Adaptive Dynamic Inversion Research Articles

Research on an Ice Tolerance Control Method for Large Aircraft Based on Adaptive Dynamic Inversion

Considering the effect of icing on aircraft control performance, this paper proposes an adaptive dynamic inverse ice tolerance control method based on piecewise constant. A control allocation algorithm is introduced to compensate for the change of control surface performance caused by icing. This method can achieve satisfactory disturbance estimation accuracy under a given sampling time, and thus ensure a closed-loop system error within an acceptable range. The proposed design method is applied to the design of a flight control law for a transport aircraft, aiming to solve the problem of ice-tolerant flight control, reduce the influence of icing conditions on controllability and safe flight of the transport aircraft, and thus improve the flight quality of the transport aircraft. The simulation results are verified under the influence of both standby ice type and failure ice type, and the interference effect on aircraft aerodynamic parameters is further added. The simulation results show that adaptive dynamic inverse control based on piecewise constant can overcome the influence caused by icing and aerodynamic parameter interference, achieve accurate tracking of command, and provide excellent fault tolerance and robustness, which ensures that the transport aircraft can achieve the desired control performance and safe flight capability.

Adaptive Bounding-Based Dynamic Inversion Control of a Coaxial Compound Helicopter

Adaptive Bounding-Based Dynamic Inversion Control of a Coaxial Compound Helicopter

Improved Adaptive NDI Flight Control Law Design Based on Real-Time Aerodynamic Identification in Frequency Domain

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.

Improved model reference‐based adaptive nonlinear dynamic inversion for fault‐tolerant flight control

AbstractDue to lack of robustness, Nonlinear Dynamic Inversion (NDI) control cannot resist the influence of disturbances. In this paper, an adaptive fault‐tolerant control method, called Improved Model Reference‐based Adaptive NDI (IMR‐ANDI), is proposed and applied to develop a fault‐tolerant flight controller to improve robustness to faults and disturbances. To improve the estimation accuracy, this paper also modified the piecewise‐constant adaptation, which improves the accuracy of adaptive estimation without increasing the sampling frequency. Moreover, a low‐pass filter is introduced to the control law creatively to weaken the disturbance of high‐frequency dynamics to the adaptation, which balances the dynamic performance and robustness as well as prevents the system oscillation. Finally, a fault‐tolerant flight controller is developed based on the IMR‐ANDI and verified under the actuator fault and center of gravity variations. All simulation and hardware‐in‐the‐loop experiment results conform to the theoretical analysis, indicating that the developed IMR‐ANDI fault‐tolerant controller is robust to faults and disturbances and can achieve expected control performance.

Modified adaptive discrete-time incremental nonlinear dynamic inversion control for quad-rotors in the presence of motor faults

Unmanned air vehicles are intrinsically non-linear, unstable, uncertain, and prone to a variety of faults, most commonly the motor faults. The main objective of this paper is to develop a fault-tolerant control algorithm for the quadrotors with the motor faults. Accordingly, a novel adaptive modified incremental nonlinear dynamic inversion (MINDI) control is proposed to stabilize and control the quad-rotor with partial motor faults. The controller consists of a MINDI controller augmented with a discrete-time nonlinear adaptive algorithm. Since the incremental nonlinear dynamic inversion (INDI) algorithm is essentially based on the sensor measurements, it necessitates the angular rates differentiation and therefore amplifies the high-frequency noises produced by the gyroscopes. The application of derivative filters causes unavoidable internal state delays in the INDI structure. Henceforth, the performance of the controller developed for the unstable and uncertain quadrotors degrades considerably. To address this drawback, this paper proposes the MINDI controller which basically derives the angular accelerations from the angular moment estimations. Furthermore, to increase the robustness of the MINDI against motor faults, a discrete-time adaptive controller has been incorporated. The performance of the proposed controllers is verified both through the nonlinear simulations and testbed experiments. The results are compared with a recent efficient algorithm, which had been implemented on a quad-rotor model.

