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Explore the behavior of x(t) and y(t) in linear systems, covering homogeneous and non-homogeneous solutions, properties, convolution, and zero-input/zero-state responses. Learn to find the state transition matrix using Maison’s gain formula and various methods like Cayley-Hamilton Theorem. Discover diagonalization, phase-variable form, and Jordan form in generalized eigenvectors.
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Linear system 1. Analysis Lesson 6 State transition matrix linear system by Meiling CHEN
The behavior of x(t) et y(t) : • Homogeneous solution of x(t) • Non-homogeneous solution of x(t) linear system by Meiling CHEN
Homogeneous solution State transition matrix linear system by Meiling CHEN
Properties linear system by Meiling CHEN
Non-homogeneous solution Convolution Homogeneous linear system by Meiling CHEN
Zero-input response Zero-state response linear system by Meiling CHEN
Example 1 Ans: linear system by Meiling CHEN
Using Maison’s gain formula linear system by Meiling CHEN
How to find State transition matrix Methode 1: Methode 2: Methode 3: Cayley-Hamilton Theorem linear system by Meiling CHEN
Methode 1: linear system by Meiling CHEN
Methode 2: diagonal matrix linear system by Meiling CHEN
Diagonization linear system by Meiling CHEN
Diagonization linear system by Meiling CHEN
Case 1: depend linear system by Meiling CHEN
In the case of A matrix is phase-variable form and Vandermonde matrix for phase-variable form linear system by Meiling CHEN
Case 1: depend linear system by Meiling CHEN
Case 3: Jordan form Generalized eigenvectors linear system by Meiling CHEN
Example: linear system by Meiling CHEN
Method 3: linear system by Meiling CHEN
any linear system by Meiling CHEN
Example: linear system by Meiling CHEN
Example: linear system by Meiling CHEN