Modeling and switching adaptive control for nonlinear morphing aircraft considering actuator dynamics

The morphing aircraft can obtain the best aerodynamic characteristics by changing its shape in order to adapt to the current mission and environment. In this paper, a non-affine parameter-dependent linear variable parameter (LPV) system model of a morphing aircraft whose wingspan and sweep angle can be changed is used as the object. First, the linear fractional form (LFR) is used to design an integral sliding mode that converges in a finite time. Then, the fuzzy switching gain adjustment method is introduced to eliminate the interference items and uncertain items in the nonlinear system. The simulation results show that the method can ensure the stability of the variant process in the presence of large disturbances and uncertainties. This controller design method has universal adaptability to LPV system.

The physical model of a variable-span variable-sweep morphing aircraft was simplified. Based on Kane's method,the morphing movements were assumed to be controllable known input,and the wings' movements were expressed by constraint equations. The six components of the translational velocity and the angular velocity of the morphing aircraft's body in the body coordinate frame were selected as the generalized speeds. Six degree-of-freedom dynamic model was built. Additional forces and additional moments were defined to describe the dynamic influence imposed on the morphing aircraft by the morphing movement. The simulation results show that,in the condition of steady-state flight,the additional forces and moments cased by the wings' morphing are small compared to the variations of aerodynamic forces. The aircraft's longitudinal dynamic responses during the morphing process are simulated and analyzed at different morphing speeds. Results show that the aircraft 's height,velocity and pitch angle will change considerably during morphing process.

A summary of a program to design, develop, and evaluate a hybrid learning augmented longitudinal flight control system for a high performance aircraft is presented. In addition to the learning augmented (hybrid) controller, two baseline controllers (a linear compensator and an adaptive controller) were also developed for purposes of comparison. The three share the same basic structure: all are model-reference controllers, the hybrid system is a learning augmented version of the adaptive controller, which is an adaptive version of the linear compensator. Each was designed to serve as a longitudinal control augmentation system to improve the basic handling qualities of a three-degree-of-freedom, nonlinear aircraft model. The hybrid controller was trained by exposing it to a number of transient responses of this aircraft. The transients were initiated by applying different stick inputs to the aircraft at randomly selected trim conditions throughout a subsonic flight envelope. The desired pitch rate responses corresponding to the same stick inputs and flight conditions were generated by a simple linearized reference model, scheduled on altitude and Mach number. Performance statistics were obtained for all three controllers by analyzing the pitch rate tracking error experienced over a variety of different flight conditions. >

Morphing aircraft offer superior properties as compared to non-morphing aircraft. They can achieve this by adapting their shape depending on the requirements of various conflicting flight conditions. These shape changes are often associated with large deformations and strains, and hence dedicated morphing concepts are developed to carry out the required changes in shape. Such intricate mechanisms are often heavy, which reduces, or even completely cancels, the performance increase of the morphing aircraft. Part of this weight penalty is determined by the required actuators and associated batteries, which are mainly driven by the required actuation force and energy. Two underexposed influences on the actuation force and energy are the flight condition at which morphing should take place and the order of the morphing manoeuvres, also called morphing scheduling. This paper aims at highlighting the importance of both influences by using a small Unmanned Aerial Vehicle (UAV) with different morphing mechanisms as an example. The results in this paper are generated using a morphing aircraft analysis and design code that was developed at the Delft University of Technology. The importance of the flight condition and a proper morphing schedule is demonstrated by investigating the required actuation forces for various flight conditions and morphing sequences. More importantly, the results show that there is not necessarily one optimal flight condition or morphing schedule and a tradeoff needs to be made.

