Linear and Nonlinear Non-minimal State Space Control System Design


This tutorial chapter uses case studies based on recent engineering applications, to re-examine the non-minimal, state variable feedback approach to control system design. We show how the non-minimal state space (NMSS) representation seems to be the natural description of a discrete-time Transfer Function, since its dimension is dictated by the complete structure of the model. This is in contrast to minimal state space descriptions, which only account for the order of the denominator and whose state variables, therefore, usually represent combinations of input and output signals. The resulting control algorithm can be interpreted as a logical extension of the conventional Proportional-Integral (PI) controller, facilitating its straightforward implementation using a standard hardware-software arrangement. Finally, the basic NMSS approach is readily extended into multivariable, model-predictive and nonlinear control systems, hence the chapter briefly discusses these areas and gives pointers to the latest research results.


Model Predictive Control Control System Design Transfer Function Model Pole Assignment Model Mismatch 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors welcome this opportunity to contribute to a book in honour of Professor Peter Young. We have particular reason to celebrate Peter’s friendship, ideas and advice over many years. We are also grateful to Essam Shaban [28] and Philip Cross.


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Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  1. 1.Engineering DepartmentLancaster UniversityLancasterUK
  2. 2.Lancaster Environment CentreLancaster UniversityLancasterUK

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