𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A two level prediction algorithm for non-linear systems

✍ Scribed by Madan G. Singh; Mohammed Hassan


Publisher
Elsevier Science
Year
1977
Tongue
English
Weight
132 KB
Volume
13
Category
Article
ISSN
0005-1098

No coin nor oath required. For personal study only.

✦ Synopsis


In this note the recent algorithm of Hassan and Singh is modified to provide a more powerful approach to the hierarchical optimisation of non-linear systems with quadratic performance indices. The new approach does not use the quadratic penalty terms in the cost function. This allows convergence over a longer time horizon and numerical studies on the synchronous machine example of Hassan and Singh show that the modified algorithm also provides faster convergence.

CONSIDER the non-linear system described by * = f(x, u, t) (I)


πŸ“œ SIMILAR VOLUMES


The optimization of non-linear systems u
✍ Mohamed Hassan; Madan G. Singh πŸ“‚ Article πŸ“… 1976 πŸ› Elsevier Science 🌐 English βš– 362 KB

A new two level method is developed for the optimization of non-linear dynamical systems with a quadratic cost function. This method used an expansion around the equilibrium point of the system to fix the second and higher order terms. These terms are compensated for iteratively at the second level

Comments on: β€œOptimisation of non-linear
✍ FΓ©lix Mora-Camino πŸ“‚ Article πŸ“… 1979 πŸ› Elsevier Science 🌐 English βš– 178 KB

Recent papers by M. G. Singh and M. F. Hassan describe a new multi-level (two or three) method to solve nonlinear optimisation problems and its application to the stabilisation of a synchronous machine. The author in this article makes several comments about a paper which appeared in Automatica rece

Non-stationary parallel multisplitting a
✍ Josep Arnal; Violeta MigallΓ³n; JosΓ© PenadΓ©s πŸ“‚ Article πŸ“… 1999 πŸ› John Wiley and Sons 🌐 English βš– 100 KB

Non-stationary parallel multisplitting iterative methods are introduced for the solution of almost linear systems. A non-stationary parallel algorithm based on the AOR-type methods and its extension to asynchronous models are considered. Convergence properties of the synchronous and asynchronous ver