Parameter Optimization-Based Automatic Design of Launch Vehicle's Attitude Controller

Abstract

This paper presents a new framework for designing a linear attitude controller of a launch vehicle during its ascent phase, using heuristic parameter optimization techniques. Attitude control is particularly important during this phase, as aerodynamic instability can lead to catastrophic consequences. The proposed approach utilizes a linearized model of the launch vehicle's dynamics, which is obtained from the nonlinear equations of motion about a reference trajectory that incorporates structural bending, propellant sloshing, and engine inertial effects (TWD, Tail-WagDog). The control structure consists of Proportional-Derivative feedback for attitude angle and the bending filter that gain-stabilizes the structural bending modes. The design parameters for the feedback and filter are designed upon the formed linear system of the launch vehicle by the series of the optimization problems designated for each part of control algorithm to mitigate the interdependency between the PD feedback and the bending filter. The parameter optimization problems are solved repeatedly using the heuristic optimization algorithm until the feedback gains and filter parameters converges to the optimal value. The proposed design scheme is verified by both linear and nonlinear methods. The resulting control algorithm can satisfy desired performance specification and stability criteria while robustly stabilize the structural bending as verified by Monte-Carlo sampling of the linear systems. Then, the highfidelity 6DOF simulation is conducted to verify the performance and stability of the designed control algorithm under the nonlinear setting. The proposed approach has several advantages over traditional design methods, which often rely on heuristic tuning of controller parameters by control engineers. The proposed approach can systematically explore the feasible space of design parameters and identify optimal controller parameters that satisfy the desired performance specifications and stability criteria. This can lead to more efficient and effective controller designs or provide a reference design to be improved upon.