Modelling, simulation and real-time control of a laboratory tide generation system

Abstract Small-scale experiments allow to reproduce and understand phenomena and to draw inferences about large-scale processes. In this paper, we consider a peculiar experimental apparatus which is aimed at reproducing a typical lagoonal environment subject to tidal forcings. This apparatus is useful for performing morphometric analyses of synthetic tidal networks. The quality of these kind of experiments strongly depends on the behaviour of the artificial tide that has to exhibit predefined characteristics. To this aim, the height of the artificial water wave is controlled in real-time. The experimental apparatus has an intrinsic complexity and it represents an example of a multi-domain physical system. In order to design and to assess suitable control strategies, we have developed a Matlab-based simulation environment which is able to reproduce the behaviour of the artificial tide generation system. The dynamic model is calibrated and validated by using real experimental data and it can be seen as an extremely useful tool in the decision making process of the real control system development. In particular, we have designed, tuned, and tested a model-free control algorithm, that is the intelligent-PI (i-PI). Finally, the proposed controller has been implemented on a real-time hardware and then its performance has been compared with that of a standard regulator for different type of experiments.

[1]  Martin Horn,et al.  Model-free control of a thermal plant , 2009, 2009 IEEE International Conference on Control and Automation.

[2]  Lennart Ljung,et al.  Modeling Of Dynamic Systems , 1994 .

[3]  Avrie Levent,et al.  Robust exact differentiation via sliding mode technique , 1998, Autom..

[4]  Arie Levant,et al.  Principles of 2-sliding mode design , 2007, Autom..

[5]  Cédric Join,et al.  Model-free control , 2013, Int. J. Control.

[6]  Andrea Cervato,et al.  Remote refrigeration system experiments for control engineering education , 2017, Comput. Appl. Eng. Educ..

[7]  Tore Hägglund,et al.  Advanced PID Control , 2005 .

[8]  Michel Fliess,et al.  Model-Free Based Water Level Control for Hydroelectric Power Plants , 2010 .

[9]  J. G. Ziegler,et al.  Optimum Settings for Automatic Controllers , 1942, Journal of Fluids Engineering.

[10]  Mirco Rampazzo,et al.  Modelling and simulation of a convective low temperature sludge dryer with multilayer belt , 2017, 2017 IEEE 3rd International Forum on Research and Technologies for Society and Industry (RTSI).

[11]  Jean-François Balmat,et al.  A model-free control strategy for an experimental greenhouse with an application to fault accommodation , 2014, Comput. Electron. Agric..

[12]  Arie Levant,et al.  Higher-order sliding modes, differentiation and output-feedback control , 2003 .

[13]  Ramin S. Esfandiari,et al.  Modeling and Analysis of Dynamic Systems , 2010 .

[14]  N. Tambroni,et al.  Can tide dominance be inferred from the point bar pattern of tidal meandering channels? , 2017 .

[15]  Giovanni Coco,et al.  Morphodynamics of tidal networks: advances and challenges , 2013 .

[16]  Alessandro Beghi,et al.  A multi-phase genetic algorithm for the efficient management of multi-chiller systems , 2009, 2009 7th Asian Control Conference.

[17]  Antonio Visioli,et al.  Practical PID Control , 2006 .

[18]  Cheng Siong Chin.  Computer-Aided Control Systems Design: Practical Applications Using MATLAB® and Simulink® , 2012 .

[19]  Cédric Join,et al.  Model-free control and intelligent PID controllers: towards a possible trivialization of nonlinear control? , 2009, ArXiv.

[20]  Aidan O'Dwyer,et al.  Handbook of PI and PID controller tuning rules , 2003 .

[21]  Michel Fliess,et al.  A mathematical explanation via “intelligent” PID controllers of the strange ubiquity of PIDs , 2010, 18th Mediterranean Conference on Control and Automation, MED'10.

[22]  Cédric Join,et al.  Stability margins and model-free control: A first look , 2014, 2014 European Control Conference (ECC).

[23]  Richard M. Murray,et al.  Feedback Systems An Introduction for Scientists and Engineers , 2007 .

[24]  Cédric Join,et al.  Toward a model-free feedback control synthesis for treating acute inflammation , 2018, bioRxiv.

[25]  Luca Carniello,et al.  Experimental analysis of tidal network growth and development , 2010 .

[26]  Viktor Perelmuter.  Electrotechnical Systems : Simulation with Simulink® and SimPowerSystems™ , 2019 .

[27]  Sigurd Skogestad,et al.  Probably the best simple PID tuning rules in the world , 2001 .