Advanced Control Strategies for Aerospace Benchmark Systems: Comparative Analysis and Mathematical Validation

This paper presents a detailed investigation of advanced control methodologies applied to the longitudinal flight dynamics of a benchmark aircraft model. The objective is to determine the most effective controller in terms of tracking accuracy, robustness to external disturbances, and real-time implementation feasibility. The benchmark system used in this study simulates a high-fidelity aerospace scenario involving turbulence and actuator limitations. The study evaluates and compares several modern control techniques—such as Optimal Control, Model Predictive Control (MPC), Sliding Mode Control (SMC), and Adaptive Control—within the context of aerospace systems, including flight path tracking, attitude stabilization, and disturbance rejection. Each method is rigorously formulated with mathematical models that support the controller design and stability proofs, ensuring theoretical soundness and real-world applicability. Simulations based on representative aerospace scenarios demonstrate the transient and steady-state performance of each approach under common disturbances, uncertainties, and operational constraints. The comparative results highlight the trade-offs between control effort, robustness, and real-time computational feasibility. This work provides valuable insights into the practical implementation of advanced control algorithms in modern aerospace systems, contributing to enhanced performance, reliability, and mission success.