Controlling a drone: Comparison between a based model method and a fuzzy inference system

International audienceThe work describes an automatically on-line self-tunable fuzzy inference system (STFIS) of a new configuration of mini-flying called XSF (X4 Stationnary Flyer) drone. A fuzzy controller based on on-line optimization of a zero order Takagi-Sugeno fuzzy inference system (FIS) by a back propagation-like algorithm is successfully applied. It is used to minimize a cost function that is made up of a quadratic error term and a weight decay term that prevents an excessive growth of parameters. Thus, we carried out control for the continuation of simple trajectories such as the follow-up of straight lines, and complex (half circle, corner, and helicoidal) by using the STFIS technique. This permits to prove the effectiveness of the proposed control law. Simulation results and a comparison with a static feedback linearization controller (SFL) are presented and discussed. We studied the robustness of the two controllers used in the presence of disturbances. We presented two types of disturbances, the case of a breakdown of an engine as well as a gust of wind

Intelligent control for a drone by self-tunable fuzzy inference system

International audienceThe work describes an automatically on-line Self-Tunable Fuzzy Inference System (STFIS) of a new configuration of mini-flying called XSF (X4 Stationnary Flyer) drone. A Fuzzy controller based on on-line optimization of a zero order Takagi-Sugeno fuzzy inference system (FIS) by a back propagation-like algorithm is successfully applied. It is used to minimize a cost function that is made up of a quadratic error term and a weight decay term that prevents an excessive growth of parameters. Thus, we carried out control for the continuation of simple trajectories such as the follow-up of straight lines, and complex (half circle, corner) by using the STFIS technique. This permits to prove the effectiveness of the proposed control law. We studied the robustness of the two controllers used in the presence of disturbances. We presented two types of disturbances, the case of a gust of wind and taking into account white noise disturbances. A comparison between the Self-Tunable Fuzzy Inference System (STFIS) and Adaptive Network based Fuzzy Inference System (ANFIS) is given

Commande d un système sous-actionné: application à un drone à quatre hélices

Le drone XSF (X4 Stationary Flyer) est un engin volant de faible dimension capable d emporter une petite charge utile, notamment une caméra, destiné à effectuer de manière autonome une mission de reconnaissance. Les travaux que nous avons effectués portent sur l'étude de stabilisation avec planification de trajectoire de deux modèles du drone. Le premier est appelé modèle X4 conventionnel, le second est le modèle X4 bidirectionnel (XSF). La particularité du modèle X4 bidirectionnel par rapport au modèle existant est le pivotement des supports qui portent les moteurs 1 et 3. Nous avons cherché à comparer des algorithmes de commande en utilisant une technique nécessitant un modèle du système (technique du Backstepping et la commande par retour d'état statique) et une approche experte s'affranchissant du modèle (Système Inférence Floue Optimisé SIFO). Nous avons ainsi réalisé des commandes pour la poursuite de trajectoires simples telles que le suivi de lignes droites, et complexes (demi cercle, coin, ....) en utilisant les deux techniques. Nous avons étudié la robustesse des deux contrôleurs utilisés en présence de perturbations. Nous avons présenté deux types de perturbations, le cas d'une panne d'un moteur ainsi qu'une rafale de vent.Drone XSF (X4 Stationary Flyer) is a flying machine of low dimension able to carry a small payload, in particular a camera, intended to carry out in an autonomous way a recognition mission. The work which we carried out concerns the study of stabilization with planning of trajectory of two models of the drone. First model is called X4 conventional; the second is the model X4 bidirectional (XSF). The characteristic of the model X4 bidirectional compared to the existing model is the swivelling of the supports which carry engines 1 and 3. We sought to compare control algorithms by using a technique requiring a model of the system (technical of Backstepping and the Static Feedback Linearization controller SFL) and an expert approach freeing itself from the model (Optimized Fuzzy Inference System OFIS). We thus carried out control for the continuation of simple trajectories such as the follow-up of straight lines, and complex (half circle, corner ) by using the two techniques. We studied the robustness of the two controllers used in the presence of disturbances. We presented two types of disturbances, the case of a breakdown of an engine as well as a gust of wind.EVRY-BU (912282101) / SudocSudocFranceF

