@inbook{12fa414b65db4e21a682ae1cb9724319,

title = "4 Continuous-time systems: Tracking control",

abstract = "In this chapter we treat the problem of H∞ tracking with stochastic multiplicative white noise. We extend the work of [98], which does not involve stochastic uncertainties, to the case where there are stochastic white noise parameter uncertainties in the matrices of the state-space model that describes the system. We treat the case where correlated parameter uncertainties appear in both the system dynamics and the input matrices for the state-feedback case, and in both, the input and the measurement matrices in the outputfeedback case. An optimal finite-horizon state-feedback tracking strategy is derived which minimizes the expected value of the standard H∞ performance index with respect to the unknown parameters and which applies game theoretic considerations. The solution of the latter problem and the stationary state-feedback case, appear in Section 4.3. In Section 4.4 we solve the outputfeedback control problem where we allow for a state-multiplicative noise in the measurement matrix. We first introduce in Section 4.4.1 an auxiliary stochastic BRL for systems that contain, in addition to the standard stochastic continuous-time BRL [10], a reference signal in the system dynamics. The BRL is solved as a max-min problem and results in a modified Riccati equation. controller.",

author = "Eli Gershon and Uri Shaked and Isaac Yaesh",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag London Limited 2005.",

year = "2005",

month = sep,

day = "21",

doi = "10.1007/11351429_4",

language = "אנגלית",

isbn = "1852339977",

series = "Lecture Notes in Control and Information Sciences",

publisher = "Springer Verlag",

pages = "55--73",

booktitle = "H-Control and Estimation of State-multiplicative Linear Systems",

}