerical case study of a cantilever beam. Furthermore, the MTMAC is validated against the traditional vibration-based approach, which involves directly comparing natural frequencies and mode shapes. Finally, an experimental dataset from a BAE Systems Hawk T1A jet trainer ground vibration test is used to demonstrate the iLF and MTMAC capabilities on a real-life, real-size SHM problem, showing their effectiveness in detecting and assessing damage.

This article studies and provides a plausible solution to address the effects of micro-particle impacts on the LISA mission. The influence of these undesired events are analysed using a set of 8 worst-case impact conditions from an ESA database of more than 200,000 impacts that captures the anticipated micro-meteoroid environment that the LISA spacecraft may encounter in a span of its envisioned 6.5 years of mission. Based on the results of this analysis, a novel operational mode called SCIHOLD is proposed to provide fast recovery from micro-meteoroid impacts. The performance of the SCIHOLD mode is validated using a LISA high-fidelity, non-linear simulator in two steps. Firstly, the identified 8 worst-case impacts are evaluated in nominal and dispersed conditions in a Monte Carlo campaign, and secondly, larger impacts beyond the ones in the database are simulated to assess the recovery limits of the proposed recovery mode. The results show that the proposed operational mode is successful in recovering the LISA spacecraft from the impacts, and most importantly, that this is achieved with a mean overall recovery time of 92.5s, a considerable reduction compared to a full re-acquisition scenario typically lasting hours.

This article presents fault-tolerant dynamic allocation strategies designed to mitigate propulsion and actuation failures in launch vehicles using a clustered engine configuration. In particular, it addresses engine thrust loss and thrust vector control (TVC) jamming faults during the atmospheric ascent flight of a five-engine launch vehicle. Three different strategies are introduced: a fault-tolerant pseudo-inverse solution, a convex optimization-based approach, and a constrained nonlinear optimization one. These approaches are analyzed and compared at a linear design point and further evaluated using a nonlinear simulator of the launcher. The results demonstrate that these three dynamic allocation techniques are able to provide successful recovery from engine thrust loss failures (up to a certain level depending on the engine throttling capability), TVC actuator jamming failures, and simultaneous engine and actuator failures.

This paper presents the development of the attitude determination and control subsystem (ADCS) for ST3LLARsat1 "BOIRA", a 2U student CubeSat mission aimed at educational and scientific objectives, specifically, measuring atmospheric water vapor. The mission comprises two main ADCS operational modes: detumbling and attitude pointing. Currently, three detumbling control solutions have been defined, and are presented and compared here in terms of key factors such as detumbling time and power consumption. For the attitude pointing mode, mainly for nadir, a hybrid approach combining the Triad method and an extended Kalman filter is employed for determination, and a sliding mode approach for the attitude pointing, which is actuated using only magnetic-torquers. Model in the loop simulation results conducted using MATLAB/Simulink indicate that the designed B-dot controller fulfills our mission detumbling requirements, and that the attitude pointing controller can provide a nadir attitude knowledge error and an attitude pointing error of respectively ≤ 3 and 5 degrees. A Monte Carlo campaign, under various disturbances and uncertain parameters, was also conducted to validate the performance of the developed algorithms.

This paper presents the design of a self‐scheduled fault‐tolerant controller for the lateral/directional motion of MuPAL‐ research aircraft using a polynomial‐scheduled structured H control. The controller is designed to be tolerant against loss‐of‐efficiency faults in the aileron and rudder, but based on industrial best practices it is scheduled with respect to an overall fault level instead of with respect to the individual faults. The performance and robustness of the resulting controller is verified first using frequency and time domain analysis, and subsequently it is validated in the Aircraft‐In‐the‐Loop configuration of MuPAL‐, where the real aircraft is operated in research Fly‐By‐Wire mode by the pilot on‐ground while coupled to an emulation computer that simulates the aircraft flying motion. The results show good behavior of the controlled aircraft across the defined fault scenarios.

