Reconfigurable Flight Control System Research Articles

THE RECONFIGURABLE FLIGHT CONTROL SYSTEM FOR RECOVERING STABILITY AND CONTROLLABILITY OF THE AIR-PLANE IN SPECIAL FLIGHT SITUATIONS

In this paper is given comparative analysis of the statistics adverse flight conditions in flight. Possibility of application of system methods parametric and structural reconfiguration in order to prevent the current flight situation in catastrophic is examined. In this paper, reconfigurable (active) flight control system for recovering stability and controllability of the aircraft when an unexpected problem (such as faults or failures to the actuators/sensors or structural damage) occurs during a flight is proposed.

Reconfigurable Control of Morphing Air Vehicle Based on Real-time Dynamic Modeling

This paper describes a reconfigurable flight control system for morphing air vehicles. The approach combines real-time physical model identification with Nonlinear Dynamic Inversion (NDI). It could solve the problem such as severe changes of aerodynamic characteristics or influences of atmospheric disturbances during the primary stage of flight, and fulfill the high robustness requirements of flight control systems. The aerodynamic characteristics are identified by the two step method which consists of a separate state estimation step and an aerodynamic coefficients identification step instead of the one step method. The two step method is based on iterated extended Kalman filter and fading memory least squares method which is easy to achieve on-line. The sensitivity of NDI to modeling errors is eliminated by making use of an on-line updated reference model of the air vehicle, then reconfigures for the changes in real time. Furthermore, the effectiveness and robustness of the designed flight controller has been validated by six Degree-of-freedom (DOF) nonlinear flight simulations with severe changes of aerodynamic characteristics on the morphing air vehicle and unknown atmospheric disturbances.

Survey on nonlinear reconfigurable flight control

An overview on nonlinear reconfigurable flight control approaches that have been demonstrated in flight-test or highfidelity simulation is presented.Various approaches for reconfigurable flight control systems are considered,including nonlinear dynamic inversion,parameter identification and neural network technologies,backstepping and model predictive control approaches.The recent research work,flight tests,and potential strength and weakness of each approach are discussed objectively in order to give readers and researchers some reference.Finally,possible future directions and open problems in this area are addressed.

Modular robust reconfigurable flight control system design for an overactuated aircraft

In this study a modular approach to the robust reconfigurable flight control system design for an overactuated aircraft is proposed. The structure of the proposed scheme consists of three parts: a backstepping controller module, a robust control allocator and an online actuator effectiveness estimator. Firstly, the backstepping control law is developed for the strict feedback form of an Aero-Data Model in Research Environment aircraft to produce the desired commands. Furthermore, a novel robust optimisation-based control allocation algorithm is proposed to distribute the commands among redundant actuators with the consideration of control effectiveness uncertainties. Lastly, the control effectiveness factors are introduced to denote the healthiness of the actuators, and the least trimming squares-based estimator is designed for online estimation of the actuator effectiveness. With the proposed scheme, good tracking performance, robustness and reconfigurable capability are achieved. Evaluation of the overall system is accomplished by numerical simulation with various conditions, including adverse scenarios where actuator failures occur. The results show the effectiveness of the proposed scheme.

Autopilot Supported by Nonlinear Model Following Reconfigurable Flight Control System

The reconfigurable flight control system was developed, applying a nonlinear aircraft model following control algorithm to support the autopilot. The model of a six degrees of freedom airplane with nonlinear aerodynamics and second-order dynamics of control system actuators was supplemented by aircraft autopilot based on classical control laws. The autopilot commands the aircraft in normal operations. In failure cases, the control system reconfiguration is performed using comparison of control external loads on damaged aircraft with loads in undamaged aircraft operation. Fuzzy logic method produces the control signals preventing the consequences of failures. The objective of reconfiguration is to continue the performed flight, including maneuvers, and, if this is not possible, to obtain the steady flight. The aircraft simulation model was tested for consistency with the expected flight performance. The selected autopilot functions were validated and reconfiguration applied in selected cases of failures. T...

A Model Reference Adaptive Variable Structure Controller for Reconfigurable Flight Control Systems

This paper presents a new design of reconfigurable flight controller, applying both variable structure control and model reference adaptive control. In case of control effectors failures, aircraft model will vary, and unknown disturbances will affect the characteristics of controller. To study this problem, a model reference adaptive variable structure control law is designed, which composes a model-following adaptive control part and a variable structure control part. According to the model matching condition, an update scheme is used in the adaptive control part to eliminate system errors caused by model mismatch. With an adaptive sliding-mode gain the variable structure control part can deal with uncertain bounded disturbances of flight system. An aircraft example with stabilsator failure is presented to demonstrate the feasibility of the proposed reconfigurable control law. Simulation results show the control law is effective for reconfigurable flight control systems.

