Litcius/Paper detail

A Robust Sliding-Mode Based Data-Driven Model-Free Adaptive Controller

M.L. Corradini

2021IEEE Control Systems Letters36 citationsDOI

Abstract

In this letter, a novel data-driven control algorithm is presented coupling Model-Free Adaptive Control and Sliding Mode Control, which addresses general discrete-time Single-Input Single-Output nonlinear nonaffine systems and is aimed at strengthening standard techniques in the presence of a class of output-dependent perturbations. Use is made of an equivalent dynamic linearization model obtained adopting a dynamic linearization technique based on pseudo-partial derivatives. A stability proof of convergence of the closed loop system is provided, showing that the closed-loop tracking error is an asymptotically vanishing sequence and ensuring boundedness of the I/O sequences. Validation of the technique has been performed using a discrete-time test plant taken from the literature in the presence of perturbations. Simulation results show a remarkable improvement in terms of control authority and of tracking accuracy with respect to recently published analogous approaches.

Topics & Concepts

Control theory (sociology)LinearizationConvergence (economics)Controller (irrigation)Nonlinear systemTracking errorComputer scienceSliding mode controlStability (learning theory)Adaptive controlStability theorySequence (biology)Reference modelFeedback linearizationDiscrete time and continuous timeTrajectoryMathematicsControl (management)Machine learningBiologyStatisticsGeneticsAstronomyEconomic growthQuantum mechanicsSoftware engineeringAgronomyPhysicsArtificial intelligenceEconomicsIterative Learning Control SystemsAdvanced Control Systems OptimizationControl Systems and Identification