This article presents the application of an on-board parameter identification approach to a reusable launch vehicle benchmark during its descent phase. The identification framework is based upon data-driven sparse regression techniques in conjunction with compressed sensing, and allows for the identification of linear or nonlinear equations from measurement data alone. The results show that the proposed approach is able to identify the system behaviour for different guidance/control architectures as well as for nominal and dispersed scenarios.

This article presents the structured H∞ design and validation of two types of flight controller architectures: a passive fault-tolerant controller for the longitudinal motion and an active observer-based fault-tolerant controller for the lateral-directional motion. In the first, the controller follows the conventional Stability/Control Augmentation System (SCAS) structure, and its gains are obtained in continuous-time with the hinfstruct command by considering a set of elevator Loss-Of-Efficiency (LOE) faults. For the second, the conventional Luenberger observer-based controller structure is used, and the design aims to monitor the health of the aileron and rudder actuators in addition to provide active tolerance against LOE faults. Two different discrete-time designs are obtained for the latter, one focused on control performance optimization (using also the hinfstruct command), and the other on simultaneous control and observer performance optimization (using the systune command and under a slightly relaxed control performance constraint). For the two types of architectures, unmodeled dynamics are represented by uncertain bounded time delays modeled as pure delays or first-order Padé approximations. The resulting controllers are implemented on-board JAXA’s research airplane MuPAL-α, and not only is their practicality demonstrated but also control performance is validated via Aircraft-In-the-Loop (AIL) testing under gust-free and realistic gusty conditions. This demonstration is at a Technological Readiness Level (TRL) of 7–8, resulting in a high-level of confidence in the validity of the proposed flight control structures.

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 7521-7530ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.1959Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain

This article presents the design of the science control mode for the LISA mission using robust control synthesis methods and legacy information from the precursor technological demonstration mission LISA Pathfinder (LPF). The LISA mission will be the first space gravitational wave observatory. As such, it is characterized by very stringent scientific constraints resulting in unprecedented control challenges in terms of precision, accuracy, and complexity. Two robust control methods are used, the standard (full-order) and the structured (fixed-order) H-infinity approaches, and the results indicated that boths are excellent candidates to be used for the science control design of LISA.

The consolidation of the artificial intelligence (AI) field has resulted in a paradigm shift towards data-driven machine learning (ML) tools for modelling, design, analysis, verification and validation. There is much interest in the space community in using these AI/ML methods with the aim to improve the performance, robustness and/or capabilities of the current (traditional and advanced) modeling and design approaches, but there are not yet many feasibility studies, and much less applications to systems of sufficient fidelity, to guarantee the successful transfer of the AI/ML methods to industrial operability. Addressing the aforementioned lack of studies, ESA released in 2020 a call for proposals to study the use of AI techniques for GNC design, implementation, and verification. This article presents results from one of the resulting projects (see details on the project and consortium below). Specifically, the article shows the results used to demonstrate the feasibility of a data-driven ML technique used to identify the most relevant parameters of a launch vehicle during the atmospheric ascent. The ML technique used is based on sparse regression techniques [1] in conjunction with compressed sensing, and it allows identification of linear or nonlinear systems from measurement data alone. The algorithm exploits sparsity-promoting techniques and machine learning with a library of possible candidate functions to identify the governing equations of systems characterized by relatively few non-zero terms. In a first phase of the project, the one presented in this article, the algorithm was applied to a simplified model of a launcher during atmospheric ascent (a well-known 2nd order nonlinear transfer function) in order to demonstrate its feasibility, performance, robustness, and shortcomings. This phase is critical to assess whether the algorithm is capable of being used subsequently for the nonlinear benchmark as well as to gather experience and knowledge on its tuning and onboard implementation capability. The aim of this feasibility application was to identify the two most relevant rigid-body rotational launcher parameters, commonly known as a6 and k1. These parameters are of particular interest to flight mechanics and control, as they are directly linked to the controllability and stability of the vehicle. The analysis of the proposed compressed sparse identification approach is presented in incremental steps of complexity in order to build confidence and gain insight on the process: starting with the case of constant dynamics, and gradually building up the complexity of the identification approach by considering a windowing compressed estimation, and finally a real ascent-flight, time-varying profile for the launcher dynamics. The results show that the proposed windowed compressed sparse identification approach can correctly identify the time-varying dynamics of the launch vehicle for a rotational parameter variation profile extracted from a real mission using nominal and dispersed (i.e uncertain) scenarios. This work is part of the project “Artificial intelligence techniques for GNC design, implementation, and verification” funded by ESA contract No. 4000134108/21/NL/CRS and participated by Deimos Engenharia, Deimos Space, INESC-ID, Lund University and TASC. References [1] S. L. Brunton, J. L. Proctor, and J. N. Kutz. Discovering governing equations from data by sparse identification of nonlinear dynamical systems, Proc. Natl. Acad. Sci. USA 113, 3932 (2016).

