Robust $H_{2}/H_\infty$ Model Predictive Control for Linear Systems With Polytopic Uncertainties Under Weighted MEF-TOD Protocol
This paper is concerned with the robust <inline-formula> <tex-math notation="LaTeX">${H_{2}/H_\infty }$ </tex-math></inline-formula> model predictive control problem for a class of linear systems with polytopic uncertainties under weighted maximum-error-first and try-once-discard (MEF-TOD) protocol. To prevent data from collision, the weighted MEF-TOD protocol is employed during the data transmission from sensors to controller, where only one sensor is allowed to transmit the measurement at every time instant. A switched linear system is established with respect to the switching signals generated by the adopted weighted MEF-TOD protocol. By taking the influence of the exogenous disturbance and the weighted MEF-TOD protocol into consideration, an online optimization problem with nonconvex conditions is formulated. Then, to deal with the couplings of unknown variables, singular value decomposition technique is utilized to transform the nonconvex conditions into solvable ones. Subsequently, a set of dynamic output-feedback controllers is designed to guarantee the stability of the closed-loop system with guaranteed robust <inline-formula> <tex-math notation="LaTeX">${H_{2}/H_\infty }$ </tex-math></inline-formula> performance. Finally, a direct current motor example is used to illustrate the validity and effectiveness of the proposed methods.