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 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.
Highlights
In the last decade, thanks to the development of both new hardware technologies and software algorithms, the employment of Multi-Rotor Aerial Vehicles (MRAVs) has significantly spread across a wide set of challenging reallife applications, thanks to their vertical take-off and landing (VTOL) and hovering capabilities, their agility, relatively compact structure, good robustness, and low cost
We provided an unfeasible rotational profile on purpose with the intent of showing that the proposed Nonlinear Model Predictive Control (NMPC) scheme can manage the re-generation and tracking of a generic trajectory, subject to the limitations imposed by the particular MRAV under analysis, without the need to resort, e.g., to differential flatness
We have presented an NMPC framework tailored to generic multi-directional thrust MRAVs with arbitrarily positioned and oriented rotors, which considers a novel and more representative model for the actuators of such systems compared to the ones often employed by other works
Summary
Thanks to the development of both new hardware technologies and software algorithms, the employment of Multi-Rotor Aerial Vehicles (MRAVs) has significantly spread across a wide set of challenging reallife applications, thanks to their vertical take-off and landing (VTOL) and hovering capabilities, their agility, relatively compact structure, good robustness, and low cost. Recent platforms characterized by particular actuator arrangements can exploit the multidirectional-thrust (MDT) capability, i.e., the possibility to exert forces in more than one direction without the need to re-orient their body frame, allowing to partially decouple the robot rotational dynamics from the translational one. A subset of this class is represented by the so-called fully-actuated systems, for which the control force can be varied in all directions, disregarding the actuator constraints Vehicles of this kind have been demonstrated to be suitable for the accomplishment of aerial physical interactions tasks [2, 3], i.e., operations which require an active contact and a consequent exchange of energy between the robots and the surrounding environment. Examples of such operations are grasping, transportation and manipulation of loads, contact-based inspection tasks, and building/decommissioning of structures
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