摘要: In previous chapters we assumed that the state variables of system are known with certainty. When outcomes a random phenomenon, is modeled as stochastic process. Specifically, now face optimal control problem where represented by controlled We shall only consider case when equation perturbed Wiener process, which gives rise to Markov diffusion Appendix D.2 have defined also Brownian motion. Sect. 12.1, will formulate governed differential equations involving Ito equations. Our goal be synthesize feedback controls for systems subject in way maximizes expected value given objective function.
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