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Learning-based Nonlinear Model Predictive Control Using Deterministic Actor-Critic with Gradient Q-learning Critic
2024 18th International Conference on Control, Automation, Robotics and Vision (ICARCV)
Year: 2024 | Conference Paper |
In this paper, we present an off-policy reinforcement learning (RL) method used to tune the optimal weights of a nonlinear model predictive control (NMPC) scheme. The objective is to find the optimal policy minimizing the closed-loop performance of point stabilization with obstacle avoidance control task. The parameterized NMPC scheme serves to approximate the optimal policy and update the paramet...Show More
Nonlinear Cascade Fuzzy Control of a Water Droplet Generator in an Subsonic Icing Wind Tunnel
César Hernández-Hernández;Thomas Chevet;Rihab El Houda Thabet;Vincent Sircoulomb;Nicolas Langlois
2024 24th International Conference on Control, Automation and Systems (ICCAS)
Year: 2024 | Conference Paper |
Droplets generation in wind tunnels plays a crucial role in studying the factors contributing to ice formation on aircrafts. The liquid water content (LWC) and median volumetric diameter (MVD) are critical parameters influencing ice formation due to their impact on the rate of ice accumulation (frost, icing, or mixed), significantly affecting aircraft performance. Controlling these parameters is t...Show More
(Re)CreativeRobot: Popularizing Workshop to Promote Control and Mobile Robotics for Kids
Cristina Stoica;Sylvain Bertrand;Aarsh Thakker;Thomas Chevet;Julien Gombert;Yvan Ngnie-Tekou;Julia Godoy;Justine Bourgeois
2023 27th International Conference on System Theory, Control and Computing (ICSTCC)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
This paper focuses on the Workshop “(Re)Creative Mobile Robotics for Kids–(Re)CreativeRobot’’ for popularizing Control and Mobile Robotics for children. Inspired from the “Girls in Control’’ workshop, this education activity allows children to individually implement basic Control algorithms on mobile robots via Scratch programming. Its first occurrence was held during the French science festival “...Show More
Robust Iterative Learning Observers Based on a Combination of Stochastic Estimation Schemes and Ellipsoidal Calculus
Andreas Rauh;Thomas Chevet;Thach Ngoc Dinh;Julien Marzat;Tarek Raïssi
2022 25th International Conference on Information Fusion (FUSION)
Year: 2022 | Conference Paper |
Cited by: Papers (5)
The state estimation of repetitive processes with periodically repeated trajectories can be interpreted as the dual task of iterative learning control design. While the latter has been widely investigated over the last two decades, only few approaches exist for the design of iterative learning observers. However, the exploitation of the knowledge about periodically repeated trajectories, which occ...Show More
A Stochastic Design Approach for Iterative Learning Observers for the Estimation of Periodically Recurring Trajectories and Disturbances
Andreas Rauh;Thomas Chevet;Thach Ngoc Dinh;Julien Marzat;Tarek Raïssi
Many repetitive control problems are characterized by the fact that disturbances have the same effect in each successive execution of the same control task. Such disturbances comprise the lumped representation of unmodeled parts of the open-loop system dynamics, a systematic model-mismatch or, more generally, deterministic yet unknown uncertainty. In such cases, well-known strategies for iterative...Show More
Robust Interval Observer for Systems Described by the Fornasini–Marchesini Second Model
Thomas Chevet;Andreas Rauh;Thach Ngoc Dinh;Julien Marzat;Tarek Raïssi
This letter proposes a novel robust interval observer for a two-dimensional (treated as a synonym for a double-indexed system) linear time-invariant discrete-time system described by the Fornasini-Marchesini second model. This system is subject to unknown but bounded state disturbances and measurement noise. Built on recent interval estimation strategies designed for one-dimensional systems, the p...Show More
Zonotopic Kalman Filter-Based Interval Estimation for Discrete-Time Linear Systems With Unknown Inputs
Thomas Chevet;Thach Ngoc Dinh;Julien Marzat;Zhenhua Wang;Tarek Raïssi
This letter proposes an unknown input zonotopic Kalman filter-based interval observer for discrete-time linear time-invariant systems. In such contexts, a change of coordinates decoupling the state and the unknown inputs is often used. Here, the dynamics are rewritten into a discrete-time linear time-invariant descriptor system by augmenting the state vector with the unknown inputs. A zonotopic ou...Show More
Interval Estimation for Discrete-Time Linear Parameter-Varying System with Unknown Inputs
2021 60th IEEE Conference on Decision and Control (CDC)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
This paper proposes a new interval observer for joint estimation of the state and unknown inputs of a discrete-time linear parameter-varying (LPV) system with an unmeasurable parameter vector. This system is assumed to be subject to unknown inputs and unknown but bounded disturbances and measurement noise, while the parameter- varying matrices are elementwise bounded. Considering the unknown input...Show More
Guaranteed Voronoi-based Deployment for Multi-Agent Systems under Uncertain Measurements
Thomas Chevet;Cristina Stoica Maniu;Cristina Vlad;Youmin Zhang
In this paper, a decentralized robust tube-based model predictive control algorithm is used for two-dimensional Voronoi-based deployment of a multi-agent system in a bounded convex area, where the planar motion of each agent is subject to uncertain measurements. A bias bounded by a rectangle is thus considered for each agent's position measurement. The convex area of deployment is then partitioned...Show More
Voronoi-based UAVs Formation Deployment and Reconfiguration using MPC Techniques
Thomas Chevet;Cristina Stoica Maniu;Cristina Vlad;Youmin Zhang
2018 International Conference on Unmanned Aircraft Systems (ICUAS)
Year: 2018 | Conference Paper |
Cited by: Papers (9)
This paper presents a decentralized Voronoi-based linear model predictive control (MPC) technique for the deployment and reconfiguration of a multi-agent system composed of unmanned aerial vehicles (UAVs) in a bounded area. At each time instant, this area is partitioned into non-overlapping time-varying Voronoi cells associated to each UAV agent. The formation deployment objective is to drive the ...Show More
State estimation of an octorotor with unknown inputs. Application to radar imaging
Thomas Chevet;Maria Makarov;Cristina Stoica Maniu;Israel Hinostroza;Pierre Tarascon
2017 21st International Conference on System Theory, Control and Computing (ICSTCC)
Year: 2017 | Conference Paper |
Cited by: Papers (3)
This paper focuses on the design of a linear Kalman filter and an extended Kalman filter for the estimation of an octorotor unmanned aerial vehicle's (UAV) state in the context of Synthetic Aperture Radar image reconstruction. A comparison to a linear interpolation method is also proposed. The Kalman filters are developed based on a complete nonlinear model of the UAV and its linearized form. A pa...Show More
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