1,720,955 research outputs found
Optical Flow Based State Estimation for an Indoor Micro Aerial Vehicle
No full textThis work addresses the problem of indoor state estimation for autonomous flying vehicles with an optic flow approach. The paper discusses a sensor configuration using six optic flow sensors of the computer mouse type augmented by a three-axis accelerometer to estimate velocity, rotation, attitude and viewing distances. It is shown that the problem is locally observable for a moving vehicle. A Kalman filter is used to extract these states from the sensor data. The resulting approach is tested in a simulation environment evaluating the performance of three Kalman filter algorithms under various noise conditions. Finally, a prototype of the sensor hardware has been built and tested in a laboratory setup. Paper published: Verveld, M.J., Chu, Q.P., De Wagter, C. and Mulder, J.A. “Optic Flow Based State Estimation for an Indoor Micro Air Vehicle” AIAA Guidance, Navigation, and Control Conference, August 2010, Toronto, Canada AIAA 2010-8209, DOI: 10.2514/6.2010-8209Aerospace EngineeringControl & Simulatio
Fault Tolerant Flight Control: A Physical Model Approach
No full textSafety is of paramount importance in all transportation systems, but especially in civil aviation. Therefore, in civil aviation, a lot of developments focus on the improvement of safety levels and reducing the risks that critical failures occur. When one analyses recent aircraft accident statistics, it is clear that a significant portion is attributed to “loss of control in flight”. A recent worldwide civil aviation accident survey for the 1989 to 2003 period, conducted by the Civil Aviation Authority of the Netherlands (CAA-NL) and based on data from the National Aerospace Laboratory NLR, indicates that this category accounts for as much as 17% of all aircraft accident cases. This has led to a common conclusion: from a flight dynamics point of view, with the technology and computing power available on this moment, it might have been possible to recover a part of the aircraft in the accident category described above on the condition that non-conventional control strategies would have been applied. These non-conventional control strategies involve the so-called concept of fault tolerant flight control (FTFC), where the control system is capable to detect and adapt for changes in the aircraft behaviour. One FTFC strategy option is using a model based control routine. This research focuses on a physical modular approach. In this setup, not only a reconfiguring controller is needed, but also a suitable FDI/identification strategy. This research focuses on both components. In this reseach project, a real-time aerodynamic model identification procedure has been combined with a model based adaptive control method. A manual as well as an autopilot version have been developed. The autopilot version has been evaluated on desktop simulations, the manual version has been tested in the Simona Research Simulator involving professional airline pilots. Both tests have demonstrated promising results. The autopilot performance is very good, and the manual controller has demonstrated to increase handling qualities and to reduce pilot workload of the damaged aircraft. These are very promising results that motivate further research in this field.Control and SimulationAerospace Engineerin
Aeroelastic model identification of winglet loads from flight test data
No full textNumerical computational methods are getting more and more sophisticated every day, enabling more accurate aircraft load predictions. In the structural design of aircraft higher levels of flexibility can be tolerated to arrive at a substantial weight reduction. The result is that aircraft of the future can be bigger, have better performance and less mass. The performance of an aircraft can be even further enhanced by the use of winglets or other wing tip devices. A more flexible structure in combination with larger dimensions can lead to substantial structural deflections. Due to these larger deflections, the interaction between the aerodynamics and structural mechanics is of increasing importance. Due to their outboard position, the aerodynamic performance of wing tip devices is obviously significantly influenced by the deformation of the flexible wing. Off course, a safe and reliable operational life of the aircraft has to be guaranteed and proven with adequate design calculations. The goal of this thesis was to develop an algorithm to enable the identification of flexibility effects on the outer wing within a manoeuvre loads context based on the Maximum Likelihood Method. The main difference with approaches of existing publications is that the models considered here are based on distributed local data rather than on the net effect on aircraft performance. While this requires the size of the specific models to be much larger, the identified models allow a much more detailed physical interpretation of the observed performance benefits or penalties of winglets or wing tip devices. There are many references that address the topic of aerodynamic performance of wing tip devices and also of winglets in particular. These studies are all based on either wind tunnel measurements or pure aerodynamic (CFD) analysis, thus valid for rigid aircraft. These studies are very important in understanding the complicated flow condition at the wing tip in order to arrive quicker at even more efficient designs. However, flight test measurements have shown that flexibility of the airframe has to be taken into account when predicting the (aerodynamic) loads on the winglet. An algorithm was developed that is able to identify the parameters in a nonlinear coupled aero-elastic manoeuvre loads model. The algorithm is based on the Maximum Likelihood