### (d) Most systems are considered as noisy in real life, where the real dynamics can be modeled as ( dot{x}(t)=A x(t)+B u(t)+w(t) ) where ( w(t) ) is the noise. We can assume that ( w(t) ) is a random variable with a well known distribution. Here, you can implement this via the randn or rand commands in MATLAB. For example, you can write ( w=0.1 *

(d) Most systems are considered as noisy in real life, where the real dynamics can be modeled as ( dot{x}(t)=A x(t)+B u(t)+w(t) ) where ( w(t) ) is the noise. We can assume that ( w(t) ) is a random variable with a well known distribution. Here, you can implement this via the randn or rand commands in MATLAB. For example, you can write ( w=0.1 *