2020Unpublished venueRequires access

State Space Approach

T. Thyagarajan, D. Kalpana

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Abstract

This chapter on ‘State Space Approach’ presents the details of topics namely: Role of eigen values and eigen vectors, free response or unforced response or homogeneous state equations, state transition matrix and its properties, forced response or non-homogeneous state equation, pictorial representation of state model using state diagram, minimal realization, non-minimal realization and balanced realization. The eigen values and eigen vectors determine the dynamic response of the given system. The eigen values also turn out to be the poles of the system transfer function. The procedures for obtaining the homogeneous and non-homogeneous state equations are illustrated with numerical examples. Manipulating the given state models into minimal and non-minimal realization forms is also presented. Balanced realization which plays a major role in model reduction is also illustrated with a numerical example.

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What this paper is about

This chapter on ‘State Space Approach’ presents the details of topics namely: Role of eigen values and eigen vectors, free response or unforced response or homogeneous state equations, state transition matrix and its properties, forced response or non-homogeneous state equation, pictorial representation of state model using state diagram, minimal realization, non-minimal realization and balanced realization. The eigen values and eigen vectors determine the dynamic response of the given system. The eigen values also turn out to be the poles of the system transfer function. The procedures for obtaining the homogeneous and non-homogeneous state equations are illustrated with numerical examples. Manipulating the given state models into minimal and non-minimal realization forms is also presented. Balanced realization which plays a major role in model reduction is also illustrated with a numerical example.

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Available abstract

This chapter on ‘State Space Approach’ presents the details of topics namely: Role of eigen values and eigen vectors, free response or unforced response or homogeneous state equations, state transition matrix and its properties, forced response or non-homogeneous state equation, pictorial representation of state model using state diagram, minimal realization, non-minimal realization and balanced realization. The eigen values and eigen vectors determine the dynamic response of the given system. The eigen values also turn out to be the poles of the system transfer function. The procedures for obtaining the homogeneous and non-homogeneous state equations are illustrated with numerical examples. Manipulating the given state models into minimal and non-minimal realization forms is also presented. Balanced realization which plays a major role in model reduction is also illustrated with a numerical example.

Key concepts: Computer science, State space, State (computer science), Space (punctuation), Mathematics, Programming language, Operating system, Statistics

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