Work

Design of Neural Networks Based Sliding Mode Control and Observation: An Overview

Year: 2024

Type: conference-paper

Abstract: This paper presents an overview of some sliding mode control and observation schemes based on the joint use of neural networks (NNs) and the so-called integral sliding mode (ISM) algorithm. More precisely, the utilization of a NN-based approach is aimed at estimating the unknown dynamics of the process, thus providing a model for the design of the ISM strategy. Both the ISM controller and observer syntheses are discussed in this work. Moreover, assuming the presence of state and input constraints, a recent version of a control scheme based on model predictive control (MPC) and NN-based ISM is presented. The convergence performance of the proposed approaches are illustrated and assessed in simulation.

Source: International Workshop on Variable Structure Systems

DOI: 10.1109/vss61690.2024.10753372

Authors: Antonella Ferrara, Gian Paolo Incremona, Edoardo Vacchini, Nikolas Sacchi

Institutions: University of Pavia, Politecnico di Milano

Language: English

Topic: Adaptive Control of Nonlinear Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4404564706

FWCI: 0.722

Cites:

Cited by: 1

Related to: 10