An interval-consistency-based hybrid optimization algorithm for automatic loop shaping in quantitative feedback theory design

Abstract

A computationally efficient method for automatic synthesis of quantitative feedback theory (QFT)-based robust controllers is proposed. The synthesis problem consists of obtaining a fixed structure QFT controller that ensures stability and achieves the performance specifications in the presence of disturbances and parametric uncertainty. The proposed method uses an interval consistency technique (hull consistency HC4) and hybrid optimization. The HC4 method is used to remove inconsistent values, which are not part of the solution in the controller parameter regions. The hybrid part incorporates interval global optimization and nonlinear local optimization methods. The proposed algorithm is illustrated by means of two examples. The first one concerns the longitudinal motion control of an aircraft system (flexible), while the second one describes the experimental study of the position control of the industrial plant emulator setup. The robustness of the designed control system for emulator setup is validated by adding extra weights on the load disk in the presence of disturbances. The experimental results show that the designed controller satisfies the robust performance specifications.

Keywords

Automatic loop shaping global optimization interval consistency technique industrial plant emulator QFT robust control

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