Abstract:As a complex and unstable nonlinear dynamic behavior, Chaos can easily lead to the oscillation and instability of the power system, and threaten the safe and stable operation of the power system seriously. Based on the finite time theory, this paper proposes a finite time command filter adaptive control method considering static error elimination for chaotic power systems. Firstly,the radial basis function neural network is used to achieve the approximation of the unknown nonlinear function in the power system model. Secondly, the command filter and error compensator are added to realize the derivation and error compensation of the virtual control signal. Finally, in view of the static error problem in the control, introducing the error integral feedback law, design the system's control law through the backstepping method to satisfy the finite time stability, and realize the tracking of the target signal in the chaotic state of the power system, thereby realizing the chaotic control of the power system indirectly. The simulation experiment proves that the method designed in this paper can effectively suppress the chaotic oscillation phenomenon of the power system, eliminate the static error in the control process, further weaken the coupling relationship between the control variables, and ensure the normal operation of the power system.
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