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Model and Controller Simplification

Order reduction of plant models and synthesized controllers

Complex models are not always required for good control. Optimization methods, including methods based on HH2, and µ-synthesis optimal control theory, generally produce controllers with at least as many states as the plant model. Model-order reduction commands help you to find less complex low-order approximations to plant and controller models.


ncfmrModel reduction from normalized coprime factorization
reduceSimplified access to Hankel singular value based model reduction functions
balancmrBalanced model truncation via square root method
bstmrBalanced stochastic model truncation (BST) via Schur method
hankelmrHankel minimum degree approximation (MDA) without balancing
hankelsvCompute Hankel singular values for stable/unstable or continuous/discrete system
modrealModal form realization and projection
schurmrBalanced model truncation via Schur method
dcgainmrReduced order model
slowfastSlow and fast modes decomposition