MATLAB Implementation of Nested Saturation Control Algorithm for Quadrotor Aircraft
- Login to Download
- 1 Credits
Resource Overview
Detailed Documentation
The nested saturation control algorithm for quadrotor aircraft is a robust control method commonly used to solve attitude stabilization problems. This algorithm employs hierarchically designed saturation functions to constrain control signals, ensuring system stability even under the influence of nonlinear characteristics.
The core control logic consists of two layered saturation constraints: the inner layer limits the amplitude of angular velocity feedback, while the outer layer further constrains the output range of attitude error signals. This hierarchical design effectively suppresses overshoot, enhances the system's disturbance rejection capability, and prevents loss of control caused by actuator saturation.
The MATLAB implementation typically includes the following modules: - Establishment of quadrotor dynamic model containing attitude dynamic equations - Design of dual saturation function structure with determination of saturation limits for each layer - Construction of error calculation module (attitude error and angular velocity error) - Implementation of control law calculation, converting saturated signals into motor PWM commands The implementation involves creating functions for saturation limits using MATLAB's saturation functions like 'saturate()' or custom clamping functions, while the control algorithm structure follows a cascaded approach with nested saturation blocks.
Compared to traditional PID control, this algorithm demonstrates stronger disturbance rejection capability, making it particularly suitable for outdoor flight scenarios with uncertain factors like wind disturbances. During practical debugging, saturation limit thresholds need to be adjusted according to the aircraft's inertial parameters to achieve a balance between response speed and stability. Code implementation typically requires parameter tuning through iterative simulation tests using MATLAB's optimization tools.
- Login to Download
- 1 Credits