Quadrotor Adaptive Control with Simulink Implementation

This article provides a comprehensive examination of quadrotor adaptive control algorithms implemented in Simulink. The framework comprises two primary adaptive control methodologies: identification-based adaptive control and parameter adjustment-based adaptive control without explicit system identification. We will delve into the functional implementation details of each module. For the identification-based adaptive approach, we demonstrate how to integrate system identification modules to dynamically recognize quadrotor parameters, enabling more precise control through real-time model updates using recursive least squares (RLS) or similar identification algorithms. The non-identification adaptive method focuses on parameter optimization techniques where control parameters are adjusted based on performance metrics without explicit system modeling, often implementing model reference adaptive control (MRAC) or self-tuning regulators. Additionally, we detail PID control algorithm implementation, a fundamental control strategy for quadrotors, covering proportional, integral, and derivative gain tuning methods and their Simulink block configurations. Through detailed implementation examples and algorithm explanations, this content will enhance understanding of quadrotor control principles and practical implementation techniques for effective mastery of these advanced control systems.