Adaptive back-stepping neural controller for reconfigurable flight control systems

This paper presents an adaptive back-stepping neural controller for reconfigurable flight control of aircraft in the presence of large changes in the aerodynamic characteristics and also failures. In the proposed controller, radial basis function (RBF) neural networks are utilized in an adaptive back-stepping architecture with full state measurement. For the RBF neural networks, a learning scheme in which the network starts with no hidden neurons and adds new hidden neurons based on the trajectory error is developed. Using the Lyapunov theory, stable tuning rules are derived for the update of the centers, widths, and weights of the RBF neural networks and a proof of stability in the ultimate bounded sense is given for the resulting controller. The theory is illustrated using the longitudinal model of an open-loop unstable high-performance aircraft in the terminal landing phase subjected to single elevator hard over failure and severe winds. The resulting controller is able to successfully stabilize and land the aircraft within a tight touch down dispersion.

Reconfigurable flight control

Indirect adaptive control for reconfigurable flight control is advocated. Specifically, online static system identification using a moving window/batch estimation is implemented. The ensuing linear regression is augmented with an intercept. The intercept parameter is included to address the effects of trim change associated with the occurrence of a control surface failure. Parameter estimate information is used to adjust the inner loop's control gains, and a command derived from the intercept estimate is fed forward to automatically retrim the aircraft. The tracking performance of this automatic retrimming method, which relies on system identification, surpasses the conventional approach of exclusively relying on integral action for retrimming. These adaptive and reconfigurable flight control concepts are illustrated in the context of a fighter aircraft's pitch plane dynamics. The novel adaptive and reconfigurable flight control system successfully handles a 50 per cent horizontal tail control surface loss.

既約分解法による耐故障型飛行制御系の設計

This paper presents a design method of reconfigurable flight control systems based on the coprime factorization method. The baseline robust control system is designed using the normalized coprime factorization method. The identification method employed is a closed-loop one, which is also based on coprime factorization; therefore, the method is suitable to the robust control system. The ν-gap metric is chosen as a criterion that indicates the effects of failures on stabilizability of the robust control system. The ν-gap metric can be computed using the identified parameters. To illustrate the effectiveness of the control and identification method, a design example and simulation results for the F-18 HARV are shown.

ADAPTIVE RECONFIGURABLE FLIGHT CONTROL SYSTEM USING MULTIPLE MODEL MODE SWITCHING

An adaptive reconfigurable flight control system using the mode switching of multiple models is studied. The conventional mode switching method may not guarantee the stability and the performance of the system. In this study, modified adaptive mode switching and decision logic are proposed to improve the adaptiveness of the transient dynamics of a system while maintaining the stability of the closed-loop system in the overall flight envelope. Fixed parameter models and adaptive models are used for mode switching, and a re-initialized adaptive model is also considered. Proper fixed system models are determined by considering various flight conditions with possible aircraft fault models. The mode switching control system is designed based on the selected models for reconfiguration. Numerical simulations are performed to validate the effectiveness of the proposed method.

Flight control system reconfiguration for “locked and centred” and “non‐neutral position” control surface failures

The research work presented in this paper deals with the design of a reconfigurable flight control system (RFCS) based on the control distribution concept (CDC). The work presented here is concerned with the reconfiguration in response to single and multiple control surface failures. A model of a generic fighter aircraft possessing a relatively large number of control surfaces was selected as a test model for the reconfiguration algorithm. The failure in the form of a control surface stuck at a non‐neutral position is one of the most performances degrading and challenging to recover from by a process of reconfiguration. An algorithm was developed to reconfigure the overall FCS by way of redistributing the control effort to the remaining healthy control surfaces, while at the same time cancelling the effects of control surface deflection locked at a non‐neutral position by the generation of another compensating signal feeding to the FCS.

Reconfigurable Flight Control System Design Using Adaptive Neural Networks

An adaptive controller design method based on neural network is proposed for reconfigurable flight control systems in the presence of variations in aerodynamic coefficients or control effectiveness deficiencies caused by control surface damage. The neural network based adaptive nonlinear controller is developed by using the backstepping technique for command following of the angle of attack, sideslip angle, and bank angle. On-line learning neural networks are implemented to compensate the control effectiveness decrease and guarantee the robustness to the uncertainties due to aerodynamic coefficients variations. The main feature of the proposed controller is that the adaptive controller is designed by assuming that all of the nonlinear functions of the system have uncertainties, whereas most of the previous works assume that only some of the nonlinear functions are unknown. Neural networks learn through the weight update rules that are derived from the Lyapunov control theory. The closed-loop stability of the error states is also investigated. A nonlinear dynamic model of a high performance aircraft is used to demonstrate the effectiveness of the proposed control law.

