Premium
Gain optimization with non‐linear controls
Author(s) -
Slater G. L.,
Kandadai R. D.
Publication year - 1984
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.4660050303
Subject(s) - linearization , linear quadratic gaussian control , covariance , linear system , computation , quadratic equation , control theory (sociology) , function (biology) , linearity , mathematical optimization , mathematics , gaussian , computer science , analysis of covariance , linear dynamical system , nonlinear system , optimal control , algorithm , statistics , control (management) , engineering , mathematical analysis , physics , geometry , quantum mechanics , artificial intelligence , evolutionary biology , electrical engineering , biology
An algorithm has been developed for the analysis and design of controls for non‐linear systems. The technical approach is to use statistical linearization to model the non‐linear dynamics of a system by a quasi‐Gaussian model. A covariance analysis is performed to determine the behaviour of the dynamical system and a quadratic cost function. Expressions for the cost function and its derivatives are determined so that numerical optimization techniques can be applied to determine optimal feedback laws. The primary application for this paper is centred about the design of controls for nominally linear systems but where the controls are saturated or limited by fixed constraints. The analysis is general, however, and numerical computation requires only that the specific non‐linearity be considered in the analysis.