A Simple MATLAB Implementation of Iterative Learning Control

This is a simple iterative learning control program implemented in MATLAB. Iterative learning control is a reinforcement learning technique that optimizes system control performance through continuous trial-and-error adjustments. The program implements common iterative learning algorithms including Q-Learning and SARSA, utilizing key MATLAB toolboxes such as the Reinforcement Learning Toolbox for algorithm implementation and the Control System Toolbox for dynamic system modeling. The implementation features state-space representation for environment modeling, reward function design for performance evaluation, and policy iteration mechanisms for control optimization. Although this program serves as a fundamental implementation, it provides an excellent starting point for beginners to understand core concepts like value iteration, policy updates, and exploration-exploitation tradeoffs in iterative learning control systems. The code structure includes clear function modularization for easy modification and extension of learning parameters and control strategies.