A Novel Experimental Model and a Drag-Optimal Allocation Method for Variable-Pitch Propellers in Multirotors

Arellano-Quintana, Victor; Merchán-Cruz, Emmanuel Alejandro; Franchi, Antonio

doi:10.1109/access.2018.2879636

Cited by 15 publications

(22 citation statements)

References 15 publications

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“…Moreover, the joint deployment of blade pitch and rotor speed supports an efficient control allocation that allows to avoid cross-coupling effects while generating rotor-based steering torques without increasing aerodynamic drag, as conventional aerodynamic rudders do. Other advantages are [60,62,63]:…”

Section: Blade Pitchmentioning

confidence: 99%

Dynamic Modeling and Analysis of Tilt-Wing Electric Vertical Take-Off and Landing Vehicles

May

Milz

Looye

2022

AIAA SCITECH 2022 Forum

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Electric vertical take-off and landing (eVTOL) aircraft enable new transport options in regional and urban air mobility. One promising but only little investigated and understood subcategory comprises tilt-wing eVTOLs. They offer high efficiency and long flight ranges but come with a trade-off in increased complexity. Consequently, a critical step towards market entry is the development of mature and safe hybrid pilot-autonomy control systems, including fault detection, identification, and recovery (FDIR) concepts. That requires a mid-fidelity dynamic model with sufficient accuracy, which is not yet available despite a long history of tilt-wing research. Without a representative model, no detailed analysis and identification of a trimmed transition trajectory could be performed. This, however, is a crucial step in the development of a control system. We approach the problem by applying and combining current modeling approaches. Furthermore, a trim analysis of different flight phases, including the transition, is conducted. The identified model lays the foundation for a representative and detailed development and investigation of future control designs, bringing tilt-wing eVTOLs closer to airworthiness.

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Section: Blade Pitchmentioning

confidence: 99%

Dynamic Modeling and Analysis of Tilt-Wing Electric Vertical Take-Off and Landing Vehicles

May

Milz

Looye

2022

AIAA SCITECH 2022 Forum

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“…3-4, allows the proposed MPC framework to be seamlessly adaptable to the particular thrust generation model specified by the user. Therefore, also different and more accurate thrust models, such as, e.g., [35] can be easily integrated in our framework.…”

Section: Model Of a Multi-rotor Platformmentioning

confidence: 99%

Nonlinear Model Predictive Control with Enhanced Actuator Model for Multi-Rotor Aerial Vehicles with Generic Designs

Bicego

Mazzetto

Carli

et al. 2020

J Intell Robot Syst

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In this paper, we propose, discuss, and validate an online Nonlinear Model Predictive Control (NMPC) method for multi-rotor aerial systems with arbitrarily positioned and oriented rotors which simultaneously addresses the local reference trajectory planning and tracking problems. This work brings into question some common modeling and control design choices that are typically adopted to guarantee robustness and reliability but which may severely limit the attainable performance. Unlike most of state of the art works, the proposed method takes advantages of a unified nonlinear model which aims to describe the whole robot dynamics by explicitly including a realistic physical description of the actuator dynamics and limitations. As a matter of fact, our solution does not resort to common simplifications such as: (1) linear model approximation, (2) cascaded control paradigm used to decouple the translational and the rotational dynamics of the rigid body, (3) use of low-level reactive trackers for the stabilization of the internal loop, and (4) unconstrained optimization resolution or use of fictitious constraints. More in detail, we consider as control inputs the derivatives of the propeller forces and propose a novel method to suitably identify the actuator limitations by leveraging experimental data. Differently from previous approaches, the constraints of the optimization problem are defined only by the real physics of the actuators, avoiding conservative – and often not physical – input/state saturations which are present, e.g., in cascaded approaches. The control algorithm is implemented using a state-of-the-art Real Time Iteration (RTI) scheme with partial sensitivity update method. The performances of the control system are finally validated by means of real-time simulations and in real experiments, with a large spectrum of heterogeneous multi-rotor systems: an under-actuated quadrotor, a fully-actuated hexarotor, a multi-rotor with orientable propellers, and a multi-rotor with an unexpected rotor failure. To the best of our knowledge, this is the first time that a predictive controller framework with all the valuable aforementioned features is presented and extensively validated in real-time experiments and simulations.

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“…Leaving the dependence of the model equations on f i , see ( 3)-( 4), allows the proposed MPC framework to be seamlessly adaptable to the particular thrust generation model specified by the user. Therefore, also different and more accurate thrust models, such as, e.g., [35] can be easily integrated in our framework.…”

Section: Model Of a Multi-rotor Platformmentioning

confidence: 99%

Nonlinear Model Predictive Control with Enhanced Actuator Model for Multi-Rotor Aerial Vehicles with Generic Designs

Bicego,

Mazzetto,

Carli

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

In this paper we propose, test, and validate an online Nonlinear Model Predictive Control (NMPC) method applied to multi-rotor aerial systems with arbitrarily positioned and oriented rotors. This work brings into question some common modeling and control design choices that are typically adopted in order to guarantee robustness and reliability but which may severely limit the attainable performance. In particular the proposed method does not resort to common simplifications such as: 1) linear model approximation, 2) cascaded control paradigm used to decouple the translational and the rotational dynamics of the rigid body, and 3) use of low level reactive trackers for stabilization, 4) unconstrained system or use of fictitious constraints. The method addresses simultaneously the problem of local reference trajectory planning and that of stabilizing the vehicle dynamics. Furthermore, by considering as control inputs the derivatives of the forces generated by the multirotor vehicle and by means of a novel actuator modeling approach, the method avoids conservative -and often fictitious -input/state saturations which are present, e.g., in cascaded approaches. The control algorithm is implemented using a state-of-the-art Real Time Iteration (RTI) scheme with partial sensitivity update method. The performances of the control system are finally validated by means of real-time simulations and in real experiments, with a large spectrum of multi-rotor systems: an under-actuated quadrotor, a fully

show abstract

A Novel Experimental Model and a Drag-Optimal Allocation Method for Variable-Pitch Propellers in Multirotors

Cited by 15 publications

References 15 publications

Dynamic Modeling and Analysis of Tilt-Wing Electric Vertical Take-Off and Landing Vehicles

Dynamic Modeling and Analysis of Tilt-Wing Electric Vertical Take-Off and Landing Vehicles

Nonlinear Model Predictive Control with Enhanced Actuator Model for Multi-Rotor Aerial Vehicles with Generic Designs

Nonlinear Model Predictive Control with Enhanced Actuator Model for Multi-Rotor Aerial Vehicles with Generic Designs

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