This paper addresses the stability of a newly-developed control strategy for networked control systems (NCS). This control strategy hones the potential of constrained model predictive control (MPC) by buffering the predicted control sequence at the actuator in anticipation of typical data transmission errors associated with NCS. Closed-loop stability in the sense of Lyapunov is guaranteed for the controller in the linear case, by bounding the projected receding horizon costs by lower-and upper-bounding terms using a predetermined terminal cost. A stability theorem is developed, which provides a suboptimal measure for the controller in real time, and is sufficient to estimate the worst-case transmission delay that can be handled by the developed control buffering strategy. The stability conditions, as governed by the theorem, are validated through real-time implementation on an electro-hydraulic servo system of an industrial processing machine, through an Ethernet network.

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This paper focuses on the stability and optimality of a novel control strategy for Networked Control Systems (NCS). The developed control strategy hones the potential of constrained Model Predictive Control (MPC) by buffering the predicted control sequence at the actuator in anticipation of the occurrence of typical data transmission errors associated with NCS. Global closed-loop stability in the sense of Lyapunov is guaranteed by bounding the projected receding horizon costs by lower-and upper-bounding terms using a predetermined terminal cost. The developed stability theorem, although suboptimal in real-time, is a sufficient measure to estimate the worst-case transmission delay that can be handled by the developed control buffering strategy.

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