Experimental investigation on the use of a discrete-time MCS adaptive strategy for the control of a strongly nonlinear automotive electromechanical system

In this report we test experimentally a novel adaptive control strategy for discrete time systems on a strongly nonlinear electromechanical automotive system like the Electronic Throttle Body (ETB). The control strategy is known as Discrete time Minimal Control Synthesis (DMCS) algorithm and requires a minimal knowledge of the plant dynamics, hence it is particulary useful for automotive devices that are actually controlled via digital control strategies affectively implemented in modern Electronic Control Units (ECUs) for engines. After a proper simplification of the plant dynamics and discretization of the model, this fundamental automotive device is described via a discrete time system that match the hypothesis of the DMCS, indeed the control canonical form required as assumption to show asymptotic convergence of the tracking error is fulfilled. A wide experimental investigation show that tracking performance are comparable to those obtained previously by discretizing the classical continuous time MCS with more complex discretization methods.