Sliding Mode Disturbance Observer-Based Adaptive Dynamic Inversion Fault-Tolerant Control for Fixed-Wing UAV

Unmanned aerial vehicles (UAVs) have been widely applied over the past decades, especially in the military field. Due to the unpredictability of the flight environment and failures, higher requirements are placed on the design of the control system of the fixed-wing UAV. In this study, a sliding mode disturbance observer-based (SMDO) adaptive dynamic inversion fault-tolerant controller was designed, which includes an outer-loop sliding mode observer-based disturbance suppression dynamic inversion controller and an inner-loop real-time aerodynamic identification-based adaptive fault-tolerant dynamic inversion controller. The sliding mode disturbance observer in the outer-loop controller was designed based on the second-order super-twisting algorithm to alleviate chattering. The aerodynamic identification in the inner-loop controller adopts the recursive least squares algorithm to update the aerodynamic model of the UAV online, thereby realizing the fault-tolerant control for the control surface damage. The effectiveness of the proposed SMDO enhanced adaptive fault-tolerant control method was validated by mathematical simulation.

Improved Neural Adaptive Control for Nonlinear Oscillatory Dynamic of Flapping Wings

Modeling uncertainties and oscillatory dynamics are control challenges for flapping vehicles. Flapping-wing aerial vehicles are nonlinear time-varying oscillatory systems with flexible multibody dynamics. As such, accurate modeling of these complex systems considering unsteady aerodynamics is a formidable task. Though adaptive controllers can work well with uncertain approximate models, inherent oscillation of flapping systems can degrade their control performance and create undesired control actuations. This paper addresses improvements of neural adaptive dynamic inversion controller toward efficient performance for flapping flight via effective utility of actuator capacity. In this respect, first an assumptive model of a bird-mimetic flapping-wing is considered for simulation and analysis. It is shown that the usage of oscillatory feedback data produces additional error in trajectory tracking and unnecessary oscillatory control actuations. Subsequently, the control loop is modified by adding an adaptive notch filter for real-time estimation, tracking, and removal of dominant oscillatory modes from the feedback data and consequently from the controller output. As a result, the required control effort is effectively reduced and the controller performance is significantly improved. Simulations are provided to demonstrate the efficiency of the proposed scheme in presence of noise, variation of system frequency, disturbances, as well as delay in the control loop.

L1 Adaptive Structure-Based Nonlinear Dynamic Inversion Control for Aircraft with Center of Gravity Variations

L1 Adaptive Structure-Based Nonlinear Dynamic Inversion Control for Aircraft with Center of Gravity Variations

An adaptive dynamic inversion control method based on improved piecewise constant for flight control system

To overcome the lack of robustness of the nonlinear dynamic inversion (NDI) control, a simple and practical adaptive NDI control method based on an improved piecewise constant is proposed in this paper to enhance its robustness to disturbances and improve the accuracy of response tracking. Firstly, reasonable assumptions and analyses are made for the system with the influence of disturbance. Secondly, an improved piecewise constant adaptive NDI control method suitable for general flight control systems is proposed. The stability of the control system with disturbance and the error convergence range of the improved piecewise constant adaptive control are proved and analyzed theoretically. Finally, taking into account the fighter actual control requirements, the angular rates control strategy is given, and the proposed method is applied to the angular rates flight controller design. Matlab simulations are carried out under the disturbance of the actuator failure and the sudden change of the center of gravity, and the robustness and dynamic performance of the controller designed based on the present method is compared and verified. The results illustrate that our present method has stronger robustness and higher control accuracy.

Longitudinal automatic carrier-landing control law rejecting disturbances and coupling based on adaptive dynamic inversion

Longitudinal automatic carrier-landing control law rejecting disturbances and coupling based on adaptive dynamic inversion

Adaptive Neural Networks-Based Dynamic Inversion Applied to Reconfigurable Flight Control and Envelope Protection Under Icing Conditions

Aircraft icing can result in degradation of the aerodynamic characteristics and reduction of the control effectiveness, which would pose serious threats to flight safety. Reconfigurable flight control and envelope protection of iced aircraft have become an effective solution to ensure flight safety in icing encounters. In this study, the dynamic model of the iced aircraft was established, and high precision numerical simulation method and wind tunnel virtual flight experiment were applied to obtain the icing aerodynamic database. Furthermore, the reconfigurable flight control law was designed by using the adaptive neural networks based dynamic inversion (ANN-DI) control method. Simulation results demonstrate that the control method behaves well tracking performance and strong robustness in the presence of modeling errors and control surface damage. After that, an icing envelope protection system was designed based on control limiting strategy and the ANN-DI control was applied to calculate the control surface deflection limits based on the limit values of the key flight safety parameters. Finally, the designed icing envelope protection system has been verified through simulation in two autopilot modes under icing conditions. The simulation results obtained here show that the system could keep the key flight safety parameters such as the flight speed, the angle of attack (AOA), the side slip angle, and bank angle within the flight safe region under icing conditions. The method proposed in this study is expected to provide flight safety measures for in-flight icing.

