ABSTRACT
This chapter discusses state-space methods of analysis and design for a broad range of dynamic systems. It introduces the role of the transfer function, the different state-space canonical forms, and the state-transition matrix. The chapter discusses the theoretical basics and design issues involved in the state-space subjects of observability, controllability, similarity transformation, full-state feedback, optimal control, estimator design, and compensator design. It also provides a number of design examples including discussions about their implementation in MATLAB. Further advantages of state space methods include the ability to study more general models, facilitating the use of ideas of geometry in differential equations, providing connections between internal and external descriptions, the ability to handle multi-input multi-output (MIMO) systems, and easy implementation using software such as MATLAB. The state-space description of a system can be expressed using another variable without losing the system input-output relationship.
