Modeling and Control in State Space

Dynamic systems are often modeled using transfer functions to characterize their input/output behavior. This type of modeling sometimes leads to the disappearance of information obtained during the physical modeling of the system, and can therefore be inappropriate. State representation is another, less compact modeling method, which saves all the information describing the internal evolution of the system. The aim of this course is therefore to present this representation, illustrating it with examples that will help you understand its advantages.
The course outline is as follows:
* Definition of the state of a system and the state representation of a system. * Different forms of state representation. * Properties of the transition matrix. * Notion of controllability and observability. * Determining an observer. * Control by state feedback.

Linear systems and linear control of systems. Basic matrix calculus.

Automatic

83-page handout