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    Area of Science:

    • Control Systems Engineering
    • Nonlinear System Analysis
    • Fuzzy Logic Control

    Background:

    • Designing controllers for large-scale nonlinear systems is complex.
    • Interconnected systems require robust control strategies for stability and adaptability.
    • Existing methods often necessitate complete redesigns when system components change.

    Purpose of the Study:

    • To develop a plug-and-play (PnP) distributed controller design method.
    • To enable seamless integration and removal of subsystems in large-scale nonlinear systems.
    • To ensure system stabilization without full controller redesign.

    Main Methods:

    • Utilizing multiple fuzzy summations and chordal decomposition of the system's interconnection graph.
    • Deriving sufficient stabilization conditions using linear matrix inequalities (LMIs).
    • Designing controllers that facilitate dynamic subsystem addition/removal.

    Main Results:

    • Sufficient conditions for distributed stabilization are established.
    • The proposed method allows for plug-and-play operations of subsystems.
    • Controllers do not require complete redesign when subsystems are added or removed.

    Conclusions:

    • The PnP approach offers a flexible and efficient method for controlling large-scale nonlinear systems.
    • This method is compatible with fault detection and isolation (FDI) systems and mixed control architectures.
    • Effectiveness demonstrated using a network of Van der Pol oscillators.