Temperature control in a cryogenic wind tunnel is the key to realizing finely controlled Reynolds number close to true flight. This study deploys the L1 adaptive control methodology to ensure the total temperature profile of the cryogenic wind tunnel tracks a specified reference trajectory. After introducing a non-linear model of a cryogenic wind tunnel and a linear temperature model, a linear–quadratic–Gaussian (LQG) controller is implemented as the baseline controller. The L1 adaptive controller with piecewise constant adaptive law is used as an augmentation to the baseline controller to cancel the matched and unmatched uncertainties within the actuator’s bandwidth. By introducing two modifications to the standard L1 adaptive controller, which are the transportation delay modelling in the state predictor and the non-linear state dependent filter, the L1 adaptive controller improves the performance of the baseline controller in the presence of uncertainties in temperature control, guaranteeing proper stability and delay margin. The simulation results and analysis demonstrate the effectiveness of the proposed control architecture. The main contribution of this paper lies in the first applications of L1 adaptive control to the wind tunnel control problem and the non-linear state dependent filter in L1 adaptive control structure.

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Cryogenic wind tunnel is a sophisticated aerodynamics ground test facility, which operates in cryogenic temperature with injection of liquid nitrogen. The multivariable, nonlinear and coupled dynamics existing between the temperature, pressure and Mach number in the tunnel, poses great challenges for the effective control of the tunnel. L 1 adaptive control is a new control methodology developed in recent years with good robustness properties, which has good potentials to address these challenges. But this control method does not provide full adaptive feedforward control in its generic structure. In the paper, adaptive feedforward control action is introduced into the standard L 1 adaptive control architecture for nonlinear systems in the presence of matched un-modeled dynamics. This new control structure is applied to the stagnation pressure control in a cryogenic wind tunnel, which could also be used for the control of temperature and Mach number in the tunnel. This new method could effectively compensate known disturbances with linear gain uncertainty, which occur in the nonlinear systems, while retaining the closed-loop control performance of L 1 adaptive control. After the proof and discussions on the stability of this method, simulations of the stagnation pressure control in the wind tunnel are presented. The results and analysis demonstrate the effectiveness of the proposed control architecture.

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