2 research outputs found
Fuzzy second order sliding mode control of a unified power flow controller
Purpose. This paper presents an advanced control scheme based on fuzzy logic and second order sliding mode of a unified power flow controller. This controller offers advantages in terms of static and dynamic operation of the power system such as the control law is synthesized using three types of controllers: proportional integral, and sliding mode controller and Fuzzy logic second order sliding mode controller. Their respective performances are compared in terms of reference tracking, sensitivity to perturbations and robustness. We have to study the problem of controlling power in electric system by UPFC. The simulation results show the effectiveness of the proposed method especiallyin chattering-free behavior, response to sudden load variations and robustness. All the simulations for the above work have been carried out using MATLAB / Simulink. Various simulations have given very satisfactory results and we have successfully improved the real and reactive power flows on a transmission lineas well as to regulate voltage at the bus where it is connected, the studies and illustrate the effectiveness and capability of UPFC in improving power.Π Π½Π°ΡΡΠΎΡΡΠ΅ΠΉ ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° ΡΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½Π½Π°Ρ ΡΡ
Π΅ΠΌΠ° ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½Π°Ρ Π½Π° Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ Π»ΠΎΠ³ΠΈΠΊΠ΅ ΠΈ ΡΠ΅ΠΆΠΈΠΌΠ΅ ΡΠΊΠΎΠ»ΡΠΆΠ΅Π½ΠΈΡ Π²ΡΠΎΡΠΎΠ³ΠΎ ΠΏΠΎΡΡΠ΄ΠΊΠ° ΡΠ½ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠ° ΠΏΠΎΡΠΎΠΊΠ° ΠΌΠΎΡΠ½ΠΎΡΡΠΈ. ΠΠ°Π½Π½ΡΠΉ ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅Ρ ΠΎΠ±Π»Π°Π΄Π°Π΅Ρ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π°ΠΌΠΈ Ρ ΡΠΎΡΠΊΠΈ Π·ΡΠ΅Π½ΠΈΡ ΡΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ°Π±ΠΎΡΡ ΡΠ½Π΅ΡΠ³ΠΎΡΠΈΡΡΠ΅ΠΌΡ, Π½Π°ΠΏΡΠΈΠΌΠ΅Ρ, Π·Π°ΠΊΠΎΠ½ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠΈΠ½ΡΠ΅Π·ΠΈΡΡΠ΅ΡΡΡ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΡΠ΅Ρ
ΡΠΈΠΏΠΎΠ² ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠΎΠ²: ΠΏΡΠΎΠΏΠΎΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎ-ΠΈΠ½ΡΠ΅Π³ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ, ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠ° ΡΠΊΠΎΠ»ΡΠ·ΡΡΠ΅Π³ΠΎ ΡΠ΅ΠΆΠΈΠΌΠ° ΠΈ ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠ° ΡΠΊΠΎΠ»ΡΠ·ΡΡΠ΅Π³ΠΎ ΡΠ΅ΠΆΠΈΠΌΠ° Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ Π»ΠΎΠ³ΠΈΠΊΠΈ Π²ΡΠΎΡΠΎΠ³ΠΎ ΠΏΠΎΡΡΠ΄ΠΊΠ°. ΠΡ
ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΠ΅ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈ ΡΡΠ°Π²Π½ΠΈΠ²Π°ΡΡΡΡ Ρ ΡΠΎΡΠΊΠΈ Π·ΡΠ΅Π½ΠΈΡ ΠΎΡΡΠ»Π΅ΠΆΠΈΠ²Π°Π½ΠΈΡ ΡΡΠ°Π»ΠΎΠ½ΠΎΠ², ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΊ Π²ΠΎΠ·ΠΌΡΡΠ΅Π½ΠΈΡΠΌ ΠΈ Π½Π°Π΄Π΅ΠΆΠ½ΠΎΡΡΠΈ. ΠΠ΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΠΈΠ·ΡΡΠΈΡΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΌΠΎΡΠ½ΠΎΡΡΡΡ Π² ΡΠ½Π΅ΡΠ³ΠΎΡΠΈΡΡΠ΅ΠΌΠ΅ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠ½ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠ° ΠΏΠΎΡΠΎΠΊΠ° ΠΌΠΎΡΠ½ΠΎΡΡΠΈ (UPFC). Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π°, ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎ Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΎΡΡΡΡΡΡΠ²ΠΈΡ Π²ΠΈΠ±ΡΠ°ΡΠΈΠΈ, ΡΠ΅Π°ΠΊΡΠΈΠΈ Π½Π° Π²Π½Π΅Π·Π°ΠΏΠ½ΡΠ΅ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Π½Π°Π³ΡΡΠ·ΠΊΠΈ ΠΈ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΠΈ. ΠΡΠ΅ ΡΠ°ΡΡΠ΅ΡΡ Π΄Π»Ρ Π²ΡΡΠ΅ΡΠΊΠ°Π·Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΡ Π±ΡΠ»ΠΈ Π²ΡΠΏΠΎΠ»Π½Π΅Π½Ρ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ MATLAB/Simulink. Π Π°Π·Π»ΠΈΡΠ½ΡΠ΅ ΡΠ°ΡΡΠ΅ΡΠ½ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π΄Π°Π»ΠΈ Π²Π΅ΡΡΠΌΠ° ΡΠ΄ΠΎΠ²Π»Π΅ΡΠ²ΠΎΡΠΈΡΠ΅Π»ΡΠ½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ, ΠΈ ΠΌΡ ΡΡΠΏΠ΅ΡΠ½ΠΎ ΡΠ»ΡΡΡΠΈΠ»ΠΈ ΠΏΠΎΡΠΎΠΊΠΈ ΡΠ΅Π°Π»ΡΠ½ΠΎΠΉ ΠΈ ΡΠ΅Π°ΠΊΡΠΈΠ²Π½ΠΎΠΉ ΠΌΠΎΡΠ½ΠΎΡΡΠΈ Π½Π° Π»ΠΈΠ½ΠΈΠΈ ΡΠ»Π΅ΠΊΡΡΠΎΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠ΅Π³ΡΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π½Π°ΠΏΡΡΠΆΠ΅Π½ΠΈΡ Π½Π° ΡΠΈΠ½Π΅, ΠΊ ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΎΠ½Π° ΠΏΠΎΠ΄ΠΊΠ»ΡΡΠ΅Π½Π°, ΡΡΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΈΠ·ΡΡΠΈΡΡ ΠΈ ΠΏΡΠΎΠΈΠ»Π»ΡΡΡΡΠΈΡΠΎΠ²Π°ΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΈ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ UPFC Π΄Π»Ρ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΡ ΠΌΠΎΡΠ½ΠΎΡΡΠΈ
Intelligent nonsingular terminal sliding-mode control via perturbed fuzzy neural network
[[abstract]]In this paper, an intelligent nonsingular terminal sliding-mode control (INTSMC)
system, which is composed of a terminal neural controller and a robust compensator, is proposed for an unknown nonlinear system. The terminal neural controller including a
perturbed fuzzy neural network (PFNN) is the main controller and the robust compensator is
designed to eliminate the effect of the approximation error introduced by the PFNN upon the system stability. The PFNN is used to approximate an unknown nonlinear term of the system dynamics and perturbed asymmetric membership functions are used to handle rule
uncertainties when it is hard to exactly determine the grade of membership functions. In additional, Lyapunov stability theory is used to discuss the parameter learning and system stability of the INTSMC system. Finally, the proposed INTSMC system is applied to an inverted pendulum and a voice coil motor actuator. The simulation and experimental results show that the proposed INTSMC system can achieve favorable tracking performance and is robust against parameter variations in the plant