Abstract
In this work, we develop the constrained model predictive control for nonlinear networked control systems in the presence of parameter uncertainties and random packet loss over the communication link. The interval type-2 (IT2) Takagi–Sugeno fuzzy model is introduced to represent the nonlinear plant because of its intrinsic capability of dealing with high levels of uncertainty. Meanwhile, a time homogenous Markov process with know transition probabilities is utilized to model the data transmission status in the controller to actuator link. An IT2 fuzzy predictive controller is designed by minimizing an upper bound on the expected quadratic performance objective function over the infinite horizon at each sampling time such that the resulting closed-loop IT2 fuzzy system is asymptotically mean-square stable. Stochastic expectation invariant set guarantees the feasibility and stochastic stability of the provided algorithm. Simulation example is provided to illustrate the effectiveness of the developed method.
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Acknowledgements
This work is supported by the High real-time WIA-PA network system-on-chip (SoC) development and demonstration applications (2015ZX03003011), National Natural Science Foundation of China (61403055), the Research Project of Chongqing Science & Technology Commission (cstc2014jcyjA40005).
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Xie, H., Wang, J. & Tang, X. Constrained Model Predictive Control of Interval Type-2 T–S Fuzzy Systems with Markovian Packet Loss. J Control Autom Electr Syst 28, 323–336 (2017). https://doi.org/10.1007/s40313-017-0310-6
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DOI: https://doi.org/10.1007/s40313-017-0310-6