Original Research Article

Article volume = 2025 and issue = 1

Pages: 50–59

Article publication Date: August 05, 2026

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A Data-Driven Framework for State-Feedback Control via Mapping in an LMI Structure to Satisfy the Generalized Lyapunov Condition

Hossein valikelari *, Ahmadreza vali *, Abdorreza Kashaninia

Faculty of Electrical & Computer Engineering, Malek-Ashtar University of Technology, Tehran, Iran.

Abstract:

This paper proposes a novel data-driven robust control framework for uncertain nonlinear systems, integrating system identification, spectral analysis, and sliding mode control (SMC). Initially, the dynamic model is extracted directly from input-output data using the Dynamic Mode Decomposition with Control (DMDc) algorithm. To ensure model fidelity, the identified structure is rigorously evaluated via spectral analysis, focusing on eigenvalues and singular values to isolate dominant modes and effective dynamic components. The control gains are derived by solving an optimization problem governed by a cost function and the discrete Riccati equation, which serves as the foundation for the SMC law design. Furthermore, operational constraints concerning the magnitude of control effort and the rate of change of the control signal are explicitly incorporated into the design process to ensure robust and reliable performance.

Keywords:

Data-Driven Control, Dynamic Mode Decomposition with Control (DMDc), Sliding Mode Control, Discrete Riccati Equation.

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Cite this article as:
  • Hossein valikelari *, Ahmadreza vali *, Abdorreza Kashaninia, A Data-Driven Framework for State-Feedback Control via Mapping in an LMI Structure to Satisfy the Generalized Lyapunov Condition, Communications in Combinatorics, Cryptography & Computer Science, 2025(1), PP.50–59, 2026
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