4,052 research outputs found
A model-free control strategy for an experimental greenhouse with an application to fault accommodation
Writing down mathematical models of agricultural greenhouses and regulating
them via advanced controllers are challenging tasks since strong perturbations,
like meteorological variations, have to be taken into account. This is why we
are developing here a new model-free control approach and the corresponding
intelligent controllers, where the need of a good model disappears. This
setting, which has been introduced quite recently and is easy to implement, is
already successful in many engineering domains. Tests on a concrete greenhouse
and comparisons with Boolean controllers are reported. They not only
demonstrate an excellent climate control, where the reference may be modified
in a straightforward way, but also an efficient fault accommodation with
respect to the actuators
Model-free control and fault accommodation for an experimental greenhouse
International audienceThe greenhouse climate control is important in modern agriculture. It is also rather difficult to design: as a matter of fact writing down a "good" mathematical model, which takes into account strong meteorological disturbances, might be an impossible task. The control is here synthesized via a new "model-free" setting, which yields an "intelligent" proportional feedback controller, the tuning of which is straightforward, and even simpler than the intelligent proportional-integral controller, which was already utilized in a previous publication. Our control strategy is successfully tested via an experimental greenhouse. The comparison with the classic Boolean approach, which is popular among manufacturers, demonstrates the superiority of our viewpoint, which permits moreover an efficient actuator fault accommodation. It might be the first model-free fault-tolerant control, which works satisfactorily in practice
Model-based versus model-free control designs for improving microalgae growth in a closed photobioreactor: Some preliminary comparisons
Controlling microalgae cultivation, i.e., a crucial industrial topic today,
is a challenging task since the corresponding modeling is complex, highly
uncertain and time-varying. A model-free control setting is therefore
introduced in order to ensure a high growth of microalgae in a continuous
closed photobioreactor. Computer simulations are displayed in order to compare
this design to an input-output feedback linearizing control strategy, which is
widely used in the academic literature on photobioreactors. They assess the
superiority of the model-free standpoint both in terms of performances and
implementation simplicity.Comment: The 24th Mediterranean Conference on Control and Automation (MED'16),
Athens, Greece (June 21-24, 2016
Some remarks on wheeled autonomous vehicles and the evolution of their control design
Recent investigations on the longitudinal and lateral control of wheeled
autonomous vehicles are reported. Flatness-based techniques are first
introduced via a simplified model. It depends on some physical parameters, like
cornering stiffness coefficients of the tires, friction coefficient of the
road, ..., which are notoriously difficult to identify. Then a model-free
control strategy, which exploits the flat outputs, is proposed. Those outputs
also depend on physical parameters which are poorly known, i.e., the vehicle
mass and inertia and the position of the center of gravity. A totally
model-free control law is therefore adopted. It employs natural output
variables, namely the longitudinal velocity and the lateral deviation of the
vehicle. This last method, which is easily understandable and implementable,
ensures a robust trajectory tracking problem in both longitudinal and lateral
dynamics. Several convincing computer simulations are displayed.Comment: 9th IFAC Symposium on Intelligent Autonomous Vehicles (Leipzig,
Germany, 29.06.2016 - 01.07.2016
A new model-free design for vehicle control and its validation through an advanced simulation platform
A new model-free setting and the corresponding "intelligent" P and PD
controllers are employed for the longitudinal and lateral motions of a vehicle.
This new approach has been developed and used in order to ensure simultaneously
a best profile tracking for the longitudinal and lateral behaviors. The
longitudinal speed and the derivative of the lateral deviation, on one hand,
the driving/braking torque and the steering angle, on the other hand, are
respectively the output and the input variables. Let us emphasize that a "good"
mathematical modeling, which is quite difficult, if not impossible to obtain,
is not needed for such a design. An important part of this publication is
focused on the presentation of simulation results with actual and virtual data.
The actual data, used in Matlab as reference trajectories, have been obtained
from a properly instrumented car (Peugeot 406). Other virtual sets of data have
been generated through the interconnected platform SiVIC/RTMaps. It is a
dedicated virtual simulation platform for prototyping and validation of
advanced driving assistance systems. Keywords- Longitudinal and lateral vehicle
control, model-free control, intelligent P controller (i-P controller),
algebraic estimation, ADAS (Advanced Driving Assistance Systems).Comment: in 14th European Control Conference, Jul 2015, Linz, Austria. 201
Model predictive control for microgrid functionalities: review and future challenges
ABSTRACT: Renewable generation and energy storage systems are technologies which evoke the future energy paradigm. While these technologies have reached their technological maturity, the way they are integrated and operated in the future smart grids still presents several challenges. Microgrids appear as a key technology to pave the path towards the integration and optimized operation in smart grids. However, the optimization of microgrids considered as a set of subsystems introduces a high degree of complexity in the associated control problem. Model Predictive Control (MPC) is a control methodology which has been satisfactorily applied to solve complex control problems in the industry and also currently it is widely researched and adopted in the research community. This paper reviews the application of MPC to microgrids from the point of view of their main functionalities, describing the design methodology and the main current advances. Finally, challenges and future perspectives of MPC and its applications in microgrids are described and summarized.info:eu-repo/semantics/publishedVersio
Green Technologies for Production Processes
This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies
On ramp metering: Towards a better understanding of ALINEA via model-free control
International audienceALINEA, which was introduced almost thirty years ago, remains certainly the most well known feedback loop for ramp metering control. A theoretical proof of its efficiency at least when the traffic conditions are rather mild is given here, perhaps for the first time. It relies on tools stemming from the new model-free control and the corresponding "intelligent" proportional controllers. Several computer experiments confirm our theoretical investigations
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