Extended incremental non-linear control allocation (XINCA) for quadplanes

Karssies, H.J.; Wagter, Christophe De

doi:10.1177/17568293211070825

Cited by 5 publications

(4 citation statements)

References 29 publications

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“…A key element of INDI is the control allocation, realizing the commanded pseudo controls by calculating setpoints for the actuators based on a simplified aircraft model. This can either be achieved by solving a quadratic programming problem as shown in [11,12,18], or by calculating a Moore-Penrose Inverse and conducting a null space transition as presented in [15,19]. Since hybrid VTOLs are usually overactuated, i.e., the required forces and torque can be created by different actuators, the solution of control allocation is often ambiguous.…”

Section: Introductionmentioning

confidence: 99%

Parameter Tuning Approach for Incremental Nonlinear Dynamic Inversion-Based Flight Controllers

Henkenjohann,

Nolte,

Sion

et al. 2024

Actuators

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Incremental nonlinear dynamic inversion (INDI) is a widely used approach to controlling UAVs with highly nonlinear dynamics. One key element of INDI-based controllers is the control allocation realizing pseudo controls using available actuators. However, the tracking of commanded pseudo controls is not the only objective considered during control allocation. Since the approach only works locally due to linearization and the solution is often ambiguous, additional aspects like control efforts or penalizing the deviation of certain states must be considered. Conducting the control allocation by solving a quadratic program this results in a considerable number of weighting parameters, which must be tuned during control design. Currently, this is conducted manually and is therefore time consuming. An automated approach for tuning these parameters is therefore highly beneficial. Thus, this paper presents and evaluates a model-based approach automatically tuning the control allocation parameters of a tiltrotor VTOL using an optimization algorithm. This optimization algorithm searches for optimal parameters minimizing a cost functional that reflects the design target. This cost functional is calculated based on a test mission for the VTOL which is conducted within a simulation environment. The test mission represents the common operating range of the VTOL. The simulation environment consists of an aircraft model as well as a model of the INDI-based controller which is dependent on the control allocation parameters. On this basis, model-based optimization is conducted and the optimal parameters are identified. Finally, successful real-world tests on a 4-degrees-of-freedom testbench using the identified parameters are presented. Since the control allocation parameters can significantly influence the aircraft’s stability, the 4-DOF testbench for the aircraft is required for rapid validation of the parameters at a minimum amount of risk.

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Section: Introductionmentioning

confidence: 99%

Parameter Tuning Approach for Incremental Nonlinear Dynamic Inversion-Based Flight Controllers

Henkenjohann,

Nolte,

Sion

et al. 2024

Actuators

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“…Unknown input observers have been used for real-time estimations of exogenous inputs, such as rotor efficiency loss faults in hexacopters [ 3 ], and to estimate multiple quadcopter rotor faults simultaneously by using nonlinear observers [ 4 ]. Sliding mode observers were also combined with incremental sliding mode control to enable the adaptive fault tolerant control of quadplanes with improved robustness to one rotor loss, compared to conventional linear quadratic regulator (LQR) based trajectory tracking [ 5 , 6 ]. Linear unknown input observers have also been used for the detection of icing [ 7 ], and for the diagnosis of fixed-wing UAV icing and actuator faults [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…In [ 28 ], integral sliding mode control was used to ensure fault tolerant control in an overactuated UAV, with a hardware-in-the-loop (HIL) validation. Other approaches use observer-based controllers as previously described in [ 5 , 6 , 11 , 14 ]. In [ 29 ], an adaptive multiple model approach was also shown to achieve efficient control of a quadplane using different models for the plane, quad and transition modes, with real-time updates of the trim conditions during transitioning.…”

Section: Introductionmentioning

confidence: 99%

Observer-Based Optimal Control of a Quadplane with Active Wind Disturbance and Actuator Fault Rejection

Zyadat

Horri

Innocente

et al. 2023

Sensors

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Hybrid aircraft configurations with combined cruise and vertical flight capabilities are increasingly being considered for unmanned aircraft and urban air mobility missions. To ensure the safety and autonomy of such missions, control challenges including fault tolerance and windy conditions must be addressed. This paper presents an observer-based optimal control approach for the active combined fault and wind disturbance rejection, with application to a quadplane unmanned aerial vehicle. The quadplane model is linearised for the longitudinal plane, vertical takeoff and landing and transition modes. Wind gusts are modelled using a Dryden turbulence model. An unknown input observer is first developed for the estimation of wind disturbance by defining an auxiliary variable that emulates body referenced accelerations. The approach is then extended to simultaneous rejection of intermittent elevator faults and wind disturbance velocities. Estimation error is mathematically proven to converge to zero, assuming a piecewise constant disturbance. A numerical simulation analysis demonstrates that for a typical quadplane flight profile at 100 m altitude, the observer-based wind gust and fault correction significantly enhances trajectory tracking accuracy compared to a linear quadratic regulator and to a H-infinity controller, which are both taken, without loss of generality, as benchmark controllers to be enhanced. This is done by adding wind and fault compensation terms to the controller with admissible control effort. The proposed observer is also shown to enhance accuracy and observer-based rejection of disturbances and faults compared to three alternative observers, based on output error integration, acceleration feedback and a sliding mode observer, respectively. The proposed approach is particularly efficient for the active rejection of actuator faults under windy conditions.

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“…32 In the work of Lu et al, 33 a fault-tolerant trajectory control law for an aircraft was studied based on INDI. Karssies 34 proposed an extended incremental nonlinear control allocation method for a quad-plane. In summary, INDI has been utilized in control law design for different aerial vehicles.…”

Section: Introductionmentioning

confidence: 99%

Incremental nonlinear dynamic inversion based path‐following control for a hybrid quad‐plane unmanned aerial vehicle

Zhou

Yang

Strampe

et al. 2022

Intl J Robust & Nonlinear

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Hybrid quad‐plane unmanned aerial vehicles (UAVs), which combine the advantages of multicopters and fixed‐wing UAVs, are gaining increasing attention. However, quad‐planes are characterized by complex structures, high nonlinearity, strong coupling, and three flight regimes (hover, transition, and fixed‐wing flight), which bring great challenges to the research of their control laws. This article aims to design control laws for a quad‐plane in fixed‐wing and hover flight regimes based on a robust nonlinear control method, incremental nonlinear dynamic inversion (INDI), so that the quad‐plane can follow a given path autonomously. Firstly, a mathematical model of the quad‐plane is established on the basis of kinematics and dynamics. Subsequently, cascade control structures are proposed and divided into inner and outer loops. A control law is designed for each control loop based on INDI. To improve the performance of the designed control law, reference models are added to the inner loops to shape the input commands and provide feedforward inputs. Finally, simulation results corroborate the performance and robustness of the proposed control law. Compared with the control law designed by active disturbance rejection control and proportional‐integral‐derivative control methods, the INDI‐based control law is more robust.

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Extended incremental non-linear control allocation (XINCA) for quadplanes

Cited by 5 publications

References 29 publications

Parameter Tuning Approach for Incremental Nonlinear Dynamic Inversion-Based Flight Controllers

Parameter Tuning Approach for Incremental Nonlinear Dynamic Inversion-Based Flight Controllers

Observer-Based Optimal Control of a Quadplane with Active Wind Disturbance and Actuator Fault Rejection

Incremental nonlinear dynamic inversion based path‐following control for a hybrid quad‐plane unmanned aerial vehicle

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