References of "Kannan, Somasundar 50002069"
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See detailImplementation and validation of an event-based real-time nonlinear model predictive control framework with ROS interface for single and multi-robot systems
Dentler, Jan Eric UL; Kannan, Somasundar UL; Olivares Mendez, Miguel Angel UL et al

in 2017 IEEE Conference on Control Technology and Applications (CCTA) (2017, August 30)

This paper presents the implementation and experimental validation of a central control framework. The presented framework addresses the need for a controller, which provides high performance combined ... [more ▼]

This paper presents the implementation and experimental validation of a central control framework. The presented framework addresses the need for a controller, which provides high performance combined with a low-computational load while being on-line adaptable to changes in the control scenario. Examples for such scenarios are cooperative control, task-based control and fault-tolerant control, where the system's topology, dynamics, objectives and constraints are changing. The framework combines a fast Nonlinear Model Predictive Control (NMPC), a communication interface with the Robot Operating System (ROS) [1] as well as a modularization that allows an event-based change of the NMPC scenario. To experimentally validate performance and event-based adaptability of the framework, this paper is using a cooperative control scenario of Unmanned Aerial Vehicles (UAVs). The source code of the proposed framework is available under [2]. [less ▲]

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See detailA real-time model predictive position control with collision avoidance for commercial low-cost quadrotors
Dentler, Jan Eric UL; Kannan, Somasundar UL; Olivares Mendez, Miguel Angel UL et al

in IEEE Multi-Conference on Systems and Control (MSC 2016), Buenos Aires, Argentina, 2016 (2016, September 20)

Unmanned aerial vehicles (UAVs) are the future technology for autonomous fast transportation of individual goods. They have the advantage of being small, fast and not to be limited to the local ... [more ▼]

Unmanned aerial vehicles (UAVs) are the future technology for autonomous fast transportation of individual goods. They have the advantage of being small, fast and not to be limited to the local infrastructure. This is not only interesting for delivery of private consumption goods up to the doorstep, but also particularly for smart factories. One drawback of autonomous drone technology is the high development costs, that limit research and development to a small audience. This work is introducing a position control with collision avoidance as a first step to make low-cost drones more accessible to the execution of autonomous tasks. The paper introduces a semilinear state-space model for a commercial quadrotor and its adaptation to the commercially available AR.Drone 2 system. The position control introduced in this paper is a model predictive control (MPC) based on a condensed multiple-shooting continuation generalized minimal residual method (CMSCGMRES). The collision avoidance is implemented in the MPC based on a sigmoid function. The real-time applicability of the proposed methods is demonstrated in two experiments with a real AR.Drone quadrotor, adressing position tracking and collision avoidance. The experiments show the computational efficiency of the proposed control design with a measured maximum computation time of less than 2ms. [less ▲]

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