Robustness and Worst-Case Analysis
A robust control system meets stability and performance requirements for all possible values of uncertain parameters. Although Monte-Carlo parameter sampling can yield a general idea of system performance across all uncertainty ranges, it cannot produce a guaranteed analysis of the worst-case parameter combination. The robustness analysis commands in this category directly calculate the upper and lower bounds on worst-case performance without random sampling. You can also calculate robustness margins that tell you how much variation in uncertain parameters the system can tolerate while maintaining stability or desired performance.
|Robust stability of uncertain system|
|Robust performance of uncertain system|
|Scale uncertainty of block or system (Since R2020a)|
|Option set for robustness analysis|
|Gap metric and Vinnicombe (nu-gap) metric for distance between two systems|
|Left normalized coprime factorization (Since R2019a)|
|Right normalized coprime factorization (Since R2019a)|
|Calculate normalized coprime stability margin of plant-controller feedback loop|
|Sensitivity functions of plant-controller feedback loop|
|Compute L2 norm of continuous-time system in feedback with discrete-time system|
|Time response of sampled-data feedback system|
- Robustness and Worst-Case Analysis
Understand the relationships among measures of robust stability, robust performance, and worst-case gain.
- Robust Stability and Worst-Case Gain of Uncertain System
Calculate the robust stability and examine the worst-case gain of a closed-loop uncertain system.
- Worst-Case Sensitivity Functions of Feedback Loops
wcgainto compute the worst-case sensitivity and complementary sensitivity functions of feedback control structures.
- Robust Stability, Robust Performance and Mu Analysis
Analyze and quantify the robustness of feedback control systems with uncertainty, and understand the relationship between robustness and the structured singular value, μ.
- MIMO Robustness Analysis
Create a MIMO system with parametric uncertainty and analyze it for robust stability and worst-case performance.
- Getting Reliable Estimates of Robustness Margins
Systems with only real uncertain parameters can have discontinuities in the structured singular value μ that hide robustness issues.