Pseudo control compensation based neural network dynamic inversion super maneuverable flight control

This paper presents an advanced single network adaptive critic (SNAC) aided nonlinear dynamic inversion (NDI) approach for simultaneous attitude control and trajectory tracking of a micro-quadrotor. Control of micro-quadrotors is a challenging problem due to its small size, strong coupling in pitch-yaw-roll and aerodynamic effects that often need to be ignored in the control design process to avoid mathematical complexities. In the proposed SNAC aided NDI approach, the gains of the dynamic inversion design are selected in such a way that the resulting controller behaves closely to a pre-synthesized SNAC controller for the output regulation problem. However, since SNAC is based on optimal control theory, it makes the dynamic inversion controller to operate near optimal and enhances its robustness property as well. More important, it retains two major benefits of dynamic inversion: (i) closed form expression of the controller and (ii) easy scalability to command tracking application even without any apriori knowledge of the reference command. Effectiveness of the proposed controller is demonstrated from six degree-of-freedom simulation studies of a micro-quadrotor. It has also been observed that the proposed SNAC aided NDI approach is more robust to modeling inaccuracies, as compared to the NDI controller designed independently from time domain specifications.

Nonlinear Dynamic Inversion(NDI) control has excellent rapidity and decoupling ability, unfortunately it lacks the essential robustness to disturbance. From the perspective of enhancing the robustness, an adaptive NDI method based on L1 adaptive structure is proposed. The L1 adaptive structure is introduced into the NDI control to enhance its robustness, which also guarantees the stability and expected dynamic performance of the system suffering from the disturbance influence. Secondly, the flight control law of the advanced aircraft is designed based on the present method to improve the robustness and fault tolerance of the flight control system. Finally, the effectiveness of the flight control law based on the present approach is verified under the fault disturbance. The results showed that the flight control law based on L1 adaptive NDI has excellent dynamic performance and strong robustness to parameter uncertainties and disturbances.

This paper describes a dual-loop control scheme for fault tolerant flight control system design. The dual-loop controller consists of an outer loop controller–so-called adaptive neural sliding mode control (ANSC) and an inner loop controller designed by using nonlinear dynamic inversion (NDI) technique. The merits of adaptive neural network and sliding mode control scheme are that 1) the ability of adaptive neural network control to deal with unstructured uncertainty and 2) the ability of sliding mode control to guarantee transient response. Using timescale separation principal, the aircraft dynamics can be decomposed into fast and slow dynamics and the decomposed dynamics are inversed for NDI controllers. For real-time pilot simulation, one-stage inverse dynamics is used and the pilot inputs are translated to roll, pitch and yaw rate commands. For cascade NDI, two-stage dynamic inversion is used. The stability analysis of the proposed controller is performed using Lyapunov theory. To verify the effectiveness of the proposed control scheme, numerical simulation is performed for six degree-of-freedom nonlinear aircraft model while a failure occurs in longitudinal control surface. Simulation results demonstrate that closedloop system has good performance while encountering lock-in-place, partial destruction and floating actuator failures. Nomenclature stick long δ , stick lat δ , stick dir δ = pilot inputs for longitudinal, lateral and directional command dir lon lat K K K , , = sticks and pedal gains ref p , ref q , ref r = reference model rate commands cmd z n , cmd y n = normal and lateral acceleration command

The traditional aircraft controller design is usually based on the off-line aerodynamic model. Due to the deviation of the off-line aerodynamic model, the flight quality is difficult to meet the requirements when the aircraft is flying in the real atmosphere. To solve this problem, this paper proposes a frequency domain identification-based improved adaptive nonlinear dynamic inversion (NDI) control method (FDI-ANDI). In this paper, an online recursive aerodynamic parameter identification method in the frequency domain is first designed, and then an adaptive dynamic inversion control method based on the online aerodynamic parameter identification results is established. Finally, aiming at the problem of the slow response speed of the NDI controller, an improved adaptive dynamic inversion control law is designed by using the method of series lead correction. Compared with the traditional control method, the adaptive dynamic inversion method based on online aerodynamic identification has stronger robustness and a faster response speed in the face of model uncertainty. The final simulation analysis shows that the method has a better control effect than the traditional control method.

