Abstract
In this paper, an adaptive dynamic surface integral sliding mode fault-tolerant controller is designed for the multimachine power system with static var compensator (SVC) to overcome the problem of actuator failure. The main features of the proposed method are as follows: (1) By combining the dynamic surface control (DSC) method with integral sliding mode (ISM), the tracking errors of the system converge to the neighborhood of zero within a finite time, and the convergence speed, tracking accuracy, and anti-interference ability of the system are also significantly improved. (2) By introducing the failure factors, an adaptive fault-tolerant controller is designed to ensure the stability of the entire system after partial failure of the actuator. (3) By estimating the norm of the ideal weight vector of the radial basis function neural networks (RBFNNs), the computational burden of the controller is reduced. Finally, the simulation results show the effectiveness of the proposed control scheme.
Highlights
System Dynamic Models and Problem StatementAccording to (2) and (15) and (20), we can obtain the following mathematical model of multimachine power systems with static var compensator (SVC): x_i1 x_i2
E static var compensator (SVC) control is one of the effective and economical means of improving the stability of power systems
Considering the external disturbance and parameter uncertainty, a nonlinear adaptive robust coordination controller for SVC and generator excitation is designed. e energy-based coordinated stability controller is constructed by using the Hamiltonian function method in [47, 48], which effectively improves the transient stability and voltage regulation performance of the power systems
Summary
According to (2) and (15) and (20), we can obtain the following mathematical model of multimachine power systems with SVC: x_i1 x_i2. Xd i X3i + X2i + X3iX2i BLi − BCi, X3i xdi + XTi. Since the damping coefficient Di is difficult to measure accurately, Di is treated as an uncertainty parameter, and the nonlinear system with uncertain parameters (1) is transformed by equation (20) into a feedback form as shown in equation (23), so that the dynamic surface integral sliding mode method can be used to design the controller of the system equation (23). Consider the closed-loop control system, including multimachine systems model with actuator failure (23), SVC system model (24), first-order low-pass filters (T2.3) and (T2.7), actual control laws (T2.10) and (T2.14), and adaptive update laws (T2.6), (T2.11), (T2.12), and (T2.15). Proof. e specific proof can be seen in the Appendix
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