Decentralized discrete adaptive sliding mode control for interconnected nonlinear systems

This article presents a study on controlling a class of large-scale systems composed of interconnected subsystems. The systems are represented by discrete block-oriented models with unknown parameters. This article proposes a novel adaptive sliding mode control strategy to address the tracking control problem and minimize the impact of interconnection. This approach leverages the robustness of sliding mode control against unmodeled dynamics and disturbances with the advantages of adaptive control. To adapt the system's parameters, a recursive parametric estimation algorithm using least-squares techniques is employed. The proposed method offers benefits such as robustness against parameter uncertainties, handling of nonlinearities, improved tracking accuracy, and reduced chattering phenomena. The effectiveness of the method is demonstrated through the evaluation of two simulation examples.

Automated summary

This article presents a study on controlling a class of large-scale systems composed of interconnected subsystems. It proposes a novel adaptive sliding mode control strategy to address the tracking control problem and demonstrates its effectiveness through the evaluation of two simulation examples. The proposed method offers benefits such as robustness against parameter uncertainties, handling of nonlinearities, improved tracking accuracy, and reduced chattering phenomena.