The first step is to represent the system with its known uncertainties, such as parameter variations (e.g., mass, stiffness) or unmodeled high-frequency dynamics.
: Use propagate or usample to generate a set of randomized Bode or step responses to visually inspect how uncertainty affects the time and frequency domains. Robust Control Design with MATLAB
norm of the closed-loop system, effectively suppressing the impact of disturbances and noise. -Synthesis : Use musyn for more complex problems where H∞cap H sub infinity end-sub The first step is to represent the system
: Use robgain to determine if the system meets specific performance goals (like H∞cap H sub infinity end-sub gain) across all uncertainty scenarios. -Synthesis : Use musyn for more complex problems
: Use robstab to find the "robust stability margin," which indicates the percentage of modeled uncertainty the system can handle before becoming unstable.
MATLAB offers several automated methods to design a controller that is "robust by design". H∞cap H sub infinity end-sub Synthesis : Use hinfsyn to minimize the H∞cap H sub infinity end-sub