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ALINEA, which was introduced almost 30 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. [ABSTRACT FROM AUTHOR]

‘Model-free control’and the corresponding ‘intelligent’ PID controllers (iPIDs), which already had many successful concrete applications, are presented here for the first time in an unified manner, where the new advances are taken into account. The basics of model-free control is now employing some old functional analysis and some elementary differential algebra. The estimation techniques become quite straightforward via a recent online parameter identification approach. The importance of iPIs and especially of iPs is deduced from the presence of friction. The strange industrial ubiquity of classic PIDs and the great difficulty for tuning them in complex situations is deduced, via an elementary sampling, from their connections with iPIDs. Several numerical simulations are presented which include some infinite-dimensional systems. They demonstrate not only the power of our intelligent controllers but also the great simplicity for tuning them. [ABSTRACT FROM AUTHOR]

We are generating residuals for linear fault diagnosis and isolation which are robust with respect to a large variety of additive disturbances, working in closed-loop, even with uncertain parameters. Several examples with their computer simulations, including a concrete case-study of a two mass system, are enlightening our viewpoint. Our methods, which are mainly of algebraic flavour (module theory, differential algebra, and operational calculus), are borrowed from recent works on control and identification. [ABSTRACT FROM AUTHOR]

We investigate an extension of predictive control, PID controllers, and Smith predictors to some classes of linear delay systems which are most encountered in practice. The predictive part is provided by extending flatness-based predictive control. Generalized PI regulators lead to a 'PID and Smith predictor'-like scheme which permits us to easily handle (deadtime-dominant) unstable systems. Numerous examples with thorough simulations demonstrate the performance of the proposed control strategy. [ABSTRACT FROM AUTHOR]

A general flatness-based framework for linear continuous-time predictive control is presented. The mathematical setting, which is valid for multivariable systems, is provided by the algebraic theory of modules where a controllable system corresponds to a finitely generated free module over a principal ideal ring. Any basis of this free module is a flat output which yields an easy calculation of the predicted trajectory. This formalism permits one to handle non-minimum phase systems, system constraints, and to deal with additive perturbations. Three concrete case studies, namely a dc motor, a flexible system, and a cement mill, are analysed and simulations are given. These examples are written in such a way that any reader who is not familiar with module theory may nevertheless grasp the proposed control strategy. [ABSTRACT FROM AUTHOR]