method which is capable of solving even rank-deficient problems. This identification procedure is applied for a loads relevant industrial case using real flight test data. The identification procedure is performed five times using these in-flight measurements with modifications in the aerodynamic modelling on the wings and winglets. One model was developed that describes the nonlinear rigid behavior and could be optimised in an identification for a best fit to the flight test measurements. It was found that especially the local alpha-gradients on the winglet are much larger in this model as predicted by the corresponding results derived from the original aerodynamic database. These identified gradients were compared with the gradients determined from the CFD-simulations and it was shown that they correspond very well. The success of the identification of a specific model strongly depends on the structure of the model and the assumed initial values. The model must be sophisticated enough to capture/describe the phenomena contained in the measurements, however simple/small enough to enable its identification with the available computational resources. The identification algorithm from this thesis was shown to be a very good means to quantify model improvements during model development. Secondly, it can obviously be used to identify the most optimal values for the free model parameters.Control and SimulationAerospace Engineerin
Adaptive Backstepping Flight Control for Modern Fighter Aircraft
No full textThe main goal of this thesis is to investigate the potential of the nonlinear adaptive backstepping control technique in combination with online model identification for the design of a reconfigurable flight control system for a modern fighter aircraft. Adaptive backstepping is a recursive, Lyapunov-based, nonlinear design method, that makes use of dynamic parameter update laws to deal with parametric uncertainties. The idea of backstepping is to design a controller recursively by considering some of the state variables as ‘virtual controls’ and designing intermediate control laws for these. Backstepping achieves the goals of global asymptotic stabilization of the closed-loop states and tracking. The proof of these properties is a direct consequence of the recursive procedure, since a Lyapunov function is constructed for the entire system including the parameter estimates. The tracking errors drive the adaptation process of the procedure. Furthermore, it is possible to take magnitude and rate constraints on the control inputs and system states into account in such a way that the identification process is not corrupted during periods of control effector saturation. A disadvantage of the integrated adaptive backstepping method is that it only yields pseudo-estimates of the uncertain system parameters. There is no guarantee that the real values of the parameters are found, since the adaptation only tries to satisfy a total system stability criterion, i.e. the Lyapunov function. Increasing the adaptation gain will not necessarily improve the response of the closed-loop system, due to the strong coupling between the controller and the estimator dynamics. The immersion and invariance (I&I) approach provides an alternative way of constructing a nonlinear estimator. This approach allows for prescribed stable dynamics to be assigned to the parameter estimation error. The resulting estimator is combined with a backstepping controller to form a modular adaptive control scheme. The I&I based estimator is fast enough to capture the potential faster-than-linear growth of nonlinear systems. The resulting modular scheme is much easier to tune than the ones resulting from the standard adaptive backstepping approacheswith tracking error driven adaptation process. In fact, the closed-loop system resulting from the application of the I&I based adaptive backstepping controller can be seen as a cascaded interconnection between two stable systems with prescribed asymptotic properties. As a result, the performance of the closed-loop system with adaptive controller can be improved significantly. To make a real-time implementation of the adaptive controllers feasible the computational complexity has to be kept at a minimum. As a solution, a flight envelope partitioning method is proposed to capture the globally valid aerodynamic model into multiple locally valid aerodynamic models. The estimator only has to update a few local models at each time step, thereby decreasing the computational load of the algorithm. An additional advantage of using multiple, local models is that information of the models that are not updated at a certain time step is retained, thereby giving the approximator memory capabilities. B-spline networks are selected for their nice numerical properties to ensure smooth transitions between the different regions. The adaptive backstepping flight controllers developed in this thesis have been evaluated in numerical simulations on a high-fidelity F-16 dynamicmodel involving several control problems. The adaptive designs have been compared with the gain-scheduled baseline flight control system and a non-adaptive NDI design. The performance has been compared in simulation scenarios at several flight conditions with the aircraft model suffering from actuator failures, longitudinal center of gravity shifts and changes in aerodynamic coefficients. All numerical simulations can be easily performed in real-time on an ordinary desktop computer. Results of the simulations demonstrate that the adaptive flight controllers provide a significant performance improvement over the non-adaptive NDI design for the simulated failure cases. Of the evaluated adaptive flight controllers, the I&I based modular adaptive backstepping design has the overall best performance and is also easiest to tune, at the cost of a small increase in computational load and design complexity when compared to integrated adaptive backstepping control designs. Moreover, the flight controllers designed with the I&I based modular adaptive backstepping approach have even stronger provable stability and convergence properties than the integrated adaptive backstepping flight controllers, while at the same time achieving a modularity in the design of the controller and identifier. On the basis of the research performed in this thesis, it can be concluded that a RFC system based on the I&I based modular adaptive backstepping method shows a lot of potential, since it possesses all the features aimed at in the thesis goal.Control & SimulationAerospace Engineerin
