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We return to the discrete-time systems and models. This Chapter deals with a special version of dynamic optimization, namely, Dynamic Programming. The structure of the Chapter is as follows. Sections 7.1 and 7.2 outline the deterministic and stochastic principle of optimality, respectively. The remaining Sections consider the so-called Linear-Quadratic-Gaussian, LQG control problems. Section 7.3 is devoted to the case of full information: LQ control. Section 7.4* refers verbally to the optimal state-estimation and control of the stochastically disturbed systems, the so-called Kalman-filter. Dynamic Programming is discussed in much detail by Sargent (1987) and in particular, Stokey and Lucas (1989). A good monograph on optimal LQG control is Bryson and Ho (1969). Our treatment is based on the last two sources.
KeywordsDynamic Programming Loss Function Return Function Optimal Feedback Reference Path
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