Four-order power system chaotic control method of bidirectional optimization BP neural network sliding mode variable structure
A BP neural network, sliding mode variable structure technology, applied in the direction of reducing/preventing power oscillation, etc., can solve the problems that affect the application effect of neural network, cannot achieve chaotic oscillation, and cannot solve the chattering problem, so as to weaken the chattering phenomenon, Improving the generalization ability and suppressing the effect of chattering
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[0060] The invention provides a fourth-order power system chaos control method for bidirectionally optimizing BP neural network sliding mode variable structure, comprising the following steps:
[0061] Step 1: Establish the chaotic mathematical model of the fourth-order power system, and simplify the chaotic mathematical model of the fourth-order power system to establish the controlled system;
[0062] according to Figure 4 As shown, the fourth-order power system chaos mathematical model described in step 1 is:
[0063]
[0064] in Generator power angle δ m , slip angular frequency ω s , node voltage phase angle δ, node voltage amplitude U, load reactive power Q 1 and mechanical input power P m , d m is the damping coefficient, M is the inertia constant, m is related to the generator, E m is the electromotive force of the generator, E' 0 is the transient electromotive force of the network, Y' 0 is the network admittance parameter, θ' 0 is the network impedance ...
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