Program for Model Reference Adaptive Control Based on Gradient Method (MIT-MRAC)

MATLAB 713B 306 views 0 downloads 1 credits
Tags:

Resource Overview

Implementation of Model Reference Adaptive Control (MRAC) using the MIT rule gradient descent approach for uncertain system adaptation

Detailed Documentation

This program implements Model Reference Adaptive Control (MRAC) using the gradient-based MIT rule approach (MIT-MRAC). The algorithm represents an adaptive control methodology that ensures tracking error convergence to zero in systems with uncertainties. The implementation employs the model reference control concept by comparing the controller performance against a reference model to achieve adaptive control for unknown systems. Key programming components include real-time parameter adjustment using gradient descent optimization, reference model tracking through error minimization, and adaptive law implementation for continuous controller refinement. The code structure facilitates simulation of various dynamic systems while providing control engineers with an effective tool for designing and developing robust adaptive control systems. Algorithm features include Lyapunov stability-based parameter update rules and real-time performance monitoring capabilities.

You May Also Like