Nonlinear Dynamics and Adaptive Control Using the Dynamic Inversion Concept and Neural Networks for a Guidance Gyrosystem (Gg) With One Gyroscope and Two Suspension Gimbals (Gar) Part 2. Adaptive Control Arhitecture Desing and Validation

This paper presents the design of the adaptive control system of GG with GAR, consisting of a stabilization controller and an orientation controller; the concept of dynamic inversion is used. The equations of nonlinear dynamics of GG were obtained in Part 1 of this paper series.The stabilization controller (for the stabilization mode) consists of a 2nd order reference model, a linear dynamic compensator, of the P.D type, a linear state observer and a neural network. The neural network models the adaptive component of the control law, which has the role of compensating for the dynamic inversion error. The orientation controller is chosen as P.I. type. In stabilization mode, the system compensates for the effect of external disturbances induced by the rotations of the base (rocket), and in orientation mode, the system controls the rotation of the target coordinator TC so that the sighting line (TC axis) overlaps the guidance line. By numerical simulations, using the Matlab/Simulink model, the dynamic characteristics of GG are drawn for the stabilization mode and for the orientation mode