Data Driven-Based Asymmetric Constrained Control for Space Inertia Sensor

Under the control framework of space gravitational wave detection spacecraft platform system, aiming at the high-precision control of nonlinear unmodeled dynamics and performance constraints of space inertial sensor, in this paper, a data-based adaptive control scheme based on data-driven theory was proposed to realize accurate and stable control target of non-affine non-global Lipstchiz space inertial sensor dynamic system. Based on the fuzzy rule, an additional uncertainty estimator is established, and its general approximation characteristics are used to ensure the bounded estimation error. Based on the Control Barrier Function (BLF), an asymmetric performance constraint is constructed, and the BLF-based controller is used to realize the asymmetric constraint control of the closed-loop signal. According to the principle of contraction mapping and the Lyapunov theory of discrete-time system, the boundedness of each closed-loop signal and adaptive estimation is analyzed, and numerical simulation verifies the feasibility and effectiveness of the data-driven adaptive asymmetric constraint control scheme.