Local Model and Controller Network Design for a Single-Link Flexible Manipulator



This paper describes a new genetic learning approach to the construction of a local model network (LMN) and design of a local controller network (LCN) with application to a single-link flexible manipulator. A highly nonlinear flexible manipulator system is modelled using an LMN comprising Autoregressive–moving-average model with exogenous inputs (ARMAX) type local models (LMs) whereas linear Proportional-integral-derivative (PID) type local controllers (LCs) are used to design an LCN. In addition to allowing the simultaneous optimisation of the number of LMs and LCs, model parameters and interpolation function parameters, the approach provides a flexible framework for targeting transparency and generalisation. Simulation results confirm the excellent nonlinear modelling properties of an LM network and illustrate the potential benefits of the proposed LM control scheme.


Local model network Local controller network Flexible manipulator Genetic algorithms 


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© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.School of Marine Science and EngineeringPlymouth UniversityPlymouthUK
  2. 2.Department of Automatic Control and Systems EngineeringThe University of SheffieldSheffieldUK

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