High performance aircraft of the future will be designed to be lighter, more maneuverable, and operate over an ever expanding flight envelope. This set of conditions will necessarily mean highly flexible vehicles operating in nonlinear regimes. A methodology proposed to better optimize their responses to both pilot input and external disturbances, as well as to decrease the cost of vehicle design is the novel dynamic inversion. The attractiveness of this methodology lies in the fact that the inherent nonlinearities of the problem and the coupled nature of flexible dynamics are explicitly considered. The contribution of this work to the state of the art is predicated on the development and application of the novel dynamic inversion methodology to handle highly flexible aircraft in an integrated flight/structural mode control manner. The unprecedented small separation between rigid body and flexible dynamics as well as the reciprocal interaction between them due to flight control action are the key elements of the aircraft model. The novel approach to the nonlinear dynamic inversion allows the methodology to more intelligently handle flexible dynamics in the context of the dual objectives of integrated flight/SMC control by altering flexible mode damping without cancellation; thus, improving disturbance response and avoiding the potentially destabilizing effect of pole cancellation close to the j-omega-axis in case of modeling uncertainty. The necessary level of model complexity for design has been established with particular attention given to understanding physics. The effect of uncertainty in the structural mode dynamics has been addressed. Further contribution of this work addresses the issue of stability of the dynamic systems driven by nonlinear controllers. One result shows how assessing stability of an n-dimensional system can be reduced to checking stability of a two-dimensional one using algebraic expressions that are based on the vehicle characteristics such as aerodynamic coefficients. This reduces a complicated dynamical problem to something purely algebraic and manageably complex. Another approach is based on algorithmically finding a local Lyapunov function using sum of squares. The presented results are the first to address the question of stability for the nonlinear dynamic inversion in the presence of flexible dynamics.

This paper focuses on the design of a disturbance rejection controller for a tailless aircraft based on the technique of nonlinear dynamic inversion (NDI). The tailless aircraft model mounted on a three degree-of-freedom (3-DOF) dynamic rig in the wind tunnel is modeled as a nonlinear affine system subject to mismatched disturbances. First of all, a baseline NDI attitude controller is designed for sufficient stability and good reference tracking performance of the nominal system. Then, a nonlinear disturbance observer (NDO) is supplemented to the baseline NDI controller to estimate the lumped disturbances for compensation, including unmodeled dynamics, parameter uncertainties, and external disturbances. Mathematical analysis demonstrates the convergence of the employed NDO and the resulting closed-loop system. Furthermore, an anti-windup modification is applied to the NDO for control performance preserving in the presence of actuator saturation. Subsequently, the designed control schemes are preliminarily validated and compared via simulations. The baseline NDI controller demonstrates satisfactory attitude tracking performance in the case of nominal simulation; the NDO augmented NDI controller presents significantly improved ability of disturbance rejection when compared with the baseline NDI controller in the case of robust simulation; the anti-windup modified scheme, rather than the baseline NDI controller nor the NDO augmented NDI controller, can preserve the closed-loop performance in the case of actuator saturation. Finally, the baseline NDI scheme and the NDO augmented NDI scheme are implemented and further validated in the wind tunnel flight tests, which demonstrate that the experimental results are in good agreement with that of the simulations.

The so-called "New Space era" has seen a disruptive change in the business models and manufacturing technologies of launch vehicle companies. However, limited consideration has been given to the benefits that innovation in control theory can bring; not only in terms of increasing the limits of performance but also reducing mission preparation or "missionisation" efforts. Moreover, there is a gap between the current state-of-practice that still relies on linear controls and other modern control techniques that could bring relevant improvements in launcher attitude control; this is the case for nonlinear control algorithms, especially those based on Nonlinear Dynamic Inversion (NDI). NDI is a technique that basically 'cancels' the nonlinearities of a class of nonlinear systems, allowing for a single linear control law to be applied without the need for gain-scheduling across different operational points. Incremental NDI (INDI) is a variation of NDI that generates incremental commands and employs acceleration feedback to reduce model dependency, making it easier to design, and results in being more robust in closed-loop. While INDI has been applied successfully to several aerospace applications, its applicability to launch vehicles has not yet been adequately investigated. The objective of this paper is therefore to introduce and raise awareness of the INDI method among the launcher guidance, navigation, and control (GNC) community, showcasing its implementation on a representative launch ascent application scenario which highlights INDI's strengths and challenges. We present a new, practical approach for stability analysis of INDI for attitude control, and compare INDI with scheduled PD controllers with-and without angular acceleration estimates. Results show that, while INDI controllers are generally more sensitive to sensor noise and actuator delay than linear controllers, their potential benefits outweigh these limitations in terms of robustness and performance.

This paper proposes a hybrid Nonlinear Dynamic Inversion (NDI) control method for the high angle of attack super-maneuverable flight control. In the post-stall flight regime, the problems of nonlinearity, time varying, coupling and uncertainties would arise, which is a big challenge for the flight control method. A hybrid NDI control method based on the angular acceleration feedback control is proposed to increase system robustness and performance. It is inspired by the idea of the NDI and the Increment NDI (INDI) control methods, and contains three parts: feedforward control, proportional control, and logical integral control. The hybrid NDI control method can not only increase system robustness, but also improve the system dynamic performance. To demonstrate the effectiveness of the method in the post-stall flight control, numerical simulations are conducted to evaluate its ability to handle system uncertainties, time-varying problems, and nonlinear factors. Simulation results show that the system responses are almost not affected by these complex, troublesome factors and have good performance and robustness.

