This paper is concerned with the design of networked control systems using the modified generalized predictive control (M-GPC) method. Both sensor-to-controller (S-C) and controller-to-actuator (C-A) network-induced delays are modeled by two Markov chains. M-GPC uses the available output and prediction control information at the controller node to obtain the future control sequences. Different from the conventional generalized predictive control in which only the first element in control sequences is used, M-GPC employs the whole control sequences to compensate for the time delays in S-C and C-A links. The closed-loop system is further formulated as a special jump linear system. The sufficient and necessary condition to guarantee the stochastic stability is derived. Simulation studies and experimental tests for an experimental hydraulic position control system are presented to verify the effectiveness of the proposed method.
Issue Section:
Research Papers
Keywords:
closed loop systems,
delay systems,
hydraulic control equipment,
hydraulic systems,
linear systems,
Markov processes,
networked control systems,
position control,
predictive control,
stability,
stochastic systems,
networked control systems (NCSs),
generalized predictive control (GPC),
time delays,
packet dropouts,
Markov chains,
stochastic stability
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