Abstract. This paper investigates the formation control problem of multiple agents. The formation control is founded on leader-following approaches. The method of integral sliding mode control is adopted to achieve formation maneuvers of the agents based on the concept of graph theory. Since the agents are subject to uncertainties, the uncertainties also challenge the formation-control design. Under a mild assumption that the uncertainties have an unknown bound, the technique of nonlinear disturbance observer is utilized to tackle the issue. According to a given communication topology, formation stability conditions are investigated by the observer-based integral sliding mode formation control. From the perspective of Lyapunov, not only is the formation stability guaranteed, but the desired formation of the agents is also realized. Finally, some simulation results are presented to show the feasibility and validity of the proposed control scheme through a multi-agent platform.Key words: multi-agent system, formation control, integral sliding mode control, uncertainty, nonlinear disturbance observer, stability.Observer-based leader-following formation control of uncertain multiple agents by integral sliding mode ysis and design of multiple agent systems. However, the classic leader-following scheme is centralized, meaning that the control systems in [4,6,9,10] heavily depend on the leader and suffer from the "single point of failure'' problem. With the development of communication technology, it is desired to consider the communication topology in the scheme because the adaptability and practicability of multiple agents can be strengthened [15,16].The leader-following scheme gains popularity in multi-agent formations because its dynamics are experimentally modelled, but the internal formation stability can be theoretically guaranteed. Adopting such a scheme, various control methods have been developed for multi-agent formations, that is, robust control [17], dynamic output feedback method [18], adaptive fuzzy approach [19], multi-step predictive mechanism [20], iterative learning technique [21], and neural network-based adaptive design [22], to name but a few. A systematic review on this topic is presented by Oh, Park and Ahn [23].As a nonlinear feedback design tool, the sliding mode control (SMC) technique is popular because of its invariance [24], meaning that matched uncertainties in an SMC system can be suppressed by the invariance. Some SMC-based methods have been addressed to solve the formation-control problem of multi-agent systems, that is, first-order SMC [25,26] [15,[25][26][27][28] have verified the feasibility of the SMC methodology for multi-agent formations.Compared to other SMC methods, the integral SMC design can guarantee an integral SMC system against matched uncertainties from the initial time, indicating that an entire response of the system is of invariance. Some successful applications of the integral SMC method have been reported in industries, for example, power systems [29], hypersonic ve...