Olama, AlirezaAlirezaOlamaShasadeghi, MokhtarMokhtarShasadeghiRamezani, AminAminRamezaniKhorramizadeh, MostafaMostafaKhorramizadehCosta Mendes, Paulo Renato daPaulo Renato daCosta Mendes2023-08-212023-08-212018https://publica.fraunhofer.de/handle/publica/44842610.1177/0142331218801126This paper proposes an ellipsoidal hybrid model predictive control approach to solve the robust stability problem of uncertain hybrid dynamical systems modelled by the mixed logical dynamical framework. In this approach, the traditional terminal equality constraint is replaced by an ellipsoid that results in a maximal positive invariant set for the closed-loop system. Then, a Lyapunov decreasing condition along with the robustness criterion is introduced to the optimization problem to achieve the robust stability of the closed-loop system. As the main advantages, the ellipsoidal terminal set proposed in this paper attains a larger domain of attraction along with the recursive feasibility guarantee. Moreover, the stability and robustness constraints are achieved by a lower prediction horizon, which leads to a smaller dimension optimization problem. In addition, to reduce the computational complexity of the corresponding optimization problem, a suboptimal version of the proposed algorithm is introduced. Finally, numerical and car suspension system examples show the capabilities of the proposed method.enMaximal positive invariant setmixed logical dynamical systemsmodel predictive controlrecursive feasibilityDDC::500 Naturwissenschaften und Mathematikjournal article