Model and Sensor Based Nonlinear Adaptive Flight Control with Online System Identification
No full textConsensus exists that many loss-of-control (LOC) in flight accidents caused by severe aircraft damage or system failure could be prevented if flight performance could be recovered using the valid and remaining control authorities. However, the safe maneuverability of a post-failure aircraft will inevitably be reduced due to the malfunction. Non-conventional control strategies which rely on modern control techniques and computational power are essential to control systems in post-failure flight conditions to extract the most from the reduced, remaining aircraft control authorities and restore the flight performance of an aircraft or achieve a safe landing. One such non-conventional control strategy is called active fault tolerant flight control (FTFC), which is designed to detect changes in an aircraft's dynamics caused by structural, actuator, or sensor failure and accommodate the damage or failure using an adaptive reconfiguration mechanism. The active FTFC technique is able to deal with unanticipated and multiple simultaneous failures. The overall architecture of an active FTFC system ideally should consist of a fault detection and diagnosis (FDD) module, a state reconstruction unit, a reconfigurable control component, a control allocation unit and a flight envelope protection (FEP) unit. Generally speaking, FTFC systems can be classified into two types: model-based FTFC systems and model-free FTFC systems, according to whether any of the system's components require an aerodynamic model at their core or not. A model-based FTFC system contains an aerodynamic model identification (AMI) module, which supplies an accurate aircraft model to an indirect adaptive nonlinear controller in the reconfigurable control block, to a dynamic flight envelope determination algorithm in an FEP unit, or to an FDD unit. An aerodynamic model identification approach using a physical, interpretable modeling structure can detect and even quantify structural failures occurring in the aircraft structure or one of the control surfaces by monitoring changes in stability derivatives and control derivatives. There are many candidate control approaches which can achieve reconfiguration when designing a reconfigurable flight controller. These reconfigurable control methods may rely on many different reconfiguration mechanisms ranging from switching, model following, matching to adaptive compensation. These methods include nonlinear adaptive control which achieves reconfiguration through compensation, and this method is receiving increasing attention in the flight control aerospace research community. Nonlinear adaptive control is divided into direct adaptive control and indirect adaptive control, the difference is that the latter requires an online system model. Indirect adaptive control is also called model-based or modular adaptive control, which has some advantages over the direct adaptive control and other model-free control methods. One advantage is that a modular control approach has the potential to yield a more efficient controller which requires less control effort. Such an efficient controller can be achieved by maintaining useful damping terms of an identified system model in the closed-loop system. This is attributed to the good properties of many control design techniques such as backstepping such that the dynamics of an original system can be chosen to be canceled or maintained during a controller design process. Modular adaptive control also has an inherited shortcoming, it can only guarantee input-to-state stability, i.e. modular adaptive control cannot guarantee the stability of the overall closed-loop system because its stability proof relies on the certainty equivalence principle. The weakness of the certainty equivalence principle, i.e., convergence problem of the model parameters, can be improved by enhancing model accuracy or reliability, to do this, it becomes critical to develop advanced, powerful aerodynamic model identification approaches capable of capturing changes in flight dynamics either during a high maneuvering flight mission or a post-failure condition. Flight envelope protection is a necessary technique that should be applied by controller designers to prevent LOC incidents, taking into account highly maneuvering flight tasks and/or highly perturbed flight conditions due to the ongoing failure. An FEP component should provide a pilot with a safe flight envelope and pose constraints on the reference commands fed to an internal controller to make the commands achievable. An aerodynamic model that is valid over an entire flight envelope plays a crucial role in full-envelope modular adaptive control and flight envelope protection. A globally valid model is required for modular adaptive control to enable the designed controller to work properly in a large operating range. Once estimated, the global model in a model-based adaptive control method can be stored for later re-use when the same flight