Engineering topics
Publications and source records attributed to Krener, A. J..
Acausal linear systems are studied as well as their controllability and observability properties, and the weighting patterns that they realize. A complete classification is given of all minimal real analytic realizations of a given weighting pattern and of all minimal autonomous realizations of a stationary weighting pattern.
Over the past decade, it has been found that concepts from differential topology such as foliation and invariant distribution play a crucial role in the study of nonlinear systems. These concepts were first employed in studies of nonlinear controllability and observability. More recently, they have occurred in the study of decoupling and linearization via feedback. In connection with the widening area of application, requirements for a greater precision have arisen. The present paper represents an attempt to provide that precision. In this paper, an introduction is given of the basic concepts which are needed for an understanding of controllability, observability, and decoupling of nonlinear systems. Attention is given to mathematical preliminaries, aspects of invariance, nonlinear controllability and observability, disturbance decoupling, and controllability distributions.
A new method for designing asymptotic observers for a class of nonlinear systems is presented. The error between the state of the systems and the state of the observer in appropriate coordinates evolves linearly and can be made to decay aribtrarily exponentially fast.
It is argued that if the nonlinearities in a system are mild, and the controller is sufficiently stabilizing, the inaccuracies of a linear model, which is often taken to be sufficient for a controller design, can be safely neglected. For systems with severe nonlinearity a linearizing technique is described, based on the change of state coordinates and nonlinear feedback; in the total context of a stable feedback design the linearization technique is considered robust. Furthermore, attention is paid to partial linearization using the same transformations. It is found that there always exist maximally linearizing transformations which are not necessarily unique.