State Space Model
Y cx du.
State space model. Where x and x are the state vector and the differential state vector respectively. State space models linear time invariant lti state space models are a linear representation of a dynamic system in either discrete or continuous time. The ss model object can represent siso or mimo state space models in continuous time or discrete time.
The true power of the state space model is to allow the creation and estimation of custom models. The state variables define the values of the output variables. U is the input vector and y is the output vector.
A descriptor state space model is a generalized form of state space model. State space models are models that use state variables to describe a system by a set of first order differential or difference equations rather than by one or more n th order differential or difference equations. The first and the second equations are known as state equation and output equation respectively.
One describing how a latent process transitions in time the state equation another describing how an observer measures the latent process at each period the observation equation. A is the system matrix. Putting a model into state space form is the basis for many methods in process dynamics and control analysis.
U and y are input vector and output vector respectively. A state space model is a mathematical representation of a physical system as a set of input output and state variables related by first order differential equations. Below is the continuous time form of a model in state space form.
In control engineering a state space representation is a mathematical model of a physical system as a set of input output and state variables related by first order differential equations or difference equations. A state space model is a discrete time stochastic model that contains two sets of equations. E d x d t a x b u y c x d u where x is the state vector.