This paper studied an intelligent adaptive flight control method. The classic dynamic inversion control provides automatic adaptation at the flight point, which is particularly suited to aerospace vehicles (aircraft, pitchers or entry vehicles). However, the inversion process is sensitive to modeling errors. A possible improvement method is to compensate these errors. In this paper, neural networks have been applied to solve this problem. A reentry hypersonic vehicle has been taken as an example for application. The kinematic equations of this system found an unstable, multivariable, and nonlinear model which contains several uncertain parameters. The main idea is to firstly divide the variables into two groups according to their rates of change, and build two close loops of dynamic inversion separately for each group; then a compensation controller is designed using neural networks. Finally the simulation demonstrates the effectiveness of this technique.

Dynamic inversion is a category of control design techniques that employ feedback linearization. In recent years; this technique has been applied to different types of nonlinear systems. This paper presents its usefulness with nonlinear electromechanical systems. Dynamic inversion method is employed to ensure robustness and stability of the system. Moreover, the inputs can be found and achieve high-precision output tracking. The proposed inputs are referred as the inverse input. This technique has been applied a two mass model system.

This paper presents a novel configuration for guidance and tracking control laws for unmanned air vehicles (UAV) based on an extended nonlinear dynamic inversion (NLDI) approach. Current outer/inner loop architectures use dynamic inversion for the outer loop controller while using linear compensation-type control for inner loops. That design, although it performs well at nominal conditions, lacks robustness under certain upset flight conditions. The design proposed in this paper includes inner and outer loop control modules that both rely on the use of an NLDI control scheme. The main objective of the control laws is to minimize forward, lateral, and vertical distances with respect to a desired trajectory, and maintain stability and adequate performance in the presence of sub-system failures and upset environmental conditions. The implementation of this control laws scheme is illustrated through a simulation example using a mathematical model of the West Virginia University (WVU) YF-22 UAV. The performance of the control laws is evaluated during autonomous flight in terms of trajectory tracking errors and control activity at nominal and abnormal conditions including actuator and sensor failures and excessive turbulence. The results obtained with the WVU UAV simulation environment show that for all cases investigated the extended NLDI approach has desirable fault tolerant capabilities.

An integrated methodology incorporating both nonlinear dynamic inversion and sliding mode control method is employed to design a robust nonlinear controller for reusable launch vehicle reentry attitude control. Stability proof and robustness analysis were conducted. Specific issues related to the torque allocation part for RLV have been discussed. The current controller architecture addresses those uncertainties and modeling errors which pertain to the fast dynamics and large envelope flight.

This paper presents a Single Network Adaptive Critic (SNAC) aided Nonlinear Dynamic Inversion (NDI) optimization controller with a Proportional-Derivative (PD) based Optimal Control Modification (OCM) design for fast pitch rate adaptation in an MRAC flight control system. The advantages of adding SNAC to the NDI MRAC controller with OCM adaptation are presented. It is seen from simulation results that the SNAC aided NDI controller with the OCM adaptation has fewer high frequency oscillations and increased robustness to the different network architectures of the OCM. Three variations of OCM uncertainty estimation basis functions, namely the OCM – Linear (OCM-L), OCM – Bias (OCM-B) and OCM Linear and Bias (OCM-LB) are included in this paper. The responses of the SNAC aided NDI and traditional NDI controllers, using the same OCM adaptation technique are compared. Simulation results run on a nonlinear model of a small single piston engine are included for demonstration.

The nonlinear dynamic inversion (DI) control techniques are used in leader-follower unmanned aerial vehicle (UAV) dynamics modelling considering new input variables in the present paper. Three separate DI controllers are developed for holding the velocity, heading and flight path angles of both UAVs in a synchronous manner. A numerical simulation is performed at the end for validating this formation control mission of multiple UAVs. The quantitative estimation of reduction in follower drag while in close formation flight is also calculated along with the controller design.

A new nonlinear control strategy incorporated the dynamic inversion method with wavelet neural networks is presented for the nonlinear coupling system of Bank-to-Turn(BTT) missile in reentry phase. The basic control law is designed by using the dynamic inversion feedback linearization method, and the online learning wavelet neural network is used to compensate the inversion error due to aerodynamic parameter errors, modeling imprecise and external disturbance in view of the time-frequency localization properties of wavelet transform. Weights adjusting laws are derived according to Lyapunov stability theory, which can guarantee the boundedness of all signals in the whole system. Furthermore, robust stability of the closed-loop system under this tracking law is proved. Finally, the six degree-of-freedom(6DOF) simulation results have shown that the attitude angles can track the anticipant command precisely under the circumstances of existing external disturbance and in the presence of parameter uncertainty. It means that the dependence on model by dynamic inversion method is reduced and the robustness of control system is enhanced by using wavelet neural network(WNN) to reconstruct inversion error on-line.