Fault tolerant control for a cluster of engines in launchers has re-gained attention in recent times thanks to the development of capabilities of new reusable launchers such as SpaceX Falcon 9 and Starship. Most mission failures in the last quarter of the century were caused by propulsion or TVC failures. The former involve an off-nominal thrust delivery by the propulsion system that causes insufficient launch delta-V, leading to a failure to reach orbit or an off-nominal orbital injection performance. Moreover, in the case of a thrust-vectored control (TVC), a reduction in thrust also leads to a reduction in control authority. However, the redundancy provided by the cluster of engines can be intelligently exploited to mitigate failures that affect propulsion or thrust vectoring. The project entitled “Fault-Tolerant Control of Clusters of Rocket Engines (FTC-CRE)” is an activity supported by the European Space Agency aimed at the demonstration of guidance and control (G&C) laws for launch vehicles with cluster of engines, with focusing on reconfiguration capabilities in case of propulsion and TVC failures. The main outcome of the activity is the definition of the most suitable set of requirements and methodologies for a G&C architecture with embedded fault tolerant capabilities, and the increase of the readiness level for recovery strategies which ensure stability and performance in the presence of failures in the engines. Here we provide an overview of the activity, aims and objectives, followed by the description of a test case of a launcher with a cluster of 5 thrusters during ascent, subjected to engine and TVC failures. A launcher simulator modelling the nonlinear dynamics, environment, the failures, including a detailed model of the TVC electro-mechanical actuator has been developed. On this basis, a recovery decision logic is proposed relying on fault tolerant control and trajectory reconfiguration, and the recovery actions are analyzed with the simulator. The work considers realistic, total and partial, failures in one of the cluster’s engines as well as thrust vectoring failures. Since the goal of the present activity is to develop fault-tolerant G&C algorithms, the considered failures are those that decrease the performance of the launcher but that are not considered catastrophic. The modelled failures simulated and analyzed are 1 - Partial and total loss of thrust in one engine 2 - For the cases where the loss of thrust is in a fixed central engine or a gimballed outer engine in the cluster: 2a - A thrust vector actuator fixed at non-zero deflection (loss of communication, avionic failure or any jamming-like behavior) 2b - Loss of power of the thrust vector actuator in an outer engine The loss of thrust is modelled by introducing failures in oxidizer and fuel injection valves, while actuator failures are simulated in a detailed multi-physics Simscape-based model of the TVC actuators. The investigated recovery strategies rely on control reconfiguration and trajectory re-planning based on the detected failure. At the control level, the considered reconfiguration actions are two-fold: 1 - Use an allocation algorithm to optimize thrust levels and deflections within the cluster to compensate for the loss of thrust and any induced parasitic torque 2 - Switch to a controller with less performance but robust to the failure up to a certain tolerance level These actions might not suffice to recover the requirements and it might be necessary to mitigate the failure at guidance level by performing a trajectory re-planning accounting for the available capability of the vehicle. The guidance trajectory generation problem encompasses nonlinear dynamics and several nonconvex state and control constraints. One approach that has been explored in recent literature for handling both nominal and reconfiguration launcher guidance is successive convexification. This approach can address the nonconvex and nonlinear nature of the problem while making it amenable for closed-loop online implementation. However, the challenge of finding an optimal solution under the assumption of clustered actuation with throttleable and gimbaled thrusters and with adaptability in response to actuation faults is yet to be tackled in the literature. In this work, successive convexification is employed to find a solution to the launcher guidance problem. The guidance considers a 6-degrees-of-freedom model, incorporating unstable dynamics and a complex actuation model for the cluster of rocket engines with throttleable thrust and TVC actuators. Additionally, the guidance problem formulation includes a novel approach for robustness against the considered engine fault scenarios and for reconfiguration of the nominal trajectory. The failure scenarios are triggered to evaluate the effectiveness of the different recovery fault-tolerant G&C strategies, in isolation or combined, with respect to the nominal operation. The analysis of the results provides the level of system degradation up to which control reconfiguration can be applied, and from which a trajectory re-planning/re-targeting needs to be performed. The provided testcase is used to show how much the fault tolerant control approaches can successfully recover and mitigate for failures in the thrust vector actuators and a partial loss of thrust. It is also demonstrated the use of closed-loop trajectory reconfiguration to exploit the redundancy in the cluster of engines, and the suitability of successive convexification for the optimal guidance problem.

