Robust Control Toolbox

Synthesizing Robust Controllers

Robust Control Toolbox lets you automatically tune centralized and decentralized MIMO control systems. The controller synthesis algorithms include H-infinity and mu-synthesis techniques, nonsmooth optimization, and LMI optimization. These algorithms are applicable to SISO and MIMO control systems. MIMO controller synthesis does not require sequential loop closure and is therefore well-suited for multiloop control systems with significant loop interaction and cross-coupling.

Automatic Tuning of Fixed-Structure Control Systems

Most embedded control systems have a fixed, decentralized architecture with simple tunable elements such as gains, PID controllers, or low-order filters. Such architectures are easier to understand, implement, schedule, and retune than complex centralized controllers. Robust Control Toolbox provides tools for modeling and tuning these decentralized control architectures. You can:

  • Specify tunable elements such as gains, PID controllers, fixed-order transfer functions, and fixed-order state-space models
  • Combine tunable elements with ordinary linear time-invariant (LTI) models to create a tunable model of your control architecture
  • Specify and visualize tuning requirements such as tracking performance, disturbance rejection, noise amplification, closed-loop pole locations, and stability margins
  • Automatically tune the controller parameters to satisfy the must-have requirements (design constraints) and to best meet the remaining requirements (objectives)
  • Validate controller performance in the time and frequency domains

Automatic Tuning of a Helicopter Flight Control System 4:56
Automatically tune a multivariable flight control system using Control System Tuner.

In addition to tuning a fixed-structure controller for one plant model, Robust Control Toolbox lets you automatically tune a controller against a set of plant models. You can use this functionality to design a controller that will be robust to changes in plant dynamics due to plant parameter variations, changes in operating conditions, and sensor or actuator failures.

Fault-Tolerant Control of a Passenger Jet
Approximate high-order plant models with simpler, lower-order models. Design a robust controller for an active suspension system using H-infinity and mu-synthesis methods.

H-Infinity and Mu-Synthesis Techniques

Robust Control Toolbox provides several algorithms for synthesizing robust MIMO controllers directly from frequency-domain specifications of the closed-loop responses. For example, you can limit the peak gain of a sensitivity function to improve stability and reduce overshoot, or limit the gain from input disturbance to measured output to improve disturbance rejection. Using mu-synthesis algorithms, you can optimize controller performance in the presence of model uncertainty, ensuring effective performance under all realistic scenarios. H-infinity and mu-synthesis techniques provide unique insight into the performance limits of your control architecture, and let you quickly develop first-cut compensator designs.

Robust Control of an Active Suspension
Approximate high-order plant models with simpler, lower-order models. Design a robust controller for an active suspension system using H-infinity and mu-synthesis methods.

Next: Tuning Gain-Scheduled Controllers

Try Robust Control Toolbox

Get trial software

Automatic Tuning of Gain-Scheduled Controllers

View webinar