Formation control of multi-agent systems with actuator saturation via neural-based sliding mode estimators

Abstract

In this paper, the formation control problem for second-order multi-agent systems with model uncertainties and actuator saturation is investigated. An estimator-based robust formation controller is developed to ensure boundedness of the system’s formation tracking error. To estimate uncertain factors without prior knowledge of their Lipschitz constants, two new estimator designs that combine the neural-based estimation process and the sliding mode technique are proposed. Finite-time stability is achieved by introducing a new terminal estimation surface. Regarding the formation controller design, we provide a new framework to study the combined effect of input saturation and input coupling. Both an adaptive compensator and an input regulation algorithm are employed to attenuate state fluctuation led by the reverse effect. Comparative simulations regarding a multi-robot system are conducted to demonstrate the effectiveness of the proposed estimators and the estimator-based controller.