Reconfigurable Nonlinear Autopilot

The paper proposes a reconfigurable flight-control system for the tracking of altitude, heading, sideslip, and velocity commands. The control law can serve for the command of unmanned air vehicles or as an autopilot for piloted aircraft. The inner core of the algorithm consists of a reconfigurable control system providing tracking of pitch-, roll-, and yaw-rate commands. It is based on a model reference control law and a stabilized recursive least-squares algorithm. The outer loop is based on a linear design, with compensation for the nonlinear couplings arising from flight dynamics. Some parameters of the outer loop are identified in real time in order to adapt to varying flight conditions. The algorithm is evaluated using a nonlinear F-16 simulation model. The results demonstrate the consistent performance of the algorithm through various flight conditions, as well as its turn coordination capabilities, its reconfiguration after a floating left elevator failure, its ability to move across the power curve, and its tolerance to measurement noise and turbulence.

Reconfigurable Flight Control System Design Using Direct Adaptive Method

A reconfigurable flight control system provides better survivability through the automatic reconfiguration of control system when faults occur during flight. The adaptive control method has been effectively applied to the reconfigurable flight control system design. However, reconfigurable flight control systems based on the indirect adaptive control method require persistent input excitation and smooth input-output data. To deal with the persistent input excitation problem and to obtain smooth control input, the system identification algorithm in reconfiguration flight control systems usually imposes some constraints on past input-output data, which may deteriorate the reconfiguration performance. Thus, a new reconfigurable flight control system based on the direct adaptive method is proposed to achieve better reconfiguration performance without the system identification process. The proposed control method uses a model following controller with direct adaptive update rules. To control the inner-loop states and the outer-loop states of the flight system simultaneously,the timescale separation principle is applied. The reconfiguration performance of the proposed control method is evaluated through numerical simulations using a six-degree-of-freedom nonlinear aircraft model.

Reconfigurable Flight Control System Design Using Sliding Mode Based Model Following Control Scheme

In this paper, a reconfigurable flight control system is designed by applying the sliding mode control scheme. The sliding mode control method is a nonlinear control method which has been widely used because of its merits such as robustness and flexibility. In the sliding mode controller design, the signum function is usually included, but it causes the undesirable chattering problem. The chattering phenomenon can be avoided by using the saturation function instead of signum function. However, the boundary layer of the sliding surface should be carefully treated because of the use of the saturation function. In contrast to the conventional approaches, the thickness of the boundary layer of our approach does not need to be small. The reachability to the boundary layer is guaranteed by the sliding mode controller. The fault detection and isolation process is operated based on a sliding mode observer. To evaluate the reconfiguration performance, a numerical simulation using six degree-of-freedom aircraft dynamics is performed.

백스테핑기법과 신경회로망을 이용한 적응 재형상 비행제어법칙

A neural network based adaptive controller design method is proposed for reconfigurable flight control systems in the presence of variations in aerodynamic coefficients or control effectiveness decrease caused by control surface damage. The neural network based adaptive nonlinear controller is developed by making use of the backstepping technique for command following of the angle of attack, sideslip angle, and bank angle. On-line teaming neural networks are implemented to guarantee reconfigurability and robustness to the uncertainties caused by aerodynamic coefficients variations. The main feature of the proposed controller is that the adaptive controller is designed with assumption that not any of the nonlinear functions of the system is known accurately, whereas most of the previous works assume that only some of the nonlinear functions are unknown. Neural networks loam through the weight update rules that are derived from the Lyapunov control theory. The closed-loop stability of the error states is also investigated according to the Lyapunov theory. A nonlinear dynamic model of an F-16 aircraft is used to demonstrate the effectiveness of the proposed control law.

직접 적응기법을 이용한 모델추종 재형상 비행제어시스템 설계

직접 적응기법을 이용한 모델추종 재형상 비행제어시스템 설계

Minimal time change detection algorithm for reconfigurable flight control systems

Concluding Remarks The first formulation based on orientation angles for control variables leads to nonconvergent behavior if, during the iterative solution procedure, a gets too close to zero; this is because of a singularity in the formulation at a = 0. The second development, based on Lagrange's form of the equinoctial variables, solves this problem; however, without additional work the second formulation creates implementation problems in a hybrid symbolic-numerical computation environment. To overcome these difficulties, the ()* operator, developed herein, can be straightforwardly implemented in these codes.

215 Use of optimal integral control to restore trim in a reconfigurable flight control system

215 Use of optimal integral control to restore trim in a reconfigurable flight control system

Optimal integral control of trim in a reconfigurable flight control system

Abstract In the event of control actuator or surface failures reconfigurable flight control is achieved by automatically constructing a new control law which uses, sometimes in a manner differing from custom, the remaining serviceable actuators and control surfaces. An early reconfiguration scheme is shown to be unsatisfactory as its use can lead to instability. Use of a weighted control distribution method produced satisfactory performance but did not restore the aircraft to its original trim state. This paper shows how the use of integral control can achieve reconfiguration, and the effectiveness of the technique in achieving acceptable flying qualities, even in the presence of several simultaneous control surface failures and atmospheric turbulence, without loss of the trim state is illustrated by means of simulation results.