Rapid Automatic Slung Load Operations with Unmanned Helicopters

Slung load operations often involve following conservative flight paths to prevent unwanted swing of the load. However, doing so often limits the maneuvering capability of the system and increases the time to complete trajectories. This work investigates methods to rapidly move a slung load with a helicopter with the intent to deliver it quickly and precisely to a fixed point. Inspired by prior work utilizing differential flatness, which is a property of certain systems that allow for advantageous controllers to be developed for nonlinear systems, the controller developed does not require instrumentation of the load or the ability to estimate the state of the load but does not preclude it. A feedforward and feedback controller was developed that modifies the helicopter commands based on the desired load path. The controller is simplified by neglecting selected higher order terms and modeling the load as a point-mass. An adaptive dynamic inversion controller is used to control the helicopter. A fixed downward-facing camera is used to provide estimates of load position for the feedback controller. Simulation and flight-test results are shown using a Yamaha R-MAX helicopter to validate the proposed method.

L1 adaptive dynamic inversion attitude control for unmanned aerial vehicle with actuator failures

This paper presents a hybrid attitude control scheme of L1 adaptive and dynamic inversion for unmanned aerial vehicle with actuator faults, where both gain fault and bias fault are considered. Firstly, dynamic inversion is employed to track attitude angles in the outer loop and ensures the rapid response. Secondly, an L1 adaptive controller for the inner loop is established to compensate for system uncertainty and uncertainty caused by actuator failures. Thirdly, the analysis of steady-state and transient performance is given by Lyapunov theory. Finally, simulation results prove the effectiveness of the proposed approach.

Robust Adaptive Nonlinear Dynamic Inversion Control for an Air-breathing Hypersonic Vehicle

This paper presents a robust adaptive nonlinear dynamic inversion control approach for the longitudinal dynamics of an air-breathing hypersonic vehicle. The proposed approach adopts a fast adaptation law using high-gain learning rate, while a low-pass filter is synthesized with the modified adaptive scheme to filter out the high-frequency content of the estimates. This modified high-gain adaptive scheme achieves a good transient process and a nice robust property with respect to parameter uncertainties, without exciting high-frequency oscillations. Based on input-output linearization, the nonlinear hypersonic dynamics are transformed into equivalent linear systems. Therefore, the pole placement technique is applied to design the baseline nonlinear dynamic inversion controller. Finally, the simulation results of the modified adaptive nonlinear dynamic inversion control law demonstrate the proposed control approach provides robust tracking of reference trajectories.

Optimization-based model reference adaptive control for dynamic positioning of a fully actuated underwater vehicle

This paper presents a predictive optimization-based model reference adaptive control (MRAC) approach for dynamic positioning (DP) of a fully actuated underwater vehicle subject to dynamic uncertainties and actuator saturation. Compared with conventional linear reference model-based approaches, this proposed MRAC controller utilizes an optimized reference model composed of the closed-loop approximate vehicle model under a nonlinear model predictive controller, in which both the state and input constraints are considered. An adaptive dynamic inversion controller is designed to track the reference trajectory in the presence of dynamic uncertainties, and a single hidden layer neural network is incorporated to compensate for the mismatch of the actual and approximate models and ensure the convergence of tracking errors. The effectiveness of the proposed DP approach is validated by comparative simulations performed with a remotely operated vehicle.

Acceleration measurement-based incremental nonlinear flight control for air-breathing hypersonic vehicles

In this paper, nonlinear flight control problem for Air-breathing Hypersonic Vehicles (AHVs) is addressed. Designing a high quality flight controller for AHVs is highly challenging due to model uncertainties caused by inherent structural/aerodynamic couplings, high nonlinearities within the large envelope. A nonlinear flight control approach named Sensor-Based Backstepping (SBB) is employed to design a highly robust controller for AHVs, and ensure that the controller does not suffer from large parameter variations and model uncertainties. The SBB approach is essentially an incremental type of approximate dynamic inversion (ADI) control scheme developed based on singular perturbation theory and multi-loop backstepping design methodology. The SBB uses angular accelerometers to capture dynamic changes in time derivatives of body angular rates, and requires nearly no accurate model information in its implementation. In this way, unlike model based adaptive nonlinear control laws such as adaptive nonlinear dynamic inversion (ANDI), dependency on accurate full model information and the associated identification workload is removed. Several key issues associated with inherent characteristics of AHVs before the SBB based AHV controller is developed. To validate the SBB flight controller, numerical simulations are performed on a nonlinear AHV model with sudden model parameter uncertainties introduced, and the controller is compared with the linear controller augmented Linear Quadratic Regulator (LQR) and the real-time model based ANDI controller. The results have demonstrated the superior tracking performance of the SBB approach, and highlighted its strong robustness to model uncertainties.

