Robust Barrier Function-based Control for Cryocoolers with Unmodeled Power Dynamics

Environmental activities have led to heightened greenhouse gas emissions, which exacerbate global warming. Transforming production processes is crucial for reducing carbon dioxide (CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>) emissions and absorption in the atmosphere. Previous studies primarily relied on a chemistry-based strategy for the direct removal of CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> from the atmosphere. In this study, we applied a control approach known as barrier function-based adaptive sliding mode to a cryocooler temperature regulator. The proposed approach provides an efficient temperature tracking control in the presence of unmodeled input power fluctuations. To the best of the authors' knowledge, this work represents the first-ever application of a barrier function-based controller to a cryocooler system with a rigorous Lyapunov-based stability analysis and finite-time real-sliding proof. This result was achieved by using detailed error system development to express the cryocooler dynamics in a control-amenable form. Through judicious control gain selection, the designed controller was used to obtain finite-time bounded temperature tracking error regulation with an arbitrarily small region of convergence. Comparative numerical simulations proved that the barrier function-based nonlinear control law offers a better temperature tracking performance than a linear proportional-integral (PI) control law amid unmodeled input power perturbations.