Introduction to System Modeling and Control. Introduction Basic Definitions Different Model Types System Identification Neural Network Modeling. Mathematical Modeling (MM). A mathematical model represent a physical system in terms of mathematical equations
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Every system is associated with 3 variables:
Linear-Time invariant (LTI)
LTI Input-Output Model
Transfer Function Model
Consider the digital system shown below:
Equivalent to an integrator:
e=p + 0
Number of poles/2
Where p=number of poles/2, Ke=back emf constant
Experimental determination of system model. There are two methods of system identification:
Graphical method is
Neural Network Approach
A single hidden layer perceptron network with a sufficiently large number of neurons can approximate any continuous function arbitrarily close.
Question: Is an arbitrary neural network model consistent with a physical system (i.e., one that has an internal realization)?
(electro-hydraulic poppet valve)