Data-driven optimal model-free control of twin rotor aerodynamic systems

2015 ◽  
Author(s):  
Raul-Cristian Roman ◽  
Mircea-Bogdan Radac ◽  
Radu-Emil Precup ◽  
Emil M. Petriu
Keyword(s):  
Data Driven ◽  
Optimal Model ◽  
Model Free ◽  
Model Free Control ◽  
Twin Rotor

Data-Driven Model-Free Sliding Mode and Fuzzy Control with Experimental Validation

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Radu-Emil Precup ◽  
Raul-Cristian Roman ◽  
Elena-Lorena Hedrea ◽  
Emil M. Petriu ◽  
Claudia-Adina Bojan-Dragos
Keyword(s):  
Fuzzy Control ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Data Driven ◽  
Control Algorithms ◽  
Control Law ◽  
Control Structures ◽  
Mode Control ◽  
Model Free ◽  
Model Free Control

The paper presents the combination of the model-free control technique with two popular nonlinear control techniques, sliding mode control and fuzzy control. Two data-driven model-free sliding mode control structures and one data-driven model-free fuzzy control structure are given. The data-driven model-free sliding mode control structures are built upon a model-free intelligent Proportional-Integral (iPI) control system structure, where an augmented control signal is inserted in the iPI control law to deal with the error dynamics in terms of sliding mode control. The data-driven model-free fuzzy control structure is developed by fuzzifying the PI component of the continuous-time iPI control law. The design approaches of the data-driven model-free control algorithms are offered. The data-driven model-free control algorithms are validated as controllers by real-time experiments conducted on 3D crane system laboratory equipment.

Optimal model-free fuzzy logic control for autonomous unmanned aerial vehicle

2021 ◽  
pp. 095441002110253
Author(s):  
Hossam E Glida ◽  
Latifa Abdou ◽  
Abdelghani Chelihi ◽  
Chouki Sentouh ◽  
Gabriele Perozzi
Keyword(s):  
Fuzzy Logic ◽  
Unmanned Aerial Vehicle ◽  
Fuzzy Logic Control ◽  
Estimation Error ◽  
Design Parameters ◽  
Multiple Model ◽  
Optimal Model ◽  
Model Free ◽  
Logic Control ◽  
Aerial Vehicle

This article deals with the issue of designing a flight tracking controller for an unmanned aerial vehicle type of quadrotor based on an optimal model-free fuzzy logic control approach. The main design objective is to perform an automatic flight trajectory tracking under multiple model uncertainties related to the knowledge of the nonlinear dynamics of the system. The optimal control is also addressed taking into consideration unknown external disturbances. To achieve this goal, we propose a new optimal model-free fuzzy logic–based decentralized control strategy where the influence of the interconnection term between the subsystems is minimized. A model-free controller is firstly designed to achieve the convergence of the tracking error. For this purpose, an adaptive estimator is proposed to ensure the approximation of the nonlinear dynamic functions of the quadrotor. The fuzzy logic compensator is then introduced to deal with the estimation error. Moreover, the optimization problem to select the optimal design parameters of the proposed controller is solved using the bat algorithm. Finally, a numerical validation based on the Parrot drone platform is conducted to demonstrate the effectiveness of the proposed control method with various flying scenarios.

scholarly journals Author Correction: Reliance on model-based and model-free control in obesity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lieneke K. Janssen ◽  
Florian P. Mahner ◽  
Florian Schlagenhauf ◽  
Lorenz Deserno ◽  
Annette Horstmann
Keyword(s):  
Model Based ◽  
Model Free ◽  
Model Free Control

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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