Minimum Operator-Based Data-Driven Control

This article introduces two novel data-driven discrete sliding mode control strategies for nonlinear discrete-time systems subjected to disturbances. The proposed method simplifies implementation by utilizing a compact form dynamic linearization (CFDL) data-driven technique that relies on system input and output (I&O) data. By incorporating minimum operator-based discrete sliding mode control (MDSMC) with CFDL, this article presents the CFDL-MDSMC approach. This new method enhances tracking accuracy and disturbance rejection compared to the previous work. Theoretical analysis rigorously establishes the stability of the proposed approach, ensuring that the system remains robust under various conditions. This analysis is complemented by numerical simulations, which thoroughly examine the method’s performance across different scenarios. Additionally, experimental validation on a two-tank water level control system showcases the practical effectiveness of the approach, illustrating its ability to maintain optimal performance in real-world applications.