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Design of Reset Control Systems

  • Alfonso BañosEmail author
  • Antonio Barreiro
Part of the Advances in Industrial Control book series (AIC)

Abstract

Reset compensation has been used to overcome limitations of LTI compensation. In this chapter, a new reset compensator, referred to as PI + CI, is introduced. It basically consists of adding a Clegg integrator to a PI compensator with the goal of improving the closed-loop response by using the nonlinear characteristic of this element. It turns out that by resetting a percentage of the integral term in a PI compensator, a significant improvement can be obtained over a well-tuned PI compensator in some relevant practical cases, such as systems with dominant lag and integrating systems. The main goal is the development of PI + CI tuning rules for basic dynamic systems in a wide range of applications, including first and higher order plus deadtime systems. In addition, a number of design improvements such as the use of a fixed or variable reset band, the integration with QFT, and the use of a variable reset percentage are discussed. This chapter is based on the publications (Baños and Vidal in Proc. European Control Conference, Kos, Greece, 2007; Baños and Vidal in Proc. IEEE International Symposium on Industrial Electronic, Vigo, Spain, 2007; Fernández et al. in IEEE Trans. Ind. Electron., 2010, doi: 10.1109/TIE.2010.2077610; Vidal et al. in 34th Annual Conference of the IEEE Industrial Electronics Society, Orlando, Florida, USA, 2008; Vidal and Baños in 16th IEEE Mediterranean Conference on Control and Automation, Ajaccio, France, 2008; Vidal and Baños in European Control Conference, Budapest, Hungary, 2009; Vidal and Baños in 14th IEEE International Conference on Emerging Technologies and Factory Automation, Mallorca, Spain, 2009).

Keywords

Internal Model Control Proportional Gain Quantitative Feedback Theory Tuning Rule Base Compensator 
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.

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Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  1. 1.Fac. Informática, Depto. Informática y Sistemas, Grupo de Informática IndustrialUniversidad de MurciaMurciaSpain
  2. 2.Depto. Ingeniería de Sistemas y Automática, ETSIIUniversidad de VigoVigoSpain

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