condition is revisited. Except being needed by a model-based controller, an accurate aerodynamic model is also required for flight envelope protection. Naturally, the estimated aerodynamic model has to be valid for the current aircraft configuration over the entire flight envelope to enable an evolution algorithm to estimate the boundary of the safe flight envelope for the current flight condition. However, only a limited number of model identification approaches are suited for estimating a globally valid aerodynamic model, and each existing possible candidate has variant shortcomings or limitations which make it hard to apply directly to identify an aircraft model. For example, neural networks usually yield a nontransparent model structure which is hard to interpret using physical knowledge of the system, and they commonly encounter a convergence problem. Most kernel methods fall into the nonparametric type of methods, which by nature need as many kernels as the data points under evaluation. It should be kept in mind that only equation-error type model identification methods were investigated in the work reported here. The assumption was made that a sufficiently accurate estimation of aircraft states was available. An alternate method to the modular adaptive reconfigurable control approach is the acceleration measurements-based incremental nonlinear control (AMINC) method. An accurate estimation of an aircraft is hard to achieve during a high maneuvering moment or at a transient period when the flight performance is highly perturbed due to aircraft failure. Incremental nonlinear controllers such as incremental nonlinear dynamic inversion (INDI), incremental backstepping (IBKS) and sensor-based backstepping (SBB) are suited for reconfigurable flight control designs in the sense that they do not require complete aircraft model knowledge. The main research question for the research presented here was: How can an advanced fault-tolerant flight control system be designed to increase the survivability of an aircraft? This led to two subsidiary questions: (1). How can the candidate function approximation methods, i.e. multivariate simplex B-splines and kernel methods, be improved in terms of approximation accuracy and computational efficiency, to meet the need of model-based adaptive control and online flight envelope protection? (2). What are the benefits of using an acceleration measurements-based control approach, i.e., the sensor based backstepping, as an alternative to a model-based adaptive control approach, when designing a reconfigurable flight controller to deal with aircraft failures in a generic fault-tolerant flight control (FTFC) system? With regard to reconfigurable control, the identified model should enable the controller to achieve active reconfiguration and restore the control performance. To answer these questions, four different global model identification methods and two nonlinear incremental adaptive controllers were developed. Two model identification methods use a parametric model structure namely standard multivariate simplex B-splines. The focus was placed on how to achieve fast parameter estimation during the research process for these two methods. In the third identification method, a new model structure called tensor-product simplex B-splines was extended from a single dimension case to a multidimensional case, with a focus on demonstrating the advantage of this new compound model structure in terms of the flexibility in model structure selection, computational efficiency and approximation power. The fourth method uses a kernel type model structure which is also parametric. The new recursive kernel approach was developed by combining a classical recursive kernel method with a novel support vector regression approach. A model identification method using standard multivariate simplex B-splines has many advantages, it can avoid the over-fitting problem which occurs with an ordinary polynomial method using a triangulation technique. The approximation power of a simplex B-spline based method is determined by the per-simplex polynomial order and smoothness order, and can be increased by increasing the density of the subdomains in a triangulation. This simplex B-spline based function approximation method guarantees that its output is bounded by the maximum and minimum B-coefficients, this facilitates its certification for future real life applications. The linear regression formulation of the simplex B-spline based method allows for applying most of the constrained recursive parameter estimation methods. Furthermore, the simplex B-spline based method has a sparse property, which can lead to high computational efficiency by adopting distributed computation or other modern computing techniques. However, a simplex B-spline method can easily yield a large amount of unknown parameters if the function dimension exceeds 4, which results in a high computational load considering the smoothness maintaining and covariance matrix updating. To enhance the computational efficiency of the model identification methods using simplex B-splines, two recursive linear-regression model identification methods were developed in this thesis: a substitution-based multivariate simplex B-spline (SB-MVSB) method and a recursive sequential multivariate simplex B-spline (RS-MVSB) method. In the SB-MVSB method, an efficient recursive solver is developed for a constrained linear regression problem when using simplex B-splines. The constrained linear regression problem is converted into a constraint-free linear regression problem using a general solution for the equality constraints. This transformation was shown to reduce the scale of the identification problem in terms of the number of unknown parameters, and thus the computational load required for the model