Background: This thesis investigates and designs guidance algorithms based on numerical optimization in constrained guidance systems. Due to inherent complexities and the presence of constraints, guidance systems require advanced algorithms capable of finding optimal and efficient paths despite multiple constraints. Numerical optimization algorithms, utilizing optimization techniques, have the ability to manage constraints and find optimal solutions. In this research, computer simulations are employed for modeling and evaluating the performance of these algorithms. Additionally, theoretical analyses assist in assessing the accuracy and efficiency of the algorithms under various conditions.
Aim: The primary objective of this research is to achieve an optimal guidance signal and command, considering the constraints and limitations present in guidance systems. Using numerical optimization methods, this study aims to provide an optimal guidance signal and command for a constrained two-dimensional guidance problem. Existing methods encounter complexities in integrating system constraints into guidance algorithms. This research seeks to find the optimal guidance signal while considering various constraints of the guidance system.
Methodology: The first step of this research involves reviewing existing work and investigating past studies to define and formulate the guidance problem. The next step is to elucidate the guidance problem, review the problem-solving methods, and focus on optimization-based methods. Subsequently, the aim is to solve a constrained optimization problem, which is generally nonlinear and non-convex, using MATLAB software. For simplicity, the proposed problem is simulated in Simulink, and the corresponding codes are added to Simulink. Finally, the results are compared with several existing guidance algorithms, demonstrating the superiority of the proposed method.
Findings: The main findings of this research include the design and implementation of gui