This article presents the application of the structured H∞ control approach to the design of the LISA mission accelerometer mode. This joint ESA/NASA mission will be the first space-based gravitational wave observatory and is characterized by very stringent scientific constraints resulting in unprecedented control challenges in terms of precision, accuracy, and complexity. The results presented in here were the first demonstration step performed within an ESA study tasked with surveying, trading-off, and applying advanced control techniques to LISA. In addition to showing the methodological gains and design capabilities of the structured H∞ approach, the effects of hardware changes as well as control switching were also analyzed for the designed controllers providing good insight on the way forward to reduce the associated transients. The results presented in this article laid the groundwork, and design process, to subsequently design and validate the full LISA accelerometer mode.

Current and future space observation missions need to perform many large-angle, multi-axis slew maneuvers between observations while keeping the scientific instrument's attitude in a safe region. The state-of-practice typically divides each multi-axis maneuver into a series of single-axis sub-maneuvers, each of which is computed by restricting its guidance solution to the exact spacecraft momentum capacity. This ensures that the constraints are explicitly considered and results in a simple on-board implementation of the guidance algorithm, but is time-consuming and non-optimal for the whole multi-axis maneuver. Addressing this issue, this article presents a novel analytical guidance approach that relies on the convexity of the permissible attitude zone. The proposed guidance is time-optimal for a given spacecraft design and set of admissible observation targets. Both guidance approaches are compared using a multi-body/multi-actuator benchmark spacecraft, whose complex repointing phase requires an autonomous on-board guidance computation. It is shown that the proposed approach is systematic and that the reduction in maneuver time, compared to the state-of-practice approach, is considerable.

In this article several robust control design techniques are compared via their application to the fault tolerant control problem for the lateral/directional motion of JAXA's research aircraft MuPAL-α. The techniques used include: (i) a single, passive-FTC, robust structured H∞ design, (ii) single, active-FTC, robust standard and structured H∞ designs, (iii) manual scheduling schemes from the previous designs, (iv) a self-scheduled structured H∞ design, and (v) a linear parameter varying design. All the designs were implemented in the onboard computer and validated in the so-called Aircraft-In-the-Loop configuration, which entails the operation of the full aircraft in fly-by-wire mode in the hangar. The results show that all the approaches provided acceptable solutions, but with the last two techniques resulting in a more homogeneous performance throughout the fault and command scenarios tested.

