Certain nonlinear partially observable stochastic optimal control problems with explicit control laws equivalent to LEQG/LQG problems
AuthorCharalambous, Charalambos D.
Elliott, R. J.
SourceIEEE Transactions on Automatic Control
Google Scholar check
MetadataShow full item record
This paper is concerned with partially observed stochastic optimal control problems when nonlinearities enter the dynamics of the unobservable state and the observations as gradients of potential functions. Explicit representations for the information state are derived in terms of a finite number of sufficient statistics. Consequently, the partially observed problem is recast as one of complete information with a new state generated by a modified version of the Kalman filter. When the terminal cost is quadratic in the unobservable state and includes the integral of the nonlinearities, the optimal control laws are explicitly computed, similar to linear-exponential-quadratic-Gaussian and linear-quadratic-Gaussian tracking problems. The results are applicable to filtering and control of Hamiltonian systems.
Showing items related by title, author, creator and subject.
Baldi, S.; Ioannou, Petros A.; Kosmatopoulos, E. B. (2012)A recently developed control scheme for approximately optimal control of nonlinear systems is the so-called Convex Control Design (ConvCD) methodology, that transforms the control problem of generic nonlinear systems into ...
Kuipers, M.; Ioannou, Petros A. (2010)Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems where strict performance and robustness guarantees ...
Baldi, S.; Michailidis, I.; Kosmatopoulos, E. B.; Papachristodoulou, A.; Ioannou, Petros A. (2014)This paper describes a new control scheme for approximately optimal control (AOC) of nonlinear systems, convex control design (ConvCD). The key idea of ConvCD is to transform the approximate optimal control problem into a ...