identification method can be reduced. The RS-MVSB method consists of two consecutive procedures at one model evolution step. The first procedure achieves updating of a local model covering the current data point instead of a global model. The requirement of updating a complete covariance matrix is avoided by only updating one local model, and therefore the computational efficiency of this method is greatly enhanced. The second procedure guarantees a smooth transition between this local model and its neighboring local models. The computational complexity of SB-MVSB and RS-MVSB was given from a mathematician point of view, then, they were validated using simulated flight test data generated using a high-fidelity nonlinear model of an F-16 aircraft. Simulation results showed that both methods can achieve higher approximation accuracy than ordinary polynomial based methods, and both can be many, e.g. 10, times faster than an equality constraint recursive least squares based MVSB (ECRLS-MVSB) method. The second feature of these two methods facilitates their future onboard applications. Tensor-product simplex (TPS) B-splines provide a compound structure, which provide more flexibility than a standard simplex B-spline model during model structure selection. Using TPS B-splines, different dimension of inputs can be treated differently depending on their characteristics determined from a priori knowledge. In the work presented in this thesis, the TPS B-spline concept was extended from a single dimension case into a more general multidimensional case. Compared to standard simplex B-splines, TPS B-splines can make better use of a priori model knowledge. By reducing many unnecessary basis polynomials from the regression vector, TPS B-splines have the potential to lead to a lower computational load than standard simplex B-splines. The TPS B-spline method was validated using a data set generated from a high-fidelity nonlinear F-16 model. Simulation results showed that TPS B-splines can yield higher approximation power than standard simplex B-splines with less B-coefficients. Two similar recursive parametric kernel methods namely weight varying least squares support vector regression (WV-LSSVR) and Gaussian process kernel based LSSVR (GPK-LSSVR) were developed for aerodynamic model identification in this thesis. The focus of this work was enhancing the approximation power of a recursive parametric kernel method by choosing an optimal set of kernels for the kernel scheme. An offline method called improved recursive reduced LSSVR (IRR-LSSVR) was used to determine optimal kernels for a classical recursive kernel method. The new kernel method was validated using a series of public available benchmark data sets well known to researchers from the field of pattern recognition. GPK-LSSVR showed a higher approximation power than WV-LSSVR, and both of them showed a higher approximation power than a classical recursive kernel method based on k-means clustering. A novel type of acceleration measurements-based incremental flight control laws was investigated with the aim of providing a reconfigurable control unit with a powerful non-conventional flight control approach which could accommodate sudden structural or actuator failures occurring in an aircraft. The preferred model-free, incremental control approach used in this thesis was the SBB approach, which was initially developed for control designs of nonlinear nonaffine-in-control systems. The SBB approach achieves an accurate reference command tracking performance by approximate dynamic inversion. The SBB approach was extended to deal with sudden model changes in an aircraft caused by structural or actuator failures. A hybrid two-loop angular controller and a joint two-loop angular controller were designed for the RECOVER model. In the hybrid two-loop angular controller, the angular control loop was designed using a nonlinear dynamic inversion (NDI) control law, and the angular rate loop controller using the SBB approach. In the joint two-loop angular controller, the overall controller was designed using a backstepping technique with each loop stabilized recursively. Both angular controllers were validated using the RECOVER model with a focus on dealing with perturbed aircraft flight performance caused by failures. Two benchmark fault scenarios were selected: a rudder runaway case and a flight 1862 engine separation scenario. Simulation results showed that both control setups can guarantee the safety of the post-failure aircraft and achieve a proper reference tracking performance. In comparison with the hybrid NDI/SBB angular controller, the joint SBB angular controller resulted in a better reference tracking performance for the sideslip angle, especially in the engine separation case. An SBB controller contains a time scale parameter, other incremental control laws such as incremental NDI (INDI) and incremental backstepping (IBKS) involve a control effectiveness matrix. Before we can investigate how the time scale parameter or a control effectiveness matrix affect the control performance of an incremental flight controller, the parameter variations of a control effectiveness matrix need to be estimated and analyzed. The TPS B-spline method and an immersion and invariance (I&I) method were chosen to estimate a control effectiveness matrix for an F-16 aircraft. Although the I&I approach initially was not aimed at high modeling accuracy, it was assumed in this thesis that it is able to estimate the changing trend of the control derivatives. Simulation results showed that TPS B-splines capture the changes in the control derivatives better than the I&I approach in terms of consistency. For F-16, the control effectiveness matrix does not evidently affect the control performance of an incremental flight controller when a flight maneuver is moderate in terms of the variation of angle of attack and airspeed. Further research on modular adaptive reconfigurable control is required, for example incorporating the SB-MVSB method or the WV-LSSVR method into control designs to further check how well they are suited for modular adaptive control in terms of approximation power and onboard computational efficiency. Further research on acceleration measurements based reconfigurable control should include tests on the SIMONA simulator, realistic test-flight with UAV and research aircraft.Control and SimulationAerospace Engineerin
