SFG 代数

A node's value equals the sum of all signals entering it. This summed value is then transmitted through every branch leaving the node, with each outgoing branch multiplying the node value by its respective gain. This principle enables signal flow graphs to represent complex system interactions clearly.

Parallel branches in the same direction can be replaced with a single branch whose gain equals the sum of the original branch gains. For example, two parallel branches with gains G1 and G2 become one branch with gain G=G1+G2. This simplification reduces graph complexity while preserving system behavior.

Cascaded or series-connected branches can be replaced with a single branch whose gain equals the product of the original gains. If two branches have gains G1 and G2, they combine into one branch with gain G=G1×G2. This algebraic rule streamlines analysis of sequential signal processing stages.

First, identify each variable and associate it with a node. Second, interconnect nodes with branches representing variable relationships, ensuring accurate signal flow direction. Third, label each branch with its corresponding gain or transfer function. This systematic conversion transforms block diagrams into signal flow graph format for algebraic analysis.

Create nodes for each variable in the equations. Connect nodes with branches based on the relationships defined by the equations. Assign gains to branches according to the coefficients in the equations. This step-by-step construction translates mathematical relationships into visual signal flow representations for system analysis.

Feedback systems in signal flow graphs follow specific algebraic equations that derive the closed-loop transfer function. The process involves recognizing the feedback loop structure and applying appropriate formulas to determine system behavior. This algebraic approach enables engineers to analyze complex control system dynamics systematically.

Branch gains represent transfer functions or coefficients connecting nodes in a signal flow graph. Each branch transmits the signal from its source node multiplied by its gain to the destination node. Gains can be simplified through parallel or cascaded combinations, making them essential for both constructing and analyzing system models.