The synthesis and optimization of Reaction Control Systems (RCS) for aircraft require precise tuning and adaptation of control structures to meet operational demands. This work focuses on developing a method for designing and adjusting nonlinear components within a complex control system, particularly enhancing PID controllers with analytical networks. These networks consist of predefined functional blocks whose structure and parameters are optimized using genetic algorithms. The proposed approach incorporates a fitness function that evaluates system performance by comparing desired and actual trajectories, enabling automated structural and parameter tuning. Recursive domain splitting transforms trajectory data into symbolic sequences, simplifying similarity analysis and improving evaluation accuracy. The method addresses the challenges of nonlinear system behavior and provides a systematic framework for optimizing control responses, ensuring reliability in high-performance applications. The approach is adaptable for software or hardware implementations, offering practical benefits for complex flight control systems.