In this paper we consider continuous-time unconstrained optimal control problems. We propose a computational method which is essentially based on the closed-loop solutions of the linear quadratic optimal control problems. In the proposed algorithm, Riccati differential equations play an important ro
Optimization algorithms for bilinear model–based predictive control problems
✍ Scribed by H. H. J. Bloemen; T. J. J. van den Boom; H. B. Verbruggen
- Publisher
- American Institute of Chemical Engineers
- Year
- 2004
- Tongue
- English
- Weight
- 137 KB
- Volume
- 50
- Category
- Article
- ISSN
- 0001-1541
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
## Abstract Laguerre Functional Model has many advantages such as good approximation capability for the variances of system time‐delay, order and other structural parameters, low computational complexity, and the facility of online parameter identification, etc., so this model is suitable for compl
Optimization neural networks have been studied and applied in the literature, and the mechanism of such neural networks has been investigated from the point of view of optimization theory. Yet, no studies have been found by the authors to investigate the mechanism from a control systems' perspective
In solving optimal control problems, the conventional dynamic programming method often requires interpolations to determine the optimal control law. As a consequence, interpolation errors often degenerate the accuracy of the conventional dynamic programming method. In view of this problem, this pape