The brief introduction stresses that in multiple input multiple output (MIMO), several variables simultaneously must be maintained each at an independent set point through the adjustment of several manipulated variables. Nonlinear MIMO systems are approximated by linear models either as state-space models in time domain or by transfer function matrices in frequency domain. If a multivariable linear time-invariant (LTI) system is acceptable, essential methods and results such as the well-known Nyquist stability criterion learned from single-variable system analysis can be applied with some adaption. Chapter 1 introduces some notations. Throughout this book, it is shown how the free open-source mathematical software GNU Octave may be applied in the use of theoretical results and for the solutions of the problems at the end of each chapter.

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Introduction

  • Wolfgang Borutzky

摘要

The brief introduction stresses that in multiple input multiple output (MIMO), several variables simultaneously must be maintained each at an independent set point through the adjustment of several manipulated variables. Nonlinear MIMO systems are approximated by linear models either as state-space models in time domain or by transfer function matrices in frequency domain. If a multivariable linear time-invariant (LTI) system is acceptable, essential methods and results such as the well-known Nyquist stability criterion learned from single-variable system analysis can be applied with some adaption. Chapter 1 introduces some notations. Throughout this book, it is shown how the free open-source mathematical software GNU Octave may be applied in the use of theoretical results and for the solutions of the problems at the end of each chapter.