Control Design Methods for Good Flying Qualities

Hodgkinson, J.

doi:10.2514/6.2009-6319

Cited by 17 publications

(6 citation statements)

References 6 publications

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“…(1) can be linearized about the current point in time indicated by the subscript '0', see Eq. (2). As such, the variables x 0 ,ẋ 0 and u 0 are given by the latest available measurements, while the variables x,ẋ and u are in the future.…”

Section: A Continuous-time Indimentioning

confidence: 99%

Stability and Robustness Analysis and Improvements for Incremental Nonlinear Dynamic Inversion Control

Veld

Kampen

Chu

2018

2018 AIAA Guidance, Navigation, and Control Conference

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Incremental nonlinear dynamic inversion (INDI) is a variation on nonlinear dynamic inversion (NDI), retaining the high-performance characteristics, while reducing model dependency and increasing robustness. After a successful flight test with a multirotor micro aerial vehicle, the question arises whether this technique can be used to successfully design a flight control system for aircraft in general. This requires additional research on aircraft characteristics that could cause issues related to the stability and performance of the INDI controller. Typical characteristics are additional time delays due to data buses and measurement systems, slower actuator and sensor dynamics, and a lower control frequency. The main contributions of this article are 1) an analytical stability analysis showing that implementing discrete-time INDI with a sampling time smaller than 0.02s results in large stability margins regarding system characteristics and controller gains; 2) a simulation study showing significant performance degradation requiring controller adaptation due to actuator measurement bias, angular rate measurement noise, angular rate measurement delay and actuator measurement delay; and 3) the use of a real-time time delay identification algorithm based on latency to successfully synchronize the angular rate and actuator measurement delay together with pseudo control hedging (PCH) to prevent oscillatory behavior.

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Section: A Continuous-time Indimentioning

confidence: 99%

Stability and Robustness Analysis and Improvements for Incremental Nonlinear Dynamic Inversion Control

Veld

Kampen

Chu

2018

2018 AIAA Guidance, Navigation, and Control Conference

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“…Figure 11 shows the contribution of reconstructed angle-of-attack, α inertial , and measured angle-of-attack, α measured to the complementary filtered angle-of-attack. As expected, the inertial and measured components sum to 1.0, as indicated by Equation 6 and Figure 11. Additionally, there is a similarly constructed complementary filter on true airspeed.…”

Section: Filtersmentioning

confidence: 64%

Longitudinal Control Law Design and Handling Qualities Optimization for a Business Jet Flight Control System

Berger¹,

Tischler

Hagerott³

et al. 2012

AIAA Atmospheric Flight Mechanics Conference

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A comprehensive set of stability, handling qualities, and performance specifications was used to drive the optimization of commonly used fixed-wing longitudinal control laws applied to a business jet. The specifications were divided into two tiers. The first were the key flight control and handling qualities requirements and were used directly for optimization, while the second were used as a check afterwards. Similarities between the commonly used longitudinal control laws investigated in this study and a model following controller were exploited to explicitly set feed-forward gains to provide good handling qualities. A linear-quadratic regulator method was employed for preliminary design as a way to initialize the control law feedback gain values for optimization. A multi-objective parametric optimization approach was then used to arrive at feedback gains that concurrently satisfy all specifications. Using this optimization approach, the trade-offs of increased crossover frequency were investigated. In addition, a smooth gain schedule was generated by optimizing the control law parameters of different flight conditions to meet the same requirements. This paper describes the control law architecture used as well as the optimization approach, the specifications used, and the design results. Nomenclature α Angle-of-attack [deg, rad] α cmd Angle-of-attack command [rad] α nz Steady state angle-of-attack per normal load factor [rad/g] q Dynamic pressure [psf] δ act Actuator position [deg] δ stk Stick force [lb] α Angle-of-attack rate [deg/sec, rad/sec] α cmd Angle-of-attack rate command [rad/sec] δ act Actuator rate [deg/sec] n z cmd Commanded normal load factor rate [g/sec] q Pitch acceleration [rad/sec 2 ] ω c Crossover frequency [rad/sec] ω n Natural frequency [rad/sec] ω α LQR output shaping function frequency of complex-pair target zeros [rad/sec] ω cmd Command model frequency [rad/sec] ω inv Inverse model frequency [rad/sec] ω sp Short-period frequency [rad/sec] φ Bank angle [rad] τ Time delay [sec] τ n Normal acceleration transfer function equivalent time delay [sec] τ q Pitch rate transfer function equivalent time delay [sec] τ cmd Command time delay [sec] θ Pitch attitude [deg, rad] θ DB Pitch attitude dropback [deg] ζ Damping ratio [-] ζ α LQR output shaping function damping of complex-pair target zeros [-] ζ cmd Command model damping [-] ζ inv Inverse model damping [-] ζ sp Short-period damping [-] a LQR output shaping function real zero [rad/sec] g Acceleration due to gravity [ft/sec 2 ] J LOES LOES fit cost J M F Model following cost K Control law gain K n Normal acceleration transfer function gain [g/deg-elev] K q Pitch rate transfer function gain [rad/sec/deg-elev] K stk Stick gain [g/lb] K u Speed error gain [g/kt] M α Dimensional pitch stiffness derivative [1/sec] M δe Dimensional pitch rate control derivative [rad/sec 2 /deg − elev] n/α Steady-state normal acceleration change per unit change of angle-of-attack [g/rad] n z Normal acceleration [g] n z Normal load factor at the ICR [g] n z u, n z +u No...

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“…Prior to the 1990s, the design method of flight control law for production fighter aircraft adopted the classical control theories such as proportional-integral-derivatives (PID) [1,2]. In recent years, modern highly maneuverable fighter aircraft have applied more advanced multivariable control techniques to flight control law design to improve flying and handling qualities.…”

Section: Introductionmentioning

confidence: 99%

Stability Margin and Structural Coupling Analysis of a Hybrid INDI Control for the Fighter Aircraft

Kim

Koh

et al. 2021

Int. J. Aeronaut. Space Sci.

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The sensor-based incremental nonlinear dynamic inversion (INDI) using angular acceleration measured by inertial measurement unit (IMU) sensor is a very robust control method on various model uncertainties when the aircraft maneuvers with moderate angle-of-attack (AoA) and high gravity in transonic speed flight conditions. However, the measured angular acceleration has time delay characteristics due to actuator and aircraft dynamics, IMU sensor dynamics, differential angular rate and structural coupling filter (SCF) and so on. These characteristics of angular acceleration feedback reduce dramatically the stability margin of the control system. In this paper, we propose the synchronization filter design method of the control surface feedback path for improving stability margin, based on the proposed hybrid INDI control method using error between the angular acceleration measured from IMU sensor and the angular acceleration calculated from on-board model (OBM) and control surface feedback. To evaluate the proposed control method, we perform the frequency-domain linear analysis and the time-domain simulation. As a result of the evaluation, synchronization method of control surface feedback not only improves the stability margin characteristics of the control system but also eliminates the structural coupling in low frequency range by designing the control surface command feedback using actuator command which is the output of flight control computer (FLCC).

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Control Design Methods for Good Flying Qualities

Cited by 17 publications

References 6 publications

Stability and Robustness Analysis and Improvements for Incremental Nonlinear Dynamic Inversion Control

Stability and Robustness Analysis and Improvements for Incremental Nonlinear Dynamic Inversion Control

Longitudinal Control Law Design and Handling Qualities Optimization for a Business Jet Flight Control System

Stability Margin and Structural Coupling Analysis of a Hybrid INDI Control for the Fighter Aircraft

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