Improved dissipativity-based sampled-data control synthesis of nonhomogeneous Markovian jump fuzzy systems against mismatched fuzzy-basis functions

This study obtains less conservative conditions for dissipativity-based sampled-data control synthesis of Markovian jump fuzzy systems against mismatched fuzzy-basis functions and incomplete transition rates. To this end, a new time-integrated state is introduced into the augmented vector that constitutes the Lyapunov–Krasovskii functional, and an additional discontinuous function is included in the Lyapunov–Krasovskii functional. Furthermore, to deal with the dissipativity-based stabilization conditions formulated in terms of multi-parameterized matrix inequalities, this study proposes more advanced relaxation techniques for mismatched fuzzy-basis functions and transition rates by taking advantage of their stringent constraints and structural features. Finally, four numerical examples were provided to demonstrate the validity and practicality of the proposed method.