Observer‐based neural adaptive fixed‐time tracking control for multi‐input multi‐output nonlinear systems with actuator faults

Abstract

This study developed a new strategy for adaptive fixed-time output feedback control of multi-input multi-output (MIMO) nonlinear systems involving unmeasurable external disturbances and actuator faults. Two actuator faults, loss of effectiveness and lock-in-place were simultaneously considered. Furthermore, a composite observer was used in MIMO systems to estimate unmeasurable states and external disturbances simultaneously, and radial basis function neural networks were employed to identify unknown internal nonlinearities. Additionally, the command-filtered backstepping approach was applied to avoid tedious analytic calculations of the backstepping framework, and a compensation item was constructed to attenuate the filter error. A fault-tolerant controller was developed to ensure that the overall states of the controlled system were practically fixed-time bounded while the tracking error was regulated to the equilibrium region having a fixed-time convergence ratio. Illustrative studies showed the validity and practicability of the proposed theory.

Untitled

“…λ ji represents the adaptive rate of the j uncertain parameter of the i generator in Eq (26) [36][37][38].…”

“…To solve the above problems, this paper applies multi-index nonlinear design to uncertain power systems with uncertain parameters and external interference, combines it with robust control theory and adaptive control theory, proposes a multiindex nonlinear robust adaptive control method, and gives its closed-loop stability proof [14,15]. In [38,39], a decentralized controller based on Lyapunov theory for excitation control of multi-machine power systems ensured global asymptotic stability and realized voltage regulation through excitation control. In [40,41], For the multi-electromechanical power system including largescale photovoltaic energy storage power station, the multi-objective holographic feedback control method is adopted.…”

Untitled

“…λ ji represents the adaptive rate of the j uncertain parameter of the i generator in Eq (26) [36][37][38].…”

“…To solve the above problems, this paper applies multi-index nonlinear design to uncertain power systems with uncertain parameters and external interference, combines it with robust control theory and adaptive control theory, proposes a multiindex nonlinear robust adaptive control method, and gives its closed-loop stability proof [14,15]. In [38,39], a decentralized controller based on Lyapunov theory for excitation control of multi-machine power systems ensured global asymptotic stability and realized voltage regulation through excitation control. In [40,41], For the multi-electromechanical power system including largescale photovoltaic energy storage power station, the multi-objective holographic feedback control method is adopted.…”