Choose a continuous Multiple-Input Multiple-Output (MIMO) system dynamics to depend linearly on the unknown parameter : x=(x,u)y=Cx, where xRn is the system state, uRm is the external input, yRp is the system output, and RN is the vector of constant unknown parameters. Also in (1), (x,u)RnN is the known regressor matrix, and CRpn is the system output known matrix. Model requirements: Choose n2 and p1. The regressor (x,u) can be nonlinear in x and u. Transform Equation (1) into a static linear-in-parameters model. The following method can be used for the linearization of the system. This method is called Filtering Method. Filtering Method: Let >0. Using Equation (1), yields: {x+x=x+(x,u)xf+xf=x,xf(0)=x(0), where xfRn is the filtered state. Note that in Equation (2), the initial conditions for the filter and for the system can be chosen as identical. This is not a requirement for the linearization, but for the simplification of the system. Let z=xxf denote the difference between the system state x and its filtered version xf. Then, z+z=(x,u) and, consequently: z(t)=(0te(t)(x(),u())d). Thus, the system output can be written as