Optimisation en ligne d'une base de règles floues : suivi de trajectoire d'un drone à quatre hélices

National audienc

Aircraft Control System Using LQG and LQR Controller with Optimal Estimation-Kalman Filter Design

AbstractThis paper, describes a LQG and LQR robust controller for the lateral and longitudinal flight dynamics of an aircraft control system. The controller is used in order to achieve robust stability and good dynamic performance against the variation of aircraft parameters. The application of the proposed LQG and LQR robust control scheme is implemented through the simulation. The proposed robust controller for aircraft stability is designed using Matlab/Simulink program. Simulation results confirm the performance of the proposed controller for aircraft control system. Since the time of its introduction, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation. For example, to determine the velocity of an aircraft or sideslip angle, one could use a Doppler radar, the velocity indications of an inertial navigation system, or the relative wind information in the air data system. Rather than ignore any of these outputs, a Kalman filter could be built to combine all of this data and knowledge of the various systems dynamics to generate an overall best estimate of pitch, roll and sideslip angle

Two Inertial Models of X4-Flyers Dynamics, Motion Planning and Control

International audienceTwo models of mini-flying robots with four rotors, called X4-flyer, presenting and studying the stabilization/tracking with and without motion planning are proposed in this paper. So the first model is called bidirectional X4-flyer and the second one is called conventional X4-flyer. The impact of the planning of the trajectory for the control of the engines, consequently economy in energy, is shown. The stabilizing (tracking) feedback control used with and without motion planning is based on receding horizon point to point steering. The developed control algorithm of the X4-flyer is based on the Lyapunov method and is obtained using the backstepping techniques. This enabled to stabilize the engine in hovering and to generate its trajectory. All the forces developed by the two models are studied and simulated. Finally, results of simulations are given for the two models

Self-Tunable Fuzzy Inference System: A comparative study for a drone

International audienceThe work describes an automatically on-line Self-Tunable Fuzzy Inference System (STFIS) of a mini-flying called XSF drone. A Fuzzy controller based on an on-line optimization of a zero order Takagi-Sugeno fuzzy inference system (FIS) by a back propagation-like algorithm is successfully applied. It is used to minimize a cost function that is made up of a quadratic error term and a weight decay term that prevents an excessive growth of parameters. Simulation results and a comparison with a Static Feedback Linearization controller (SFL) are presented and discussed. A path-like flying road, described as straight-lines with rounded corners permits to prove the effectiveness of the proposed control law

Motion Planning and Stabilisation of a X4 Bidirectional Rotors using a Neuro-Fuzzy Controller

International audienc

Control of a Drone: Study and Analysis of the Robustness

International audienceThe work describes an automatically on-line Self-Tunnable Fuzzy Interference Systems (STFIS) of a new configuration of mini-flying called XSF (X4 Stationary Flyer) drone. A Fuzzy controller based on-line optimization of a zero order Takagi-Sugeno fuzzy interference system (FIS) by a back propagation like algorithm is successfully applied. It is used to minimize a cost function that is made up of a quadratic error term and a weight decay term that prevents an excessive growth of parameters. Thus, we carried out control for helical trajectories by using the STFIS technique. This permits to prove the effectiveness of the proposed control law. Simulation results and a comparison with a Static Feedback Linearization controller (SFL) are presented and discussed. We studied the robustness of the two used controllers in the presence of disturbances. We presented the case of an engine breakdown as well as a gust of wind and taking into account white noise disturbances

Control of an under-actuated system: Application to a four rotors rotorcraft

International audienceThis paper presents the study of stabilization with motion planning of a four rotors mini-flying machine (robot with four rotors rotorcraft). A particular design of this structure where two rotors are directional (X4 bidirectional rotors) is also presented. The dynamic of this last system involves five control inputs which are computed to stabilize the engine with predefined trajectories. Our aim is to obtain control algorithms using the backstepping approach in order to stabilize the engine in hovering and to generate its trajectory