Features of control system
All standard model representations are supported, including transfer function, zero-pole-gain, explicit and descriptor state-space, and frequency-response data. Linear models can be SISO or MIMO, and continuous or discrete. You can represent PID controllers as PID objects. In addition, you can accurately model and simulate systems with time delays, including feedback loops with delays.
Control System Toolbox enables you to create and work with collections of linear models and model arrays. You can use model arrays to represent and analyze sensitivity to parameter variations or to validate a controller design against several plant models. You can also approximate nonlinear dynamics using linear parameter-varying (LPV) systems. The toolbox lets you simulate such systems using LPV System block.
Building a model of your plant is usually the first step in designing a control system. If no linear model is available, you can build one by fitting test data using System Identification Toolbox™, or by linearizing a Simulink® model using Simulink Control Design™. Once you have created a linear model, you can use Control System Toolbox to analyze it and design a controller.