Multivariable offset-free MPC with steady-state target calculation and its application to a wind tunnel system

Area of Science:

• Aerospace Engineering
• Control Systems Engineering
• Computational Fluid Dynamics

Background:

• Intermittent transonic wind tunnels (ITWT) require precise control for efficient operation.
• Set-point optimization is crucial for maximizing the performance and data quality in wind tunnel testing.

Purpose of the Study:

• To develop and validate a computationally efficient Model Predictive Control (MPC) approach for set-point optimization in an ITWT.
• To demonstrate the application and effectiveness of the proposed MPC strategy on a real-world ITWT.

Main Methods:

• Utilizing a Kalman filter for open-loop dynamic and steady-state predictions of manipulated and controlled variables.
• Employing a linearized steady-state model for set-point optimization via linear programming (LP) in steady-state target calculation (SSTC).
• Implementing dynamic control through quadratic programming (QP) to compute optimal control moves based on optimized set-points.

Main Results:

• The proposed MPC approach demonstrated computational efficiency.
• Satisfactory performance was achieved when applied to the intermittent transonic wind tunnel.
• The method effectively optimized set-points for the ITWT.

Conclusions:

• The developed MPC strategy offers an efficient solution for set-point optimization in ITWT.
• The integration of Kalman filtering, LP, and QP provides a robust control framework.
• The successful application on ITWT validates the practical utility of the proposed method.