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

被引:0
|
作者
Davide Bicego
Jacopo Mazzetto
Ruggero Carli
Marcello Farina
Antonio Franchi
机构
[1] University of Twente,Robotics and Mechatronics group
[2] Université de Toulouse,LAAS
[3] University of Padova,CNRS
[4] Politecnico of Milano,Department of Information Engineering
来源
关键词
Model predictive control; Multi-rotor aerial vehicles; Multi-directional thrust; Actuator constraints;
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:1213 / 1247
页数:34
相关论文
共 50 条
  • [1] Nonlinear Model Predictive Control with Enhanced Actuator Model for Multi-Rotor Aerial Vehicles with Generic Designs
    Bicego, Davide
    Mazzetto, Jacopo
    Carli, Ruggero
    Farina, Marcello
    Franchi, Antonio
    [J]. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2020, 100 (3-4) : 1213 - 1247
  • [2] Nonlinear Model Predictive Control for a multi-rotor with heavy slung load
    Trachte, Jan
    Gonzalez, Felipe
    McFadyen, Aaron
    [J]. 2014 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS), 2014, : 1105 - 1110
  • [3] Nonlinear Control of Multi-Rotor Aerial Vehicles Based on the Zero-Moment Direction
    Michieletto, Giulia
    Cenedese, Angelo
    Zaccarian, Luca
    Franchi, Antonio
    [J]. IFAC PAPERSONLINE, 2017, 50 (01): : 13144 - 13149
  • [4] Position and attitude control of multi-rotor aerial vehicles: A survey
    Nascimento, Tiago P.
    Saska, Martin
    [J]. ANNUAL REVIEWS IN CONTROL, 2019, 48 : 129 - 146
  • [5] ANALYSIS AND SYNTHESIS OF MULTI-ROTOR AERIAL VEHICLES
    Jiang, Qimi
    Mellinger, Daniel
    Kappeyne, Christine
    Kumar, Vijay
    [J]. PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE - 2011, VOL 6, PTS A AND B, 2012, : 711 - 720
  • [6] Guided Time-Optimal Model Predictive Control of a Multi-Rotor
    Zhang, Guangyu
    Zheng, Yongjie
    He, Yuqing
    Yang, Liying
    Nie, Hongyu
    Huang, Chaoxiong
    Zhao, Yiwen
    [J]. IEEE CONTROL SYSTEMS LETTERS, 2023, 7 : 1658 - 1663
  • [7] Formation Control and Target Interception for Multiple Multi-rotor Aerial Vehicles
    Karras, George C.
    Bechlioulis, Charalampos P.
    Fourlas, George K.
    Kyriakopoulos, Kostas J.
    [J]. 2020 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS'20), 2020, : 85 - 92
  • [8] Model Predictive Control of a Multi-Rotor with a Suspended Load for Avoiding Obstacles
    Son, Clark Youngdong
    Seo, Hoseong
    Kim, Taewan
    Kim, H. Jin
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2018, : 5233 - 5238
  • [9] Model Predictive Control of a Multi-Rotor with a Slung Load for Avoiding Obstacles
    Son, Clark Youngdong
    Kim, Taewan
    Kim, Suseong
    Kim, H. Jin
    [J]. 2017 14TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI), 2017, : 232 - 237
  • [10] Nonlinear MPC Without Terminal Costs or Constraints for Multi-Rotor Aerial Vehicles
    Gomaa, Mahmoud A. K.
    De Silva, Oscar
    Mann, George K., I
    Gosine, Raymond G.
    [J]. IEEE CONTROL SYSTEMS LETTERS, 2022, 6 : 440 - 445