Prediction and Recovery of Aircraft Unstable Nonlinear Phenomena Using Bifurcation Analysis and Backstepping Method

To protect the aircraft flight safety across the envelope of angle of attack, bifurcation analysis and backstepping method are investigated to predict and suppress the unstable nonlinear flight phenomena. By applying bifurcation analysis and continuation method to the flight motion, the onsets of both the chaotic phenomenon called falling leaf motion and the catastrophe phenomenon named coupled jump behavior are derived. To stabilize these unstable motions, a backstepping and disturbance observer based flight controller is designed. According to the main function of the control surface, we divide the flight controller into the airspeed subsystem and the flight path subsystem, where the airspeed subsystem is regulated by an adaptive dynamic inversion controller while the flight path subsystem is stabilized by a third-order compound controller. Considering the parametric uncertainties of aerodynamics, three sliding mode disturbance observers are presented as compensators to approximate the compound uncertainties. Simulations demonstrate that the proposed controller can recover the aircraft from falling leaf motion or coupled jump behavior to straight level flying.

Multivariate Spline-Based Adaptive Control of High-Performance Aircraft with Aerodynamic Uncertainties

In this paper, a new modular adaptive control system is presented to compensate for aerodynamic uncertainties in high-performance flight control systems. This approach combines nonlinear dynamic inversion with multivariate spline-based adaptive control allocation. A new real-time identification routine for multivariate splines is presented to compensate for aerodynamic uncertainties in the control allocation system. This method, indicated as spline-based adaptive nonlinear dynamic inversion, is applied to control an F-16 aircraft subject to significant aerodynamics uncertainties. Simulation results indicate that the new controller can tune itself each time a model error is detected and has superior adaptability compared to an ordinary polynomial-based adaptive controller. Multivariate splines have sufficient flexibility and approximation power to accurately model nonlinear aerodynamics over the entire flight envelope. As a result, the global model remains intact. Although a part of the model is being reconfigured using incoming observations, the remainder of the model remains unchanged and can be used as an a priori source of information. This prevents the occurrence of sudden fundamental changes in the global model structure, which are experienced when using ordinary polynomials.

Adaptive Incremental Nonlinear Dynamic Inversion for Attitude Control of Micro Air Vehicles

Incremental nonlinear dynamic inversion is a sensor-based control approach that promises to provide high-performance nonlinear control without requiring a detailed model of the controlled vehicle. In the context of attitude control of micro air vehicles, incremental nonlinear dynamic inversion only uses a control effectiveness model and uses estimates of the angular accelerations to replace the rest of the model. This paper provides solutions for two major challenges of incremental nonlinear dynamic inversion control: how to deal with measurement and actuator delays, and how to deal with a changing control effectiveness. The main contributions of this article are 1) a proposed method to correctly take into account the delays occurring when deriving angular accelerations from angular rate measurements; 2) the introduction of adaptive incremental nonlinear dynamic inversion, which can estimate the control effectiveness online, eliminating the need for manual parameter estimation or tuning; and 3) the incorporation of the momentum of the propellers in the controller. This controller is suitable for vehicles that experience a different control effectiveness across their flight envelope. Furthermore, this approach requires only very coarse knowledge of model parameters in advance. Real-world experiments show the high performance, disturbance rejection, and adaptiveness properties.

L1 Adaptive Dynamic Inversion Controller for an X-wing Tail-sitter MAV in Hover Flight

This paper presents a hover flight attitude controller for a tail-sitter vertical take-off and landing (VTOL) micro aerial vehicle (MAV). The MAV named Novlit-3 combines a novel non-orthogonal X shaped wing layout with a single propeller, which is capable for high efficient cruise and prop-hang hover. Considering the nonlinear unstable dynamics and disturbance sensitivity of the VTOL MAV, we apply the L1 adaptive control theory to augment the baseline dynamic inversion controller. The L1 adaptive augmentation acts on the angular dynamics, estimating and compensating the time-varying uncertainty with fast adaptation rate and appropriate time-delay margin. The flight validation is executed on the Novlit-3 VTOL MAV