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Controlled diffusion processes with markovian switchings for modeling dynamical engineering systems

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  • Cañada, Héctor
  • Romera, Rosario

Abstract

A modeling approach to treat noisy engineering systems is presented. We deal with controlled systems that evolve in a continuous-time over finite time intervals, but also in continuous interaction with environments of intrinsic variability. We face the complexity of these systems by introducing a methodology based on Stochastic Differential Equations (SDE) models. We focus on specific type of complexity derived from unpredictable abrupt and/or structural changes. In this paper an approach based on controlled Stochastic Differential Equations with Markovian Switchings (SDEMS) is proposed. Technical conditions for the existence and uniqueness of the solution of these models are provided. We treat with nonlinear SDEMS that does not have closed solutions. Then, a numerical approximation to the exact solution based on the Euler- Maruyama Method (EM) is proposed. Convergence in strong sense and stability are provided. Promising applications for selected industrial biochemical systems are showed.

Suggested Citation

  • Cañada, Héctor & Romera, Rosario, 2009. "Controlled diffusion processes with markovian switchings for modeling dynamical engineering systems," DES - Working Papers. Statistics and Econometrics. WS ws093714, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Handle: RePEc:cte:wsrepe:ws093714
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    References listed on IDEAS

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    1. O. L. V. Costa & E. K. Boukas, 1998. "Necessary and Sufficient Condition for Robust Stability and Stabilizability of Continuous-Time Linear Systems with Markovian Jumps," Journal of Optimization Theory and Applications, Springer, vol. 99(2), pages 359-379, November.
    2. Yuan, Chenggui & Mao, Xuerong, 2004. "Convergence of the Euler–Maruyama method for stochastic differential equations with Markovian switching," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(2), pages 223-235.
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    markov chains;

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