This paper presents an enhanced Verification and Validation (V&V) framework accompanied by dedicated tools that allows to analytically evaluate pointing error performance of high-pointing accuracy missions in the presence of disturbances and uncertainties. The proposed analysis approach poses the V&V problem in the robust control framework using linear fractional transformation modelling theory (to include model uncertainties) and frequency dependent weighting functions (to capture the spectral properties of the disturbances and the pointing error performance metrics), and is based on the structured singular value approach as well as the integral quadratic constraint (IQC) framework. The validity of this formal approach is exemplified through the verification of the stringent pointing performance of the Euclid mission during the science observation phase. The results show that the proposed enhanced V&V approach is capable of providing certificates for robust stability and performance for all modelled uncertainties.

This article presents the design of an atmospheric control system for the VEGA launcher using Linear Parameter-Varying (LPV) synthesis techniques, both non-rate and rate-bounded. Following the Space industry traditional approach, the control problem is first formulated to design a rigid-body controller. Subsequently, it is shown how the launcher control problem can be systematically augmented to obtain the rigid-body controller and bending filters in one single procedure. The resulting LPV controller is analyzed in terms of classical linear stability margins and compared with the VEGA baseline controller via Monte-Carlo analyses using a high-fidelity, nonlinear simulator developed by industry. In addition, the LPV design is benchmarked using extended uncertainty ranges against two other advanced controllers: a structured H∞ and an adaptive augmented design. The results show that the LPV controller provides satisfactory stability margins and excellent performance and robustness characteristics, with the advantage of the design technique offering a systematic and methodological design framework.

This article presents the design, verification, and validation of a fault tolerant linear parameter varying controller for JAXA’s MuPAL-α aircraft. The design focuses on the synthesis of a lateral/directional LPV controller robust to velocity changes and actuator uncertainty, and with the scheduling variable chosen to make it fault tolerant to aileron and/or rudder loss-of-efficiency faults. The verification activities include linear, frequency and time, analyses as well as time-domain simulations –the latter with the LPV controller as it will be implemented in the aircraft. The validation is performed in the so-called Aircraft-In-the-Loop, which is best described as a type of aircraft Iron-Bird test-bench where the full aircraft is connected in the hangar to an external computer that allows to introduce exogenous effects (such as wind/gust) while using pilot, or also computer user-defined, commands. The verification and validation results show very good robustness and fault tolerance characteristics of the LPV controller for a wide set of fault conditions and speeds. The article discusses in detail the design and implementation issues for such type of controllers.

This paper investigates the effect of model uncertainty on the nonlinear dynamics of a generic aeroelastic system. Among the most dangerous phenomena to which these systems are prone, Limit Cycle Oscillations are periodic isolated responses triggered by the nonlinear interactions among elastic deformations, inertial forces, and aerodynamic actions. In a dynamical systems setting, these responses typically emanate from Hopf bifurcation points, and thus a recently proposed framework, which address the problem of robustness from a nonlinear dynamics viewpoint, is employed. Briefly, the notion of robust bifurcation margin extends the concept of $$\mu $$ analysis technique from the robust control theory. The main contribution of this article is a systematic investigation of the numerous scenarios arising in the study of nonlinear flutter when uncertainties in the model are accounted for in the analyses. The advantages of adopting this framework include the possibility to: quantify relevant information for the determination of the nonlinear stability envelope; gain a more in-depth understanding of the physical mechanisms triggering subcritical and supercritical Hopf bifurcations; and reveal properties of the nominal system by identifying isolated branches not straightforward to detect with conventional numerical approaches.

The development of effective load relief strategies is key to the improvement of launcher flight performance as it enables a joint increase of wind resilience and decrease of mass. This is particularly relevant for reusable launchers, which are aimed at maximising operational availability and payload capacity. Yet, despite various load relief advances in the aeronautics and wind energy sectors, classical feedback-only techniques remain the state-of-practice for launchers. In this article, an improved load relief functionality for reusable vehicles is proposed based on the use of a disturbance observer for on-board wind anticipation and a load relief compensator driven by the estimate of the wind for its amelioration. Two space systems are used to demonstrate the capabilities of the proposed approach. First, it is applied to a 3 degrees-of-freedom nonlinear simulation model of DLR’s EAGLE vertical-flight demonstrator. Then, it is applied to a 6 degrees-of-freedom nonlinear simulation model of a generic lightweight, reusable launch vehicle. For both cases, the results highlight the benefits of using this type of wind-estimation/load-relief compensation schemes. Further, for the second case, which uses thrust vector control and planar fins for ascent and descent attitude control, it is also shown that the use of fins during ascent (which is not common practice), can further improve launcher performance.