The purpose of this paper is to present linear parameter varying modeling and simulation of a folding-wing morphing aircraft in the wing-folding process. Morphing aircraft can alter the shape to adapt to mission environment changing. When the wing shape is varying, the dynamic responses of the morphing aircraft will be dependent on the time-varying aerodynamic forces and moments, which will be a function of the wing shape change by the morphing command. The folding-wing morphing aircraft is regarded as a variable geometry rigid body, and the six-degree-of-freedom nonlinear dynamic model in the wing-folding process is founded. The decoupled longitudinal dynamic equation of the morphing process is deduced by simplification, and the longitudinal dynamic responses of the wing morphing process are numerically simulated by the quasi-steady aerodynamic assumption. Furthermore, using the Jacobian linearization approach, the longitudinal nonlinear dynamics equations of morphing aircraft are linearized, and the longitudinal linear parameter varying model of the morphing aircraft in the wing-folding process is obtained. Finally, the linear parameter varying model is validated by the open-loop time responses compared to the nonlinear aircraft responses. The research results can be as great reference for the linear parameter varying controller design for the morphing aircraft in the wing shape varying.

This paper presents an adaptive neural control for the longitudinal dynamics of a morphing aircraft. Based on the functional decomposition, it is reasonable to decompose the longitudinal dynamics into velocity and altitude subsystems. As for the velocity subsystem, the adaptive control is proposed via dynamic inversion method using neural network. To deal with input constraints, the additional compensation system is employed to help engine recover from input saturation rapidly. The highlight is that high order integral chained differentiator is used to estimate the newly defined variables and an adaptive neural controller is designed for the altitude subsystem where only one neural network is employed to approximate the lumped uncertain nonlinearity. The altitude subsystem controller is considerably simpler than the ones based on backstepping. It is proved using Lyapunov stability theory that the proposed control law can ensure that all the tracking error converges to an arbitrarily small neighborhood around zero. Numerical simulation study demonstrates the effectiveness of the proposed strategy, during the morphing process, in spite of some uncertain system nonlinearity.

Morphing aircraft can adaptively regulate their aerodynamic layout to meet the demands of varying flight conditions, improve their aerodynamic efficiency, and reduce their energy consumption. The design and fabrication of high-performance, lightweight, and intelligent morphing structures have become a hot topic in advanced aircraft design. This paper discusses morphing aircraft development history, structural characteristics, existing applications, and future prospects. First, some conventional mechanical morphing aircraft are examined with focus on their morphing modes, mechanisms, advantages, and disadvantages. Second, the novel applications of several technologies for morphing unmanned aerial vehicles, including additive manufacturing for fabricating complex morphing structures, lattice technology for reducing structural weight, and multi-mode morphing combined with flexible skins and foldable structures, are summarized and categorized. Moreover, in consideration of the further development of active morphing aircraft, the paper reviews morphing structures driven by smart material actuators, such as shape memory alloy and macro-fiber composites, and analyzes their advantages and limitations. Third, the paper discusses multiple challenges, including flexible structures, flexible skins, and control systems, in the design of future morphing aircraft. Lastly, the development and application of morphing structures in the aerospace field are discussed to provide a reference for future research and engineering applications.

Aircraft flight dynamics trim is the basis for the large civil aircraft flight dynamics characteristics analysis. In this paper, the full nonlinear flight dynamics model of civil aircraft is systematically deduced, an iterative trim method for the six-degree-of-freedom flight dynamics model based on the Downhill Simplex optimization algorithm is designed, and the trim accuracy and computational efficiency of the Downhill Simplex optimization algorithm are analyzed and the variation of trim variables under different initial weights is studied. Results show that the Downhill Simplex optimization algorithm can effectively solve the six-degree-of-freedom full nonlinear aerodynamics trim problem of large civil aircraft under the condition of straight forward and level flight, and the trim deviation can be controlled within the range of ±0.05N/Nm within 500 steps. The flight dynamics iterative trim method based on the Downhill Simplex optimization algorithm designed in this paper can provide reference and technical support for civil aircraft flight simulation, flight dynamics characteristics and flight quality research.

Aircraft are non-minimum phase, MIMO and highly nonlinear systems which undergo significant disturbances and variation in system parameters during operation. In spite of the prosperous literature in adaptive control, application of the promising control strategy on aircraft control has been restricted by the lack of assurance in closed-loop stability. This paper proposes a robust adaptive control scheme for aircraft. The scheme is composed of an inner-level adaptive fuzzy PD control law and an outer-level supervisory control law. Importantly, the outer-level controller of the two-level scheme is designed based on a fuzzy model which takes non-minimum phase phenomena and modeling error explicitly into account. Numerical studies of the tracking control of a five degree of freedom aircraft system demonstrate the effectiveness of the proposed control strategy in the face of bursting disturbances.

