@article {2020l-BicMazFarCarFra,
	title = {Nonlinear Model Predictive Control with Enhanced Actuator Model for Multi-Rotor Aerial Vehicles with Generic Designs},
	journal = {Journal of Intelligent and Robotic Systems},
	volume = {100},
	year = {2020},
	pages = {1213-1247},
	abstract = {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 ref- erence trajectory planning and tracking problems. This work brings into question some common modeling and control design choices that are typically adopted to guarantee ro- bustness and reliability but which may severely limit the at- tainable 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 ac- tuator dynamics and limitations. As a matter of fact, our so- lution does not resort to common simplifications such as: 1) linear model approximation, 2) cascaded control paradigm used to decouple the translational and the rotational dynam- ics 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 suit- ably identify the actuator limitations by leveraging experi- mental data. Differently from previous approaches, the con- straints of the optimization problem are defined only by the real physics of the actuators, avoiding conservative {\textendash} and often not physical {\textendash} input/state saturations which are present, e.g., in cascaded approaches. The control algorithm is im- plemented using a state-of-the-art Real Time Iteration (RTI) scheme with partial sensitivity update method. The perfor- mances 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 unex- pected 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 exten- sively validated in real-time experiments and simulations},
	doi = {10.1007/s10846-020-01250-9},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2020l-BicMazFarCarFra.pdf},
	author = {Davide Bicego and Jacopo Mazzetto and Marcello Farina and Ruggero Carli and Antonio Franchi}
}
