An Adaptive and Robust Control Strategy for Real-Time Hybrid Simulation.

Area of Science:

• Structural Engineering
• Control Systems Engineering
• Computational Mechanics

Background:

• Real-time hybrid simulation (RTHS) is a powerful technique for analyzing complex or large-scale structures by integrating numerical and physical components.
• Designing control systems for RTHS presents significant challenges due to intricate feedback loops and the complexity of physical control plants.

Purpose of the Study:

• To propose a novel RTHS control strategy that simplifies design and enhances performance.
• To address the challenges associated with control system design in RTHS by integrating adaptive and robust control theories.

Main Methods:

• A novel control strategy combining adaptive and robust control theories is proposed.
• A simplified 'reformed plant' is utilized for control system design, avoiding direct modeling of the complex physical plant.
• The adaptation feature is achieved using a bounded-gain forgetting least-squares estimator.
• The robustness feature is implemented via a sliding mode controller.

Main Results:

• The proposed control strategy simplifies the control system design process for RTHS.
• The strategy does not necessitate a precise physical plant model, enhancing practicality.
• Validation was performed using a benchmark problem involving a nonlinear three-story steel frame RTHS.

Conclusions:

• The developed RTHS control strategy offers an efficient and practical solution for cyber-physical testing of structures.
• The integration of adaptive and robust control simplifies design while maintaining performance.
• This approach is suitable for investigating complex structural systems through RTHS.