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.

High-Efficient parametric aeroelastic modeling and experimental validation for a morphing aircraft testbed

The morphing aircraft can change different wing shapes or geometries to achieve the optimal flight performance according to various mission scenarios. In this paper, DATCOM is used to calculate aerodynamic parameters based on Firebee UAV morphing aircraft with different wing configurations and analyze aerodynamic characteristics. A novel adaptive wing morphing strategy for morphing aircraft based on reinforcement learning method is proposed. This method can highly meet the demand of keeping optimal performance in multiple flight conditions, and the adaptive wing morphing strategy, three-loop normal load altitude controller and sliding mode velocity controller can together make sure stability of morphing aircraft during morphing process with good tracking performance.

Recent advances in adaptive structures and advanced compact actuators have renewed interest in variable geometry aircraft that can change shape in flight to obtain better performance during dissimilar flight conditions. These new morphing aircraft may allow for shape changes beyond the current variable sweep and variable camber available in the F-111 or F-14 aircraft. Because of the potential for a wider range of shape changes, significant effort has been put forth to develop strategies for the conceptual sizing of such vehicles, including the “morphing as an independent variable” sizing approach that allows the use of continuous optimization techniques to size the morphing aircraft. Although these previous aircraft sizing studies have predicted advantages for variable geometry in performance and weight by conventional design comparisons, this paper extends the evaluation by investigating the effectiveness of a morphing aircraft design in a fleet of aircraft. A key feature of this work involves creating surrogate models to approximate the capability of an aircraft or a fleet of aircraft as a function of parameters describing the aircraft design mission. These capability surrogate models, coupled with similarlyconstructed cost models, enable the design of a best fleet in which the number of aircraft and the design parameters of the aircraft may be determined simultaneously. The approach here uses some initial simplifications to the approach and relies upon enumerating a number of discrete choices, but it suggests that more formalized approaches could be used for this kind of aircraft fleet design problem. For the morphing aircraft application, comparisons of the best fleet of morphing aircraft offer improvements in capability and cost over the best fleet of fixed-geometry aircraft for an example search-and-find concept of operations.

With the development of robot control theory and the requirement for robot to provide better performance in uncertain working environment, more and more research interests have been attracted to the two research topics of dealing with kinematic uncertainty existing in the robot system and considering actuator dynamics into the controller design during the past one decade. However, the studies in these two research areas have been developing separately in the literature. This thesis is dedicated to solve the adaptive control problems of robot in the presence of all uncertainties in the kinematics, manipulator dynamics and actuator dynamics. The main contribution of the thesis is that a novel adaptive regressor design method is proposed which enables the adaptation of different kinds of uncertainties simultaneously during the control process. Based on the novel regressor design, adaptive control methods have been proposed for regulation and tracking control of robot with uncertain kinematics, manipulator and actuator dynamics. These approaches constitute the first results in the research area of robot control to deal with both kinematic and actuator dynamic uncertainties. Through Lyapunov analysis, the stability of the closed-loop systems are shown to be guaranteed and the sufficient conditions to be satisfied are explicitly presented.

SUMMARYTo the best of our knowledge, this is the first paper focus on the adaptive impedance control of robot manipulators with consideration of joint flexibility and actuator dynamics. Controller design for this problem is difficult because each joint of the robot has to be described by a fifth-order cascade differential equation. In this paper, a backstepping-like procedure incorporating the model reference adaptive control strategy is employed to construct the impedance controller. The function approximation technique is applied to estimate time-varying uncertainties in the system dynamics. The proposed control law is free from the calculation of the tedious regressor matrix, which is a significant simplification in implementation. Closed-loop stability and boundedness of internal signals are proved by the Lyapunov-like analysis with consideration of the function approximation error. Computer simulation results are presented to demonstrate the usefulness of the proposed scheme.