Application of grey wolf optimization in fuzzy controller tuning for servo systems

Application of grey wolf optimization in fuzzy controller tuning for servo systems

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This chapter presents aspects concerning the tuning of fuzzy controllers (FCs) by grey wolf optimization (GWO) algorithms with focus on cost-effective Takagi-Sugeno proportional-integral fuzzy controllers (T-S PI-FCs). GWO is one of the latest swarm intelligence algorithms, which has been developed by mimicking grey wolf social hierarchy and hunting habits. T-S PI-FCs are applied to servo systems, represented as non-linear processes characterized by second-order dynamics with an integral component, variable parameters, a saturation and dead-zone static non-linearity. The variable parameters of the processjustify the need to design fuzzy control systems with a reduced process parametric sensitivity. Four optimization problems are defined with this regard, with the tuning parameters ofT-S PI-FCs considered as vector variables and with objective functions that include the weighted output sensitivity function of the state sensitivity model with respect to process parametric variations. GWO is next employed in the minimization of these objective functions. Simulation and experimental results are given for a case study that deals with the optimal tuning of T-S PI-FCs for the angular position control of a laboratory non-linear servo system. The process gain is variable, and fuzzy control systems with a reduced process gain sensitivity are offered.

Chapter Contents:

  • Abstract
  • 13.1 Introduction
  • 13.2 Fuzzy controllers
  • 13.2.1 Fuzzy controller structure and design methodology
  • 13.2.2 Definition of optimization problems
  • 13.3 Optimal tuning of fuzzy controllers based on GWO with non-linear servo system applications
  • 13.3.1 General presentation of GWO
  • 13.3.2 GWO-based optimal tuning methodology
  • 13.4 Laboratory servo system-based application
  • 13.4.1 Real-time experimental results
  • 13.4.2 The performance indices
  • 13.5 Conclusion and outlook
  • Acknowledgements
  • References

Inspec keywords: position control; nonlinear control systems; grey systems; fuzzy control; PI control; optimisation; servomechanisms; control system synthesis; sensitivity

Other keywords: grey wolf social hierarchy; controller design; GWO; grey wolf optimization algorithms; hunting habits; angular position control; fuzzy controller tuning; swarm intelligence algorithms; Takagi-Sugeno proportional-integral fuzzy controllers; T-S PI-FCs; weighted output sensitivity function; laboratory nonlinear servo system; optimal tuning

Subjects: Fuzzy control; Optimisation techniques; Control system analysis and synthesis methods; Actuating and final control devices; Nonlinear control systems; Combinatorial mathematics

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