This article investigates the collision-free cooperative formation control problem for second-order multiagent systems with unknown velocity, dynamics uncertainties, and limited reference information. An observer-based sliding mode control law is proposed to ensure both the convergence of the system's tracking error and the boundedness of the relative distance between each pair of agents. First, two new finite-time neural-based observer designs are introduced to estimate both the agent velocity and the system uncertainty. The sliding mode differentiator is then employed for every agent to approximate the unknown derivatives of the formation reference to further construct the limited-information-based sliding mode controller. To ensure that the system is collision-free, artificial potential fields are introduced along with a time-varying topology. An example of a multiple omnidirectional robot system is used to conduct numerical simulations, and necessary comparisons are made to justify the effectiveness of the proposed limited-information-based control scheme.

In this paper, the problem of formation control is studied for second-order multi-agent systems with practical issues like mismatched uncertainties and obstacle avoidance. A reference correction algorithm based sliding mode control scheme is proposed to ensure the boundedness of each agent's position tracking error. Both disturbance observer and artificial potential field are implemented to first tackle the problem of obstacle avoidance with the existence of mismatched uncertainties. The unreachable reference scenarios are then defined to describe the passive correcting behaviours of the multi-agent system when agents are trying to avoid obstacles. A distributed reference correction algorithm is developed for each agent to attenuate the harmful effects of passive correcting behaviours. The effectiveness of obstacle avoidance and boundedness of position tracking error are both verified by Lyapunov stability theory. Finally, multi-robot system based numerical simulations and comparisons are conducted to demonstrate the effectiveness of the proposed algorithm and controller.

This paper considers the problem of achieving time-varying formation for second-order multi-agent systems with actuator hysteresis, unknown system dynamics and external disturbances. A novel adaptive dynamic sliding mode scheme is developed to control a group of agents to follow desired trajectories. First, a dynamic sliding mode approach based on local formation tracking error is utilised to reject external disturbances and obtain smooth and chattering-free control input. Then, Chebyshev neural network is employed to estimate the nonlinear function related to the system's dynamic equation. A smooth projection law is also applied to regulate the output of the neural network. Moreover, a Bouc–Wen hysteresis compensator has been added to the current control law to offset the known actuator hysteresis effect. Finally, a numerical simulation based on a multiple omni-directional robot system is presented to illustrate the performance of the proposed control law.

The challenging problem of robust formation control pertaining to omnidirectional robots with model uncertainty and actuator saturation is comprehensively investigated in this article. First, an observer-based formation controller is designed to ensure the semiglobal uniform ultimate boundedness of the system's formation tracking error. Then, both global stability and practical finite-time stability are achieved to ascertain the practicality of the observer design. Apart from restricting the control input amplitude, we also investigate the reverse effect caused by saturated and coupled control input. As such, an adaptive compensator is formulated to attenuate the state oscillation caused by the reverse effect. Both numerical simulations and hardware-in-the-loop experiments are carried out to illustrate and evaluate the effectiveness and potentials of the proposed new techniques for real-world applications.

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.