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This paper proposes a global cooperative control framework to address leader-follower consensus of constraints subsystems of industrial plants, in which each subsystem is modeled as an agent and all the subsystems and networks of information flow construct a multiagent system. The focus of this paper is to solve the global leader-follower consensus for multiagent systems with input saturation via low-high gain feedback approach and parametric algebraic Riccati equation approach, in which the feedback gain design is distributed and decoupled from network topologies. By introducing appropriate assumptions, a class of low-high gain feedback protocol is designed based on the states of local neighbors to reach the global stability. It is proved in the sense of Lyapunov that, if the dwell time is larger than a positive threshold, the global leader-follower consensus for the closed-loop linear multiagent systems with input saturation under the derived topology containing a directed spanning tree can be achieved. The results are further extended to leader-follower consensus for nonlinear multiagent systems with the design of nonlinear low-high gain feedback protocol. As industrial applications of the proposed low-high gain scheduling approaches, the controller design of vibration in mechanical systems and satellite formation systems are revisited. Numerical simulations with cooperative control of industries subsystems show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]