Showing papers by "Cédric Join published in 2020"

Model-free control algorithms for micro air vehicles with transitioning flight capabilities

Abstract: Micro air vehicles with transitioning flight capabilities, or simply hybrid micro air vehicles, combine the beneficial features of fixed-wing configurations, in terms of endurance, with vertical ta...

Model-Free Control as a Service in the Industrial Internet of Things: Packet loss and latency issues via preliminary experiments

Abstract: Model-Free Control (MFC), which is easy to implement both from software and hardware viewpoints, permits the introduction of a high level control synthesis for the Industrial Internet of Things (IIoT) and the Industry 4.0. The choice of the User Diagram Protocol (UDP) as the Internet Protocol permits to neglect the latency. In spite of most severe packet losses, convincing computer simulations and laboratory experiments show that MFC exhibits a good Quality of Service (QoS) and behaves better than a classic PI regulator.

Machine learning and control engineering: The model-free case

Abstract: This paper states that Model-Free Control (MFC), which must not be confused with Model-Free Reinforcement Learning, is a new tool for Machine Learning (ML). MFC is easy to implement and should be substituted in control engineering to ML via Artificial Neural Networks and/or Reinforcement Learning. A laboratory experiment, which was already investigated via today’s ML techniques, is reported in order to confirm this viewpoint.

Towards a unified model-free control architecture for tailsitter micro air vehicles: Flight simulation analysis and experimental flights

Abstract: Hybrid Micro Air Vehicles (MAVs) combine the beneficial features of rotorcraft with fixed-wing configurations providing a complete flight envelope that includes vertical take-off, hover, transitioning flights, forward flight and vertical landing. Tailsitter MAVs belong to a particular class of hybrid MAVs and its peculiar issue is related to the transitioning flight phase where, for high incidence angles, fast changing of aerodynamic forces and moments are observed which are difficult to model and control accurately. To overcome this issue, we proposed a control architecture with model-free control (MFC) algorithms that has been able to stabilize the hybrid MAV's attitude, velocity, and position without any modeling process. The proposed control architecture consisted basically two steps~: 1) The attitude control, to ensure the hybrid MAV's attitude tracking and stability within the entire flight envelope; 2) The guidance system responsible to control both velocity and position. We validated the MFC architecture according to a comprehensive set of flight simulations and experimental flight tests. Experimental flight tests shown an effective and promising control strategy solving the principal issue of hybrid MAVs that was the formulation of accurate hybrid MAV's dynamic equations to design control laws. The obtained results have provided a straightforward way to validate the methodological principles presented in this article as well as to certify the designed MFC parameters, and to establish a conclusion regarding MFC benefits in both theoretical and practical contexts.

First steps toward a simple but efficient model-free control synthesis for variable-speed wind turbines

Abstract: Although variable-speed three-blade wind turbines are nowadays quite popular, their control remains a challenging task. We propose a new easily implementable model-free control approach with the corresponding intelligent controllers. Several convincing computer simulations, including some fault accommodations, shows that model-free controllers are more efficient and robust than classic proportional-integral controllers. See, also, the YouTube video: https://youtu.be/9uEb-RUGwKI

Model-free control for machine tools

Abstract: Cascade P-PI control systems are the most widespread commercial solutions for machine tool positioning systems. However, friction, backlash and wearing effects significantly degrade their closed-loop behaviour. This works proposes a novel easy-to-tune control approach that achieves high accuracy trajectory tracking in a wide operation domain, thus being able to mitigate wear and aging effects.

A robust but easily implementable remote control for quadrotors: Experimental acrobatic flight tests

Abstract: Experimental flight tests are reported about quadrotors UAVs via a recent model-free control (MFC) strategy, which is easily implementable. We show that it is possible to achieve acrobatic rate control of the UAV, which is beyond the previous standard. The same remote controller is tested on two physical vehicles without any re-tuning. It produces in both cases low tracking error. We show that MFC is robust even when the quadrotor is highly damaged. A video footage can be found at: this https URL

Comments on ‘Differentiator application in altitude control for an indoor blimp robot’

Abstract: Comparison of several types of differentiation algorithms has been performed in the paper Wang, Zheng, Efimov, and Perruquetti (2018) with application to a robotic blimp altitude control Unfortunately, one of the differentiation methods, the algebraic differentiator, has not been applied properly The clarifications and the new comparison results are given in this note

Data mining and time series segmentation via extrema: preliminary investigations.

Abstract: Time series segmentation is one of the many data mining tools. This paper, in French, takes local extrema as perceptually interesting points (PIPs). The blurring of those PIPs by the quick fluctuations around any time series is treated via an additive decomposition theorem, due to Cartier and Perrin, and algebraic estimation techniques, which are already useful in automatic control and signal processing. Our approach is validated by several computer illustrations. They underline the importance of the choice of a threshold for the extrema detection.

A robust but easily implementable remote control for quadrotors: Experimental acrobatic flight tests.

Abstract: Experimental flight tests are reported about quadrotors UAVs via a recent model-free control (MFC) strategy , which is easily implementable. We show that it is possible to achieve acrobatic rate control of the UAV, which is beyond the previous standard. The same remote controller is tested on two physical vehicles without any re-tuning. It produces in both cases low tracking error. We show that MFC is robust even when the quadrotor is highly damaged. A video footage can be found at: https://youtu.be/wtSLalA4szc

Model-free control for machine tools

Abstract: Cascade P-PI control systems are the most widespread commercial solutions for machine tool positioning systems. However, friction, backlash and wearing effects significantly degrade their closed-loop behaviour. This works proposes a novel easy-to-tune control approach that achieves high accuracy trajectory tracking in a wide operation domain, thus being able to mitigate wear and aging effects.

An intelligent Proportional controller of a Seeded Batch Crystallizer

Abstract: Crystallization process is used in a very wide range of industrial applications. However, highly nonlinear comportment of such process and the difficulties of characterizing several phenomenological effects makes difficult to find suitable operational procedures for producing required products. In this article, we use a model-free control (MFC) for controlling the mean size of crystals produced by seeded batch cooling crystallization. The MFC method is distinguished notably in terms of the modeling strategy. Rather than developing a crystallization model within the classic population balance equation (PBE) together with the mass balance and the energy balance, as is usually done, we use a local approximation model. The model is continuously updated using the unique knowledge of the input-output behavior to handle both unknown dynamics and any possible disturbances. The MFC is only based on intelligent Proportional (iP) control. Simulation results prove the iP controller's efficiency even with noisy measurements, disturbances, and parameter variations.