Multi-objective evolutionary design of robust controllers on the grid

SHENFIELD, Alex and FLEMING, Peter (2014). Multi-objective evolutionary design of robust controllers on the grid. Engineering Applications of Artificial Intelligence, 27, 17-27.

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Coupling conventional controller design methods, model based controller synthesis and simulation, and multi-objective evolutionary optimisation methods frequently results in an extremely computationally expensive design process. However, the emerging paradigm of grid computing provides a powerful platform for the solution of such problems by providing transparent access to large-scale distributed high-performance compute resources. As well as substantially speeding up the time taken to find a single controller design satisfying a set of performance requirements this grid-enabled design process allows a designer to effectively explore the solution space of potential candidate solutions. An example of this is in the multi-objective evolutionary design of robust controllers, where each candidate controller design has to be synthesised and the resulting performance of the compensated system evaluated by computer simulation. This paper introduces a grid-enabled framework for the multi-objective optimisation of computationally expensive problems which will then be demonstrated using and example of the multi-objective evolutionary design of a robust lateral stability controller for a real-world aircraft using H ∞ loop shaping.

Item Type: Article
Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Identification Number:
Page Range: 17-27
Depositing User: Alex Shenfield
Date Deposited: 22 Jul 2014 14:24
Last Modified: 18 Mar 2021 06:09

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