Multivariable Computer-controlled Systems : A Transfer Function Approach /
By: Rosenwasser, Efim N [author.].
Contributor(s): Lampe, Bernhard P [author.] | SpringerLink (Online service).
Material type:![materialTypeLabel](/opac-tmpl/lib/famfamfam/BK.png)
Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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PK Kelkar Library, IIT Kanpur | Available | EBK8955 |
Algebraic Preliminaries -- Polynomial Matrices -- Fractional Rational Matrices -- Normal Rational Matrices -- General MIMO Control Problems -- Assignment of Eigenvalues and Eigenstructures by Polynomial Methods -- Fundamentals for Control of Causal Discrete-time LTI Processes -- Frequency Methods for MIMO SD Systems -- Parametric Discrete-time Models of Continuous-time Multivariable Processes -- Mathematical Description, Stability and Stabilisation of the Standard Sampled-data System in Continuous Time -- Analysis and Synthesis of SD Systems Under Stochastic Excitation -- H2 Optimisation of a Single-loop Multivariable SD System -- -Design of SD Systems for 0 < t < ?.
The transfer function approach is widely used in classical control theory for its easy handling and physical meaning. Although the use of transfer functions is well-established for linear time-invariant systems, it is not suitable for non-stationary systems among which are sampled-data systems and processes with periodically varying coefficients. Computer-controlled continuous-time processes are a very important subset of periodic sampled-data systems which are not treatable using ordinary transfer functions. Having established the ability of the parametric transfer function to solve this problem for single-input, single-output systems in previous work, the authors extend these methods, which incorporate time-dependence, to the idea of the parametric transfer matrix in a complete exposition of analysis and design methods for multiple-input, multiple-output (MIMO) sampled-data systems. Multivariable Computer-controlled Systems is divided into three parts: • Preliminary algebraic material describing the established fundamentals of polynomial and rational matrices necessary for the understanding of later chapters. • Control problems, important in their own right but which also have a substantial bearing on what follows (eigenvalue assignment and the use of z- and zeta-transforms in discrete systems). • Frequency methods for the investigation of MIMO sampled-data systems (parametric discrete-time models; stability; stochastic methods; H2 optimization and L2 design). Appendices covering basic mathematical formulae and the description of two MATLAB® toolboxes round out this self-contained guide to multivariable control systems. Of special interest to researchers in automatic control and to development engineers working with advanced control technology, Multivariable Computer-controlled Systems will also interest mathematical control theorists and graduate students studying advanced methods of computer-based control.
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