Abstract
This paper is concerned with the event-triggered output feedback robust model predictive control (RMPC) for time-varying discrete-time systems via networks with data quantization, packet loss and bounded disturbance. An observer-based event-triggered scheme is introduced according to the error between the estimated state at the current time and the latest event-triggered state. The overall designed controller consists of two components, a state observer which is offline designed by using the notion of robust positively invariant (RPI) set, and an online RMPC optimization problem which minimizes the upper bound of the expect value of the infinite horizon performance cost based on the obtained estimated state. Applying the S-procedure and the sufficient conditions of RPI sets, a constraint tightening method of estimated error bound is utilized to ensure the recursive feasibility of RMPC optimization problem. An example is performed to illustrate the availability of the developed technique.
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Funding
We acknowledge funding received from the Key Research Program of the Science Foundation of Shandong Province (ZR2020KE001); This is also a publication of the Enroll Plan of Young Innovative Talents of Shandong Province (Big Data and Ecological Security Research and Innovation Team Project).
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The author declares that there is no conflict of interest.
Hongchun Qu received his Ph.D. degree from Iowa State University in 2009. He is currently a Professor at the College of Information Science and Eengineering, Zaozhuang University. His research interest covers model predictive control, computer modeling and simulation, predictive modeling as well as bigdata.
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Qu, H. An Event-triggered Output Feedback Robust MPC Scheme for Time-varying System with Packet Loss and Bounded Disturbance. Int. J. Control Autom. Syst. 20, 1087–1098 (2022). https://doi.org/10.1007/s12555-020-0860-4
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DOI: https://doi.org/10.1007/s12555-020-0860-4