System Entropy Measurement of Stochastic Partial Differential Systems

摘要: System entropy describes the dispersal of a system’s energy and is an indication disorder physical system. Several system measurement methods have been developed for dynamic systems. However, most real systems are always modeled using stochastic partial differential equations in spatio-temporal domain. No efficient method currently exists that can calculate (SPDSs) consideration effects intrinsic random fluctuation compartment diffusion. In this study, novel indirect proposed calculating SPDSs Hamilton–Jacobi integral inequality (HJII)-constrained optimization method. other words, we solve nonlinear HJII-constrained problem measuring (NSPDSs). To simplify NSPDSs, global linearization technique finite difference scheme were employed to approximate spatial state space This allows be transformed equivalent linear matrix inequalities (LMIs)-constrained problem, which easily solved MATLAB LMI-toolbox (MATLAB R2014a, version 8.3). Finally, several examples presented illustrate SPDSs.