Adaptive fuzzy inverse optimal output feedback decentralised prescribed performance control for interconnected nonlinear systems

This paper investigates an adaptive fuzzy inverse optimal output feedback decentralised prescribed performance control problem for interconnected systems. Firstly, the fuzzy logic systems (FLSs) are utilised to model unknown nonlinear functions in each subsystem and then an auxiliary system is constructed. Based on the auxiliary system, a fuzzy decentralised state observer is formulated to estimate unmeasurable states. Secondly, by applying the adaptive backstepping design technique and the inverse optimal control theory, an adaptive fuzzy inverse optimal output feedback decentralised controller is ultimately designed. It is proved that the proposed adaptive fuzzy inverse optimal decentralised controller not only minimises the cost function but also ensures that all variables of the control systems are semi-globally ultimately bounded and that the tracking errors converge to a small residual set with the prescribed performance bound. Finally, the effectiveness of the proposed control approach is verified by a nonlinear inverted pendulum large-scale system.