Dissipativity theory and applications of nonlinear stochastic systems with Markov jump and Lévy noise
DOI10.1016/j.cnsns.2021.105796zbMath1481.60170OpenAlexW3135752893WikidataQ112880679 ScholiaQ112880679MaRDI QIDQ2025524
Ze-Hao Wu, Mengling Li, Fei Qi Deng, Zheng-Yong Ouyang
Publication date: 14 May 2021
Published in: Communications in Nonlinear Science and Numerical Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cnsns.2021.105796
Lévy noiseMarkov jumpLasalle-type stabilitystochastic dissipativitystochastic feedback passivitystochastic KYP conditions
Continuous-time Markov processes on discrete state spaces (60J27) Jump processes on general state spaces (60J76)
Related Items (2)
Cites Work
- Dissipative dynamical systems: basic input-output and state properties
- Stability results for nonlinear feedback systems
- Exponential stability and extended dissipativity criteria for generalized discrete-time neural networks with additive time-varying delays
- Almost sure stability with general decay rate of neutral stochastic delayed hybrid systems with Lévy noise
- Dissipative dynamical systems. I: General theory
- Dissipative dynamical systems. II: Linear systems with quadratic supply rates
- The stability of nonlinear dissipative systems
- Dissipativity Theory for Switched Systems
- Dissipative hamiltonian realization and energy-based L/sub 2/-disturbance attenuation control of multimachine power systems
- Dissipativity Theory for Nonlinear Stochastic Dynamical Systems
- Razumikhin-type theorem for stochastic functional differential equations with Lévy noise and Markov switching
- Dissipativity-Based Sliding Mode Control of Switched Stochastic Systems
- Passivity Based Control of Stochastic Port-Hamiltonian Systems
- Stochastic Differential Equations with Markovian Switching
- Robust extended dissipative control for sampled-data Markov jump systems
- Dissipative systems analysis and control. Theory and applications
This page was built for publication: Dissipativity theory and applications of nonlinear stochastic systems with Markov jump and Lévy noise