Adaptive Backstepping Control and Safety Analysis for Modern Fighter Aircraft
No full textThere exist many examples of aircraft incidents in which the pilots have successfully used the remaining control authority over an aircraft to save the airframe and its passengers and cargo from apparently hopeless failure conditions. Unfortunately, the opposite is also true. Several accidents happened in which the crew was not able to save the aircraft, although post-flight analysis showed that it was possible with alternative, perhaps unconventional, control strategies. These aircraft accidents indicate that there is a potential benefit of fault tolerant flight control techniques, which are able to accommodate changes in the aircraft’s dynamics due to damage to the aircraft and failures of its systems. In this dissertation a modular adaptive flight control approach was developed based on adaptive backstepping with a recursive least squares estimator. The proposed control design was evaluated in numerical simulations on high-fidelity fighter aircraft models. The performance has been compared in simulation scenarios at several flight conditions with the aircraft model suffering from actuator failures, longitudinal center of gravity shifts and changes in aerodynamic coefficients. Results of the simulations demonstrate that the adaptive flight controller provides a significant performance improvement over classical, non-adaptive flight control designs. Although adaptive flight control techniques have shown that it may be possible to stabilize a damaged aircraft for a variety of faults and failures, it is still unclear what maneuvers are still possible and how much the performance of the aircraft has degraded due to these faults and failures. The safe flight envelope is defined as the region in the state space for which safe operation of the aircraft, and safety of its cargo and passengers can be guaranteed. In this dissertation the level set method was researched to determine the safe region of operation of the aircraft. Application of this method to an F-16 model at different flight conditions showed shrinking of the safe flight envelope and decreased maneuverability with decreasing dynamic pressure.Control and SimulationAerospace Engineerin
Robust and Adaptive Nonlinear Attitude Control of a Spacacraft: A Comparison of Backstepping-based Designs
No full textIn the context of the initiative Formation for Atmospheric Science and Technology demonstration (FAST), this dissertation describes the design and comparison of several nonlinear attitude controllers for TU Delft’s micro-satellite. The control requirements include robustness against model uncertainties and disturbances. To this end, Backstepping is selected as the base control design for the stability awareness provided and the versatility in rendering the control law robust and adaptive. Five Backstepping schemes are selected for comparison: Standard Static, Static Robust, Integrated Adaptive with tuning functions estimation, Modular Adaptive with nonlinear extended state observation and, finally, Immersion and Invariance Adaptive. The spacecraft model is written using Modified Rodrigues Parameters. Three perturbation sources are considered and applied separately: constant inertia tensor mismatch; saturated reaction wheel; and moving mirror from a payload spectrometer. All perturbations are translated to time-variant disturbance torques. Convergence of the tuning functions estimator to the true disturbance value is proved. The Immersion and Invariance Adaptive Backstepping law is here proved input-to-state stable in case of time-variable perturbation. Command filters are used in all designs allowing the inclusion of magnitude and rate constraints. Simulation reveals similar tracking performances of all controlled systems in a disturbance-free case. In all disturbance scenarios the adaptive laws clearly outperform the static ones. This is especially evident in the presence of a faulty reaction wheel and a moving payload. Sampling time analysis shows higher dependence of the adaptive designs on the control frequency. The Modular Adaptive and the Immersion and Invariance Adaptive Backstepping controllers display the best performances. However, the latter design emerges as, not only the easiest to tune, but also as the one with the most consistent performance.Control and SimulationAerospace Engineerin
An Integrated Approach to Aircraft Modelling and Flight Control Law Design
