A Nonlinear Model Predictive Control scheme for cooperative manipulation with singularity and collision avoidance
Alexandros Nikou,Christos K. Verginis,Shahab Heshmati-alamdari,Dimos V. Dimarogonas +3 more
- pp 707-712
TLDR
In this article, the authors propose a nonlinear model predictive control (NMPC) scheme that guarantees the navigation of the object to a desired pose in a bounded workspace with obstacles, while complying with certain input saturations of the agents.Abstract:
This paper addresses the problem of cooperative transportation of an object rigidly grasped by N robotic agents. In particular, we propose a Nonlinear Model Predictive Control (NMPC) scheme that guarantees the navigation of the object to a desired pose in a bounded workspace with obstacles, while complying with certain input saturations of the agents. Moreover, the proposed methodology ensures that the agents do not collide with each other or with the workspace obstacles as well as that they do not pass through singular configurations. The feasibility and convergence analysis of the NMPC are explicitly provided. Finally, simulation results illustrate the validity and efficiency of the proposed method.read more
Citations
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Journal ArticleDOI
Routing and collision avoidance techniques for unmanned aerial vehicles: Analysis, optimal solutions, and future directions
Bhisham Sharma,Mohammad S. Obaidat,Mohammad S. Obaidat,Mohammad S. Obaidat,Vinay Sharma,Kuei-Fang Hsiao +5 more
TL;DR: There are various routing techniques, real‐time applications of UAVs which are elaborated in this paper, namely, representative, cooperative, and noncooperative techniques, and collision avoidance techniques which are very important for the obstacle‐free environment.
Journal ArticleDOI
Recurrent Neural Network-Based Robust Nonsingular Sliding Mode Control With Input Saturation for a Non-Holonomic Spherical Robot
Shu-Bo Chen,Alireza Beigi,Amin Yousefpour,Farhad Rajaee,Hadi Jahanshahi,Stelios Bekiros,Raul Martinez,Yu-Ming Chu +7 more
TL;DR: A recurrent neural network-based robust nonsingular sliding mode control is proposed for stabilization and tracking control of the system and the performance of the proposed control technique for the uncertain system in the presence of an external disturbance, unknown input saturation, and dynamic uncertainties has been investigated.
Journal ArticleDOI
Robust Cooperative Manipulation Without Force/Torque Measurements: Control Design and Experiments
TL;DR: In this article, two control methodologies for the cooperative manipulation of an object by $N$ robotic agents are presented, one of which employs quaternion feedback for the object orientation to avoid potential representation singularities.
Journal ArticleDOI
Decentralized tube‐based model predictive control of uncertain nonlinear multiagent systems
TL;DR: This paper addresses the problem of decentralized tube-based nonlinear Model Predictive Control for a class of uncertain nonlinear continuous-time multi-agent systems with additive and bounded disturbance and proposes a decentralized feedback control protocol that guarantees that the initially connected agents remain connected for all times.
Proceedings ArticleDOI
Communication-based Decentralized Cooperative Object Transportation Using Nonlinear Model Predictive Control
TL;DR: A decentralized Nonlinear Model Predictive Control (NMPC) scheme that guarantees the navigation of the object to a desired pose in a bounded workspace with obstacles, while complying with certain input saturations of the agents.
References
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A Quasi-Infinite Horizon Nonlinear Model Predictive Control Scheme with Guaranteed Stability
Hong Chen,Frank Allgöwer +1 more
TL;DR: It is proved that feasibility of the open-loop optimal control problem at time t = 0 implies asymptotic stability of the closed-loop system.
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State and output feedback nonlinear model predictive control: An overview
TL;DR: In this article, the authors give a review on the current state of nonlinear model predictive control (NMPC) and derive conditions that guarantee stability of the closed-loop if an NMPC state feedback controller is used together with a full state observer for the recovery of the system state.
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Contractive model predictive control for constrained nonlinear systems
TL;DR: It is shown in this work that the implementation of this additional constraint into the online optimization makes it possible to prove strong nominal stability properties of the closed-loop system.
Journal ArticleDOI
A General Framework to Design Stabilizing Nonlinear Model Predictive Controllers
TL;DR: In this paper, a new model predictive control (MPC) framework is proposed to generate feedback controls for time-varying nonlinear systems with input constraints, and a set of conditions on the design parameters that permits to verify a priori the stabilizing properties of the control strategies considered.