Zero-sum game-based H∞ optimal finite-time prescribed performance control for nonlinear multiagent systems with actuator faults

This article proposes an H-infinity optimal leader-follower consensus control protocol with finite-time prescribed performance for nonlinear multiagent systems suffering from the actuator fault based on the zero-sum game framework. First, to guarantee the specified performance of the system within a finite time frame, a novel error transformation function (ETF) is constructed. The ETF proposed in this paper can adjust the mapping range of error transformation to achieve better error convergence performance, thereby enhancing the flexibility of the controller design. Then, to compensate for the negative impact of actuator fault, an error-related item is separated from the optimal performance index function to design an online fault estimator, which can obtain a better error estimation accuracy. Furthermore, to lessen the need for difficult-to-verify persistent excitation signal in adaptive dynamic programming algorithm, both historical and real-time data are applied to adjust the updating law of neural network weight. Moreover, it demonstrates that the signals within the closed-loop system are bounded and the expected finite-time prescribed performance can be ensured in the presence of faults. Finally, a numerical example of multiple single-link robots manipulator system is executed to validate the efficacy of the developed scheme.