Gain-scheduled control of a system with input constraint by suppression of input derivatives

Hidekazu Nishimura, Kiyoshi Takagi, Kohei Yamamoto

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)

Abstract

The purpose of this study is to design a gain-scheduled feedback compensator for a system constrained on the input. Description of the input saturation by the hyperbolic tangential function transfers the system description to a form of a linear parameter-dependent system. This formulation allows applying the gain-scheduling control synthesis via linear matrix inequalities (LMI). In order to avoid the windup phenomena caused by input limitation suppression of the input derivatives is employed. While the input derivatives could not be taken into account in the previous studies because of using the discontinuous functions as the input limitations, in this study it is available to take account of the input derivatives in the controller design. This means that the designed controller includes integrators and constructs a type-one control system. Consideration of input derivatives may mitigate sudden change of the input even if there is no feedback loop of error between input and output of the nonlinear function. Simulation results show usefulness of the proposed design method.

Original languageEnglish
Pages1698-1703
Number of pages6
Publication statusPublished - 1999 Dec 1
Externally publishedYes
EventProceedings of the 1999 IEEE International Conference on Control Applications (CCA) and IEEE International Symposium on Computer Aided Control System Design (CACSD) - Kohala Coast, HI, USA
Duration: 1999 Aug 221999 Aug 27

Other

OtherProceedings of the 1999 IEEE International Conference on Control Applications (CCA) and IEEE International Symposium on Computer Aided Control System Design (CACSD)
CityKohala Coast, HI, USA
Period99/8/2299/8/27

ASJC Scopus subject areas

  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Gain-scheduled control of a system with input constraint by suppression of input derivatives'. Together they form a unique fingerprint.

Cite this