Robust Control Toolbox provides tools for analyzing and automatically tuning control systems for performance and robustness. You can create uncertain models by combining nominal dynamics with uncertain elements, such as an uncertain parameter or unmodeled dynamics. You can analyze the impact of plant model uncertainty on control system performance and identify worst-case combinations of uncertain elements. Using H-infinity or mu-synthesis techniques, you can design controllers that maximize robust stability and performance. The toolbox can automatically tune both SISO and MIMO robust controllers, including decentralized control architectures modeled in Simulink(R). You can validate your design by calculating worst-case gain and phase margins and worst-case sensitivity to disturbances. The more important features are de next: - Modeling of systems with uncertain parameters or neglected dynamics - Worst-case stability and performance analysis of uncertain systems - Automatic tuning of centralized and decentralized control systems - Robustness analysis and controller tuning in Simulink - H-infinity and mu-synthesis algorithms - General-purpose LMI solvers for feasibility, minimization of linear objectives, and generalized eigenvalue minimization - Model reduction algorithms based on Hankel singular values
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