No AccessEngineering NotesEnvelope Extension via Adaptive Augmented Thrust Vector Control SystemDiego Navarro-Tapia, Andrés Marcos and Samir BennaniDiego Navarro-Tapia https://orcid.org/0000-0001-5483-9686University of Bristol, Bristol, England BS8 1TR, United Kingdom*Department of Aerospace Engineering; currently Senior Engineer at Technology for AeroSpace Control, Ltd., London, W1B 3HH, United Kingdom.Search for more papers by this author, Andrés MarcosUniversity of Bristol, Bristol, England BS8 1TR, United Kingdom†Department of Aerospace Engineering; currently Director of Technology for AeroSpace Control, Ltd., London, W1B 3HH, United Kingdom. Senior Member AIAA.Search for more papers by this author and Samir BennaniEuropean Space Agency–European Space Research and Technology Centre, 2201 AZ Noordwijk, The Netherlands‡Senior Advisor, Guidance Navigation & Control Systems Division. Senior Member AIAA.Search for more papers by this authorPublished Online:17 Feb 2021https://doi.org/10.2514/1.G005436SectionsRead Now ToolsAdd to favoritesDownload citationTrack citations ShareShare onFacebookTwitterLinked InRedditEmail About References [1] Orr J. S., Wall J. H., VanZwieten T. S. and Hall C. E., “Space Launch System Ascent Flight Control System,” NASA AAS 14-038, 2014. Google Scholar[2] Wall J. H., “Development and Flight Readiness of the SLS Adaptive Augmenting Control System,” NASA M17-5900, 2017. Google Scholar[3] VanZwieten T. S., Gilligan E. T. and Wall J. H., “Adaptive Augmenting Control Flight Characterization Experiment on an F/A-18,” NASA AAS 17-126, 2017. Google Scholar[4] Hodel A., Whorton M. and Jim Zhu J., “Stability Metrics for Simulation and Flight-Software Assessment and Monitoring of Adaptive Control Assist Compensators,” Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, AIAA Paper 2008-7005, 2008. https://doi.org/10.2514/6.2008-7005 Google Scholar[5] Clements K. and Wall J. H., “Time Domain Stability Margin Assessment of the NASA Space Launch System GNC Design for Exploration Mission One,” NASA AAS 17-126, 2017. Google Scholar[6] VanZwieten T. S., Hannan M. R. and Wall J. H., “Evaluating the Stability of NASA’s Space Launch System with Adaptive Augmenting Control,” CEAS Space Journal, Vol. 10, No. 4, 2018, pp. 583–595. https://doi.org/10.1007/s12567-018-0211-y Google Scholar[7] Orr J. S. and VanZwieten T. S., “Robust, Practical Adaptive Control for Launch Vehicles,” Proceedings of the AIAA Guidance, Navigation, and Control Conference, AIAA Paper 2012-4549, 2012. https://doi.org/10.2514/6.2012-4549 Google Scholar[8] Wall J. H., Orr J. S. and VanZwieten T. S., “Space Launch System Implementation of Adaptive Augmenting Control,” NASA AAS 14-051, 2014. Google Scholar[9] Navarro-Tapia D., Marcos A., Bennani S. and Roux C., “Joint Robust Structured Design of VEGA Launcher’s Rigid-Body Controller and Bending Filter,” Proceedings of the 69th International Astronautical Congress, International Astronautical Federation Paper 45007, 2018. Google Scholar[10] Apkarian P., Dao M. N. and Noll D., “Parametric Robust Structured Control Design,” IEEE Transactions on Automatic Control, Vol. 60, No. 7, 2015, pp. 1857–1869. https://doi.org/10.1109/TAC.2015.2396644 CrossrefGoogle Scholar[11] Roux C. and Cruciani I., “Roll Coupling Effects on the Stability