Optimization Control Algorithm Implementation

This document presents an optimization control algorithm implemented using Newton's Gradient Method, accompanied by complete MATLAB source code. The algorithm's architecture leverages MATLAB's computational efficiency for numerical optimization and matrix operations. Key implementation aspects include: iterative gradient descent with Newton direction computation, Hessian matrix formulation for second-order derivatives, and convergence criteria handling. The algorithm demonstrates particular strength in high-dimensional optimization scenarios through vectorized operations and sparse matrix utilization. Beyond control systems applications, the codebase can be adapted for general optimization problems and machine learning tasks like parameter tuning and loss function minimization. We recommend examining the source code's core functions - particularly the optimization solver, gradient calculator, and termination condition modules - for deeper technical understanding and potential customization.