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A control design scheme combining iterative learning and adaptive control is proposed to perform parameter adaptive time\u2010varying adjustment and prove the effectiveness of the control protocol by designing Lyapunov functions. Simulation results show that the high\u2010precision tracking control problem of the nonlinear multiagent system based on adaptive iterative learning control can be well realized even when the input is saturated. 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