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18 results on '"Van Parys, Ruben"'

2. Embedded nonlinear model predictive control for obstacle avoidance using PANOC

Author

Sathya, Ajay, Sopasakis, Pantelis, Van Parys, Ruben, Themelis, Andreas, Pipeleers, Goele, and Patrinos, Panagiotis

Subjects
Mathematics - Optimization and Control
Abstract

We employ the proximal averaged Newton-type method for optimal control (PANOC) to solve obstacle avoidance problems in real time. We introduce a novel modeling framework for obstacle avoidance which allows us to easily account for generic, possibly nonconvex, obstacles involving polytopes, ellipsoids, semialgebraic sets and generic sets described by a set of nonlinear inequalities. PANOC is particularly well-suited for embedded applications as it involves simple steps, its implementation comes with a low memory footprint and its fast convergence meets the tight runtime requirements of fast dynamical systems one encounters in modern mechatronics and robotics. The proposed obstacle avoidance scheme is tested on a lab-scale autonomous vehicle.

Published
2019
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7. Flexible Multi-Agent System for Distributed Coordination, Transportation & Localisation

Author

Van Parys, Ruben, Verbandt, Maarten, Kotzé, Marcus, Swevers, Jan, Bruyninckx, Herman, Philips, Johan, and Pipeleers, Goele

Abstract

© 2018 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. This demonstration presents Flexonomy, a flexible autonomous system for distributed coordination, transportation and localisation in a lab-scale factory floor. It illustrates the use of multi-agent systems in manufacturing and leverages new Industry 4.0 design principles to cope with manufacturing requirements in factories of the future: rapidly changing customer needs, market volatility and shortened product life cycles. Three main contributions are identified: (i) distributed auction-based coordination allows local decision making and task allocation, (ii) distributed model predictive control-based transportation enables free space collision avoidance of automated guided vehicles (AGVs), and (iii) distributed vision-based localisation provides scalable and dynamic position information of key resources on the factory floor. ispartof: pages:1832-1834 ispartof: Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems vol:3 pages:1832-1834 ispartof: International Conference on Autonomous Agents and Multiagent Systems location:Stockholm, Sweden date:11 Jul - 13 Jul 2018 status: published

Published
2018

9. Design of robust decentralised controllers for MIMO plants with delays through network structure exploitation.

Author

Dileep, Deesh, Van Parys, Ruben, Pipeleers, Goele, Hetel, Laurentiu, Richard, Jean-Pierre, and Michiels, Wim

Subjects
*MIMO systems, *COST functions, *ROBUST control, *ALGORITHMS, *MAXIMUM power point trackers
Abstract

A methodology is proposed for the design of robust controllers for retarded and neutral-type time-delay systems, focusing on decentralised and overlapping fixed-order controllers for Multiple Input Multiple Output (MIMO) systems. The methodology is grounded in a direct optimisation approach and relies on the minimisation of spectral abscissa and H ∞ cost functions, as a function of the controller or design parameters. First, an approach applicable to generic MIMO systems is presented, which imposes a suitable sparsity pattern with the possibility of fixing elements in the controller parameterisation. Second, if the system to be controlled has the structure of a network of coupled identical subsystems, then it is shown that this structure can be exploited by an improved algorithm for the design of decentralised controllers, thereby improving computational efficiency and scalability with the number of subsystems. Several numerical examples illustrate the effectiveness of the methodology, and its extension towards consensus type problems. [ABSTRACT FROM AUTHOR]

Published
2020
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18. Optimal Autonomous Quadrotor Navigation in an Obstructed Space

Author

Goele Pipeleers, Gianluca Rossetti, Ruben Van Parys, Fabrizio Giulietti, Giulietti, Fabrizio, Pipeleers, Goele, Rossetti, Gianluca, and Van Parys, Ruben

Subjects
Engineering, Control and Optimization, business.industry, Process (engineering), Aerospace Engineering, Thrust, Control engineering, Time horizon, Spline (mathematics), Model predictive control, Artificial Intelligence, Control theory, Modeling and Simulation, Trajectory, Motion planning, Multirotor, business
Abstract

This paper shows an ambitious methodology of autonomous navigation for multirotor UAVs in obstructed environments. The following strategy was formulated to ensure to ultirotor vehicles the capability to produce autonomously quasi-optimal and safe trajectories, although generally they have at their disposal limited computational resources on board. The problem is formuled in a model predictive control (MPC) architecture in which motion planning and trajectory tracking processes are solved separately like they were stored in two different devices. The first one uses a spline-based motion planning approach to generate smooth and safe trajectories. At this step also a multicopter’s simplified dynamic model and environment information are taken in account. The second one uses trajectory inputs (total thrust and attitude angle rates) to steer the multicopter during the flight. Both adequate time horizon and update frequency are chosen in order to take in account disturbances and dynamics model mismatch. The following methodology will be validated with simulations and future work include experimental tests in outdoor environement. ispartof: pages:19-24 ispartof: Proceedings of the 4th International Workshop on Research, Education and Development on Unmanned Aerial Systems pages:19-24 ispartof: International Workshop on Research, Education and Development on Unmanned Aerial Systems location:Linköping, Sweden date:3 Oct - 5 Oct 2017 status: published

Published
2017

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