No full textThe design of flight control laws (FCLs) for automatic and manual (augmented) control of aircraft is a complicated task. FCLs have to fulfil large amounts of performance criteria and must work reliably in all flight conditions, for all aircraft configurations, and in adverse weather conditions. Consequently, a large part of the FCL design process involves extensive simulation analyses, hardware-in-the-loop testing, and, eventually, flight testing. Multi-disciplinary aspects hereby play an important role. For example, control laws heavily influence (aerodynamic) loads on the airframe during manoeuvring and in turbulence, as well as flutter stability of the structure. These aspects are extensively addressed, but only -after- the actual design phase. As a consequence, problems that arise with other disciplines usually give rise to re-design of control law functions. This thesis proposes an FCL design process that allows multi-disciplinary aspects to be addressed from the beginning. In the first place, this requires multi-disciplinary aspects to be present in the aircraft dynamics models used for FCL design. To this end, the use of object-oriented modelling techniques is proposed, which, in contrast to contemporary techniques, inherently supports the development of models consisting of components from various engineering areas. As a specific application, its use for development of integrated flight mechanics and aeroelastic aircraft models is discussed. In the second place, multi-disciplinary FCL design requires a means to automate tuning of design parameters, since consideration of the many additional criteria make manual parameter synthesis very elaborate. For this reason, the use of multi-objective optimisation is proposed. This technique allows parameters to be optimised with respect to many, possibly conflicting, design criteria via a so-called min-max approach. The process is demonstrated on the design of control laws for automatic landing (autoland) of a passenger aircraft. The certification of autoland systems requires extensive Monte Carlo (MC) analyses to be performed in order to show that landing mishaps in all sorts of extreme conditions are very unlikely. The proposed design process allows the MC analyses to be directly addressed in the synthesis of control law parameters, so that MC analyses for certification can be passed in one shot. The proposed multi-disciplinary design process further allows the control design department to increase participation in aircraft preliminary design, by providing a means for rapid control law prototyping. This methodology allows nonlinear control laws for a specific aircraft design status to be automatically generated from an object-oriented implementation of a current flight dynamics model, using the technique of feedback linearisation and the possibility of automatic model inversion from object-oriented model implementations. For the control department, rapid prototyping allows for quick experimentation with controller structures, the selection of command variables, etc. For other engineering departments, the methodology results in early availability of representative control laws to analyse dynamic flight characteristics of the current aircraft design status.Aerospace Engineerin
Adaptive Incremental Backstepping Flight Control
No full textThis thesis deals with the development of Adaptive Incremental Backstepping control laws for a high-performance aircraft model (F-16), in order to make the airplane robustly seek references in roll rate and angle of attack at a constant airspeed while minimizing sideslip. An Incremental Backstepping scheme that relies on estimates of the angular accelerations and measurements of the current control deflections is used to reduce the dependency on the on-board aircraft model. The contribution of this thesis is the design and evaluation of three parameter estimators to handle the remaining uncertainties. The estimators that are evaluated in this research are based on Tuning Functions, Least-Squares and Immersion & Invariance. It is shown that the Incremental Backstepping controller is not only more robust to uncertainties in the system dynamics compared to Backstepping, but is also more robust to uncertainties in the control effectiveness matrix. Furthermore, by augmenting the Incremental control law with on-line parameter update laws, the tracking performance of the uncertain F-16 model is significantly increased. The results of this study show the great potential of Adaptive Incremental Backstepping control in increasing the survivability of damaged aircraft.Control and SimulationControl and OperationsAerospace Engineerin
Helicopter nonlinear flight control: An acceleration measurements-based approach using incremental nonlinear dynamic inversion
No full textDue to the inherent instabilities and nonlinearities of rotorcraft dynamics, its changing properties during flight and the difficulties to predict its aerodynamics with high levels of fidelity, helicopter flight control requires strategies that allow to cope with the nonlinearities of the model and assure robustness in the presence of inaccuracies and changes in configuration. The control laws developed in the last years normally concern a complex architecture based on an approximate model inversion, with a robust control synthesis or adaptive elements to compensate for the inversion error. In this thesis, a novel approach based on an incremental model inversion is applied to simplify the design of helicopter flight controllers. With the adopted strategy, by employing the feedback of acceleration measurements to avoid the need for information relative to aerodynamic changes in the rotorcraft, the controller does not need any model data that depends exclusively on the states of the system, thus enhancing its robustness to model uncertainties and disturbances. The control system is composed of a three time scale separated loops architecture that allows to provide navigational control of the vehicle. The overall system is tested by simulating several maneuvers with distinct agility levels commonly used for flying qualities analysis and an efficient tracking of the commanded references is achieved. Furthermore, with the robustness properties verified within the range of inaccuracies expected to be found in reality, the suggested method seems to be eligible for a potential practical implementation, even if only a simplified model of the vehicle is available.Control and SimulationAerospace Engineerin
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