This paper describes the design, implementation and flight testing of flight control laws based on Incremental Nonlinear Dynamic Inversion (INDI). The method compares commanded and measured accelerations to compute increments on the current control deflections. This results in highly robust control solutions with respect to model uncertainties as well as changes in aircraft dynamic characteristics of failure cases during flight. At the same time, the complexity of the algorithms is similar to classical ones. The key for practical implementation is in ensuring synchronization between angular acceleration and control deflection measurements or estimates. The underlying theory and practical design methods of INDI are very well understood, but implementation and testing has remained limited to sub-scale UAVs. The main contribution of this paper is to present the design and validation of manual attitude control functions for a Cessna Citation II experimental aircraft, covering control structure design, application of INDI, design optimization, robustness analyses, software implementation, ground and flight testing. For comparison, also control laws based on classical Nonlinear Dynamic Inversion were implemented and flown. The flight tests were highly successful and marked the first successful demonstration of INDI on a CS-25 certified aircraft. The flight test results proved that INDI clearly outperforms NDI and provided valuable lessons-learnt for future applications. Nomenclature A x , A y , A z Specific forces along body X/Y/Z axis, g C Dimensionless coefficient F Force, N J Inertia matrix, kg•m 2 J Moment of Inertia, kg•m 2 K Gain M Moment, Nm M Mach number N 1 Fan speed, s −1 S Wing surface area, m 2 V Velocity vector, m/s V Airspeed, m/s a x , a y , a z Linear accelerations along body X/Y/Z axis, m/s 2 b Wing span, m 2 c Mean aerodynamic chord, m

A computer assisted modelling methodology is developed for the generation of linearized models with parametric uncertainties described by Linear Fractional Transformations (LFTs). The starting point of the uncertainty modelling is a class of generic nonlinear aircraft models with explicit parametric dependence used for simulation purposes. The proposed methodology integrates specialized software tools for object-oriented modelling, for simulation, and for numerical as well as symbolic computations. The methodology has many generic features being applicable to similar nonlinear model classes.

In this paper we give a theoretical and a computational solution to the most general inner-outer factorization problem formulated for a discrete-time system G. Our method is based on descriptor state-space computations and relies on an efficient dislocation of the minimal indices and of the "unstable" zeros of G by left multiplication with all-pass factors. The minimal indices are dislocated by solving for the stabilizing solution an algebraic Riccati equation of order n (the sum of left minimal indices) while the n b unstable zeros are dislocated by solving a Lyapunov equation of order n b. The results reported here are a nontrivial extension of a recently developed approach to the continuous-time inner-outer factorization problem.

This paper discusses the design, implementation and flight testing of an incremental Backstepping (IBS) based manual flight control law with angular accelerometer (AA) feedback. The main advantages of incremental control laws is that they only require a partial model of the system and are of low complexity. Incremental control laws for aircraft rotational motion, however, need angular acceleration measurements to compute the control increments. Previously, estimates based on angular rate measurements were used for this. The newly implemented AA feedback is expected to improve the performance by decreasing the sensor delay. The manual control laws command roll rate/angle, side slip angle and angle of attack and have been implemented on a Cessna Citation II aircraft, which is equipped with an experimental fly-by-wire system. The IBS based control law has an integrated integral control term and uses Pseudo Control Hedging to handle actuator saturations. A load factor outerloop has been added to improve the manual flyability. The IBS based control law has highly satisfactory performance in flight. Test manoeuvres included standard roll and load factor commands and asymmetric thrust handling. Fault tolerance has been compared in a nonlinear simulation for the controllers with and without AA feedback in simulation. In general, the angular accelerometer feedback improved the tolerance to mismatch substantially. Nomenclature A x , A y , A z Linear accelerations along body x,y, and z axis, g C D,Y, L Dimensionless Force coefficients along stability x,y, and z axis C l,m,n Dimensionless Moment coefficients around body x,y, and z axis F A , F T Aerodynamic and Propulsive Force vectors, N G Control dependent part of the model I Inertia matrix, kgm 2 K Gain M A ,M T Aerodynamic and Propulsive Moment vectors, Nm M Mach number S Wing surface area, m 2 T AB Rotation Matrix from reference frame B to A V Velocity vector, m/s V TAS , V CAS True air speed and calibrated air speed, m/s V Lyapunov function W Weight, N X, Y, Z Position, m b Wing span, m 2 c Mean aerodynamic chord, m f Control independent part of the model f x , f y , f z Specific forces along body x,y, and z axis, g g Gravitational acceleration, m/s 2

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