Margins for VEGA Launcher,” Proceedings of the AIAA Atmospheric Flight Mechanics Conference and Exhibit, AIAA Paper 2007-6630, 2007. https://doi.org/10.2514/6.2007-6630 Google Scholar[12] Marcos A., Rosa P., Roux C., Bartolini M. and Bennani S., “An Overview of the RFCS Project V&V Framework: Optimization-Based and Linear Tools for Worst-Case Search,” CEAS Space Journal, Vol. 7, No. 2, 2015, pp. 303–318. https://doi.org/10.1007/s12567-015-0092-2 CrossrefGoogle Scholar[13] Navarro-Tapia D., Marcos A., Bennani S. and Roux C., “Robust-Control-Based Design and Comparison of an Adaptive Controller for the VEGA Launcher,” Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, AIAA Paper 2019-0649, 2019. https://doi.org/10.2514/6.2019-0649 Google Scholar[14] Roux C. and Cruciani I., “Scheduling Schemes and Control Law Robustness in Atmospheric Flight of VEGA Launcher,” Proceedings of the 7th ESA International Conference on Spacecraft Guidance, Navigation and Control Systems, 2008, Paper 53. Google Scholar[15] Simplício P., Marcos A. and Bennani S., “New Control Functionalities for Launcher Load Relief in Ascent and Descent Flight,” Proceedings of the 8th European Conference for Aeronautics and Aerospace Sciences, 2019, Paper 275. https://doi.org/10.13009/EUCASS2019-275 Google Scholar[16] Navarro-Tapia D., Marcos A., Simplício P., Bennani S. and Roux C., “Legacy Recovery and Robust Augmentation Structured Design for the VEGA Launcher,” International Journal of Robust and Nonlinear Control, Vol. 29, No. 11, 2019, pp. 3363–3388. https://doi.org/10.1002/rnc.4557 CrossrefGoogle Scholar Previous article Next article FiguresReferencesRelatedDetailsCited bySatellite micro-launcher control: An integrated adaptive-robust and nonlinear approachControl Engineering Practice, Vol. 122The VEGA launcher atmospheric control problem: A case for linear parameter‐varying synthesisJournal of the Franklin Institute, Vol. 359, No. 2Improved Adaptive Augmentation Control for a Flexible Launch Vehicle with Elastic Vibration16 August 2021 | Entropy, Vol. 23, No. 8 What's Popular Volume 44, Number 5May 2021 CrossmarkInformationCopyright © 2021 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the eISSN 1533-3884 to initiate your request. See also AIAA Rights and Permissions www.aiaa.org/randp. TopicsAircraft ControlAircraft DesignAircraft EnginesAircraft Flight Control SystemAircraft Operations and TechnologyAircraft Stability and ControlAircraft Wing DesignFlight Control SurfacesJet EnginesPropellantPropulsion and Power KeywordsThrust Vector ControlState Space RepresentationFlight Control SystemFlight TestingYawIndustrial ApplicationsAttitude Control SystemAerodynamic InstabilityPropellantSix Degree of FreedomAcknowledgmentsThis work was funded by the European Space Agency through the Networking/Partnering Initiative contract no. 4000114460/15/NL/MH/ats. Navarro-Tapia was also the recipient of a Doctoral Training Partnership award no. 1609551 by the U.K. Engineering and Physical Sciences Research Council. The authors would like to thank AVIO and in particular Christophe Roux for providing the high-fidelity, nonlinear simulator of the VEGA launcher, as well as their support during the first author’s Ph.D. studies.PDF Received15 June 2020Accepted16 January 2021Published online17 February 2021