Command Filtered Adaptive Fuzzy Neural Network Backstepping Control for Marine Power System

Abstract

In order to retrain chaotic oscillation of marine power system which is excited by periodic electromagnetism perturbation, a novel command-filtered adaptive fuzzy neural network backstepping control method is designed. First, the mathematical model of marine power system is established based on the two parallel nonlinear model. Then, main results of command-filtered adaptive fuzzy neural network backstepping control law are given. And the Lyapunov stability theory is applied to prove that the system can remain closed-loop asymptotically stable with this controller. Finally, simulation results indicate that the designed controller can suppress chaotic oscillation with fast convergence speed that makes the system return to the equilibrium point quickly; meanwhile, the parameter which induces chaotic oscillation can also be discriminated.

Robust adaptive command filtered control of a robotic manipulator with uncertain dynamic and joint space constraints

“…Dong et al 37 proposed an adaptive approach of the previous idea. Zhang et al 38 used command filters backstepping in adaptive fuzzy neural network control for a marine power system. In refs.…”

Chaos suppression for a four-dimensional fundamental power system model using adaptive feedback control

“…The rapid development of modern control theory has provided many advanced control methods for chaos control, such as finite time control (Wei et al, 2014a), feedback control (Chen and Han, 2003), fuzzy control (Vembarasan and Balasubramaniam, 2013), backstepping control (Zhang and Mu, 2014), adaptive control (Wei et al, 2014b), sliding mode control (Aghababa and Feizi, 2012), projective synchronization (Wang and He, 2008), passive control (Wei and Luo, 2007a), neural network control (Kao et al, 2011), optimal control (Chavarette et al, 2009), etc. Some of them have been applied to design a power system controller, such as Thyristor Controlled Series Compensation (TCSC) (Jiang et al, 2012), Static Var Compensator (SVC) (Ginarsa et al, 2013), Power System Stabilizer (PSS) (Farhang and Mazlumi, 2013) and Unified Power Flow Controller (UPFC) (Jiang et al, 2006).…”

Linear Matrix Inequality Based Fuzzy Synchronization for Fractional Order Chaos

“…For example, in [26], a new controller is proposed via fuzzy logic for real-time substructuring applications, and the effectiveness is proved by evaluating the response of a framework fixed at one of the beam joints for El-Centro earthquake. In [27], by introducing fuzzy techniques, a command-filtered adaptive fuzzy neural network backstepping control law is presented to restrain chaotic oscillation of marine power system. In [28], a fuzzy adaptive control law is proposed for the projective synchronization of unknown multivariable chaos.…”