Controlling bifurcation in power system based on LaSalle invariant principle

De-min, Wei; Xiao-Shu, Luo; Ying-Hua, Qin

doi:10.1007/s11071-010-9806-3

Cited by 16 publications

(16 citation statements)

References 19 publications

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“…So far a lot of control methods have been studied to suppress chaotic oscillation in power system. Wei 12 designed an adaptive controller based on the LaSalle invariance principle to suppress different undesirable bifurcations which threatened the secure and stable work of power system. Li 13 proposed a robust adaptive fuzzy controller for a single machine bus system through static var compensator.…”

Section: Introductionmentioning

confidence: 99%

Bifurcations, chaos and adaptive backstepping sliding mode control of a power system with excitation limitation

et al. 2016

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The bifurcation and Lyapunov exponent for a single-machine-infinite bus system with excitation model are carried out by varying the mechanical power, generator damping factor and the exciter gain, from which periodic motions, chaos and the divergence of system are observed respectively. From given parameters and different initial conditions, the coexisting motions are developed in power system. The dynamic behaviors in power system may switch freely between the coexisting motions, which will bring huge security menace to protection operation. Especially, the angle divergences due to the break of stable chaotic oscillation are found which causes the instability of power system. Finally, a new adaptive backstepping sliding mode controller is designed which aims to eliminate the angle divergences and make the power system run in stable orbits. Numerical simulations are illustrated to verify the effectivity of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Bifurcations, chaos and adaptive backstepping sliding mode control of a power system with excitation limitation

et al. 2016

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“…Systems (15) and (16) can be expressed in a uniform form (24) with r = 3 for system (15) and r = 2 for system (16):…”

Section: Lemma 2 [54]mentioning

confidence: 99%

“…Besides, too small τ i will increase the control input and control cost. (15) and (16) According to design process for system (24), the design procedure of the proposed control scheme for systems (15) and (16) are listed in Table 2.…”

Section: Remarkmentioning

confidence: 99%

“…As shown in Table 2, the control inputs for systems (15) and (16) are: (16) 1. Virtual control It is straightforward from Theorem 1 that Theorems 2 and 3 hold.…”

Section: Controller Design For Systemsmentioning

confidence: 99%

“…Recently, many chaos control methods have been proposed, such as, feedback control [12], passive control [13], backstepping control [14], adaptive control [15], fuzzy neural network control [16], and sliding mode control [17,18]. Utilizing these control methods, several works have designed power system controllers to suppress chaos and stabilize voltage in three-bus power system.…”

Section: Introductionmentioning

confidence: 99%

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Fixed-time dynamic surface high-order sliding mode control for chaotic oscillation in power system

Liu

et al. 2016

Nonlinear Dyn

130

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In this paper, a fixed-time dynamic surface high-order sliding mode control approach is presented for chaos suppression and voltage stabilization in three-bus power system via design of current source converter-based static synchronous compensator controller. The proposed control strategy constructs two high-order sliding mode surfaces to achieve control objective. By combining backstepping idea with dynamic surface control (DSC) technique, highorder sliding mode controller is designed and the inherent problem of "explosion of complexity" in backstepping design is avoided. Further, a new stability concept is introduced into DSC design to achieve semiglobal uniform ultimate boundedness of the signals in high-order sliding mode system within finite time independent of initial condition. In addition, stability analysis is provided to show that the proposed control scheme can achieve semi-globally fixed-timely uniformly ultimately bounded stabilization. Finally, simulation results are given to demonstrate the effectiveness of the proposed control scheme and the superior performance over conventional DSC.

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Sliding mode control with mismatched disturbance observer for chaotic oscillation in a seven‐dimensional power system model

Wang

Liu

2020

Int Trans Electr Energ Syst

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In this article, a sliding mode control scheme with mismatched disturbance observer to achieve chaos control in power system is presented. A novel design method of mismatched disturbance observer is proposed for a second‐order system with mismatched disturbance, it is proved that the designed observer can theoretically observe disturbances with arbitrary accuracy by adjusting the parameters of disturbance observer artificially, and the designed controller realizes uniformly ultimately bounded asymptotic system stability. The designed disturbance observer and controller exhibit two main features. The first is the form of the observer is simpler than the existing observer. The other is the designed observer and controller do not contain system functions, which makes them can be applied to the control of complex systems. Furthermore, the proposed control scheme is adopted to design mismatched disturbance observers and controllers for suppressing chaotic oscillation in a seven‐dimensional power system model and simulation results are presented to demonstrate its validity.

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Controlling bifurcation in power system based on LaSalle invariant principle

Cited by 16 publications

References 19 publications

Bifurcations, chaos and adaptive backstepping sliding mode control of a power system with excitation limitation

Bifurcations, chaos and adaptive backstepping sliding mode control of a power system with excitation limitation

Fixed-time dynamic surface high-order sliding mode control for chaotic oscillation in power system

Sliding mode control with mismatched disturbance observer for chaotic oscillation in a seven‐dimensional power system model

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