Neural-based formation control of uncertain multi-agent systems with actuator saturation

The formation control problem for a group of first-order agents with model uncertainty and actuator saturation is investigated in this manuscript. An algorithm-and-observer-based formation controller is developed to ensure the semi-global boundedness of the formation tracking error with actuator saturation. First, a fully local-error-related cooperative weight tuning procedure is proposed for the adaptive uncertainty estimation of each agent. The effect of actuator saturation on both the cooperative adaptive estimation and the controller design part is then analysed and discussed. A three-layer neural-based observer is further constructed to achieve finite-time uncertainty approximation with actuator saturation. Besides, the reverse effect led by coupled and saturated control inputs is defined and a new control input distribution algorithm is presented to attenuate the potential oscillation in system states. Finally, comparative simulations based on a multiple omnidirectional robot system are conducted to illustrate the performance of the proposed formation controllers and the new algorithm.