This package is providing an object oriented real-time nonlinear model predictive control (NMPC) framework which developed at the Automation & Robotics Research Group http://wwwde.uni.lu/snt/research/automation_robotics_research_group at the University of Luxembourg. It features a modularization for multi-agent systems which allows the on-line change of agents, control objectives, constraints and couplings, triggered by ROS-messages.

The GPLv3 licenced source code is available under https://github.com/snt-robotics/denmpc and https://github.com/DentOpt/denmpc . Proprietary licences are available under request.

It is based on following contributions:

• J. Dentler, S. Kannan, M. A. O. Mendez and H. Voos,
  "A modularization approach for nonlinear model predictive control of distributed fast systems",
  24th Mediterranean Conference on Control and Automation (MED), Athens, Greece, 2016, pp. 292-297.
  doi: 10.1109/MED.2016.7535973

• Jan Dentler and Somasundar Kannan and Miguel Angel Olivares Mendez and Holger Voos,
  "A real-time model predictive position control with collision avoidance for commercial low-cost quadrotors",
  Proceedings of 2016 IEEE Multi-Conference on Systems and Control (MSC 2016), Argentina, Buenos Aires, 2016

The used kernel solver is a "Condensed Multiple Shooting Generalized Minimal Residuum Method (CMSCGMRES)" developed by Prof. Dr. Toshiyuki OHTSUKA:

• Ohtsuka, T.,
  “A Continuation/GMRES Method for Fast Computation of Nonlinear Receding Horizon Control,”
  Automatica, Vol. 40, No. 4, Apr. 2004, pp. 563-574.

• Seguchi, H., and Ohtsuka, T.,
  “Nonlinear Receding Horizon Control of an Underactuated Hovercraft,”
  International Journal of Robust and Nonlinear Control, Vol. 13, Nos. 3-4, Mar.-Apr. 2003, pp. 381-398.

Its features include:

1. Nonlinear model predictive control (e.g. a quadrotor with nonlinear system dynamics)
2. Central control of single agent systems (e.g. a single robot)
3. Central control of multi-agent systems (e.g. multiple robots that are interacting)
4. Object oriented code to easily adapt it:
   • Controller: Interface class for implementations of controllers, e.g.CMSCGMRES
   • Agent: Interface class for implementations of agents, respective system or robot types, e.g. Quadrotor
   • Constraint: Interface class for implementations of single agent constraints
   • Coupling: Interface class for implementations for coupling agents
5. Open-source code

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A tutorial and application examples are currently under construction

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