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This chapter describes the behaviour of a transport aircraft and its systems during rolling. Notations and conventions are given first, followed by the main equations of motion. Loads affecting aircraft motion are then described and their modelling given. Finally a short aircraft behaviour analysis is provided. This chapter aims at offering the reader a clear understanding of the control application and its requirements.

This chapter provides the main guidelines for the control design and analysis of a “rolling on the ground” control law. The rolling of aircraft is a very challenging task in term of piloting. The overall design of transport aircraft is clearly not optimized for rolling on ground but for flight. Its natural rolling qualities are very poor, both in term of stability and performance. Besides the coupling of aerodynamic loads, engine-thrusts, gravity and friction loads at the contact point of each tyre produce highly nonlinear and time-varying dynamics. These dynamics are strongly influenced by many parameters such as the velocity, the runway state, aircraft configuration (mass and inertia) and external disturbances like wind turbulence or gusts. The control objectives may also vary depending on the rolling phase: taxiing, runway acceleration prior to take-off, runway deceleration after landing, and runway deceleration after a rejected take-off.

In this chapter we describe the simulation model ADMIRE. ADMIRE is an advanced generic simulation model of a modern delta-canard fighter aircraft. The model is based on the Generic Aerodata Model (GAM), developed by Saab AB.

This chapter gives a description of the requirements on the design and analysis of new Flight Control Laws (FCL’s) for the ADMIRE model. The ADMIRE model is currently augmented with “conventional” FCL’s. These are to be replaced with new FCL’s based on new non-linear design methods. The current ADMIRE FCL’s shall be used for the purposes of comparison with the new FCL’s. The objective of the design task is to show the potential of different non-linear methods for aircraft flight control.

In this chapter, a general nonlinear symbolic LFT modelling framework and its supporting LFT tools are presented. The modelling approach developed combines the natural modularity and clarity of presentation from LFT modelling with the ease of manipulation from symbolic algebra. It results in an exact nonlinear symbolic LFT that represents an ideal starting point to apply subsequent assumptions and simplifications to finally transform the model into an approximated symbolic LFT ready for design and analysis. The development of the framework is supported by a novel algebraic algorithm for symbolic matrix decomposition and two new LFT operations: nested substitution and symbolic differentiation.

In this chapter, the challenging problem of aircraft on-ground modelling for control design and analysis is dealt with using a novel NDI-based force identification approach and a general nonlinear symbolic LFT modelling framework. It is shown how the modelling framework is applicable to derive an exact LFT model of the aircraft-on-ground as well as some simplified design-oriented versions. An important contribution is the proposed force identification method, which allows nonlinear ground forces to be replaced with saturation-type nonlinearities. As a result, the simplified model boils down to a reduced-order LFT plant where the Δ block only contains time-varying or constant (but uncertain) parameters on the one hand, and saturation-type non-linearities on the other hand. Such a model is then very useful for applying modern analysis and synthesis techniques.

Based on the LFT model of the on-ground aircraft developed in Chapter 6, an anti-windup control technique is proposed to improve lateral control laws which have been designed using classical methods. The original idea of this work consists in taking advantage of a simplified representation of the nonlinear lateral ground forces, which are approximated by saturation-type nonlinearities. The anti-windup compensator is then implemented on the full nonlinear aircraft model using an on-line estimator of the ground forces. Simulations demonstrate the efficiency of the resulting adaptive controller.

Object-oriented modelling allows for efficient construction of multi-disciplinary system models in a physically-oriented way. As a unique feature, the modelling approach allows for automatic generation of regular, static, as well as inverse simulation models. Inverse models form the basis of various commonly used nonlinear controller synthesis methods, such as Feedback Linearisation. The resulting multivariable control laws are easily tuned to meet performance specifications and avoid the need for gain scheduling. In combination with automatic inversion, these synthesis methods are ideally suited for control law rapid prototyping, allowing experimentation with command variables, control selection and allocation, etc. in very short automated design cycles. After selection of the final architecture, the control laws may be developed further in a detailed design stage. In this chapter, we demonstrate this approach on the aircraft-on-ground nonlinear control problem.

In this chapter, the robustness properties of the adaptive anti-windup controller designed in Chapter 7 are evaluated, with special emphasis on the high uncertainty level affecting the nonlinear ground forces. It is first shown how to convert the initial nonlinear problem into a fairly standard robustness analysis problem versus mixed time-invariant/time-varying uncertainties. An original approach, based on the notion of semi-positive realness, is then introduced to solve the problem. The application of this method to the on-ground aircraft finally reveals the good robustness properties of the lateral controller despite uncertainties and saturation effects. It also gives some relevant information that enables further improvements to be made to the design.

This chapter presents the design and evaluation of an LPV control law for the ADMIRE model over a specified wide flight envelope, including subsonic, transonic and supersonic regions. The design of the LPV control law is based on the parameter-dependent Lyapunov function approach with gridding of the parameter space. It is demonstrated that by using a linear piece-wise interpolation of the aircraft model the LPV approach allows the design of a controller for the whole flight envelope (including the transonic region) with satisfactory performance and robustness characteristics. The longitudinal LPV controller provides an automatic transition from the α-demand system at Mach numbers M < 0.58 to the n _z-demand system at M < 0.62; in the intermediate region a mixed control principle is implemented. A thorough evaluation of the designed LPV controllers is performed using a number of methods, including time and frequency domain criteria, linear and nonlinear simulation tests, and also piloted simulation in real time on the HELIFLIGHT simulator at the University of Liverpool. The performed evaluation clearly demonstrates that the designed LPV control laws satisfy most of the design requirements. Ways of further improving the performance of the LPV controller are discussed at the end of the chapter.