Robust Control Toolbox

Design robust controllers for uncertain plants

Robust Control Toolbox™ provides functions, blocks, and an app for analyzing and tuning control systems for performance and robustness. You can create uncertain models by combining nominal dynamics with uncertain elements, such as uncertain parameters or unmodeled dynamics. You can analyze the impact of plant model uncertainty on control system performance and identify worst-case combinations of uncertain elements. H-infinity and mu-synthesis techniques let you design controllers that maximize robust stability and performance.

The toolbox automatically tunes both SISO and MIMO controllers. These can include decentralized, fixed-structure controllers with multiple tunable blocks spanning multiple feedback loops. The toolbox lets you tune one controller against a set of plant models or against a plant model with parametric uncertainty. You can also tune gain-scheduled controllers and specify multiple tuning objectives, such as reference tracking, disturbance rejection, stability margins, and closed-loop pole locations.

Uncertain System Representation

Models of systems with uncertain parameters or unmodeled dynamics

Uncertain System Analysis

Statistical and worst-case analysis of stability and performance

Control System Tuning

Automated tuning of control systems to meet design requirements

Robust Controller Synthesis

Frequency-domain MIMO controller design, controller design for uncertain systems

Model Simplification

Order reduction of plant models and synthesized controllers

Linear Matrix Inequalities

LMI solvers, control system analysis and design with LMIs