Application of IFT and SPSA to Servo System Control

Authors:
Mircea-Bogdan Radac;Radu-Emil Precup;Emil M. Petriu;Stefan Preitl
Affiliations:
Department of Automation and Applied Informatics, Politehnica University of Timisoara, Timisoara, Romania;Department of Automation and Applied Informatics, Politehnica University of Timisoara, Timisoara, Romania;School of Information Technology and Engineering, University of Ottawa, Ottawa, Canada;Department of Automation and Applied Informatics, Politehnica University of Timisoara, Timisoara, Romania
Venue:
IEEE Transactions on Neural Networks - Part 2
Year:
2011

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Abstract

This paper treats the application of two data-based model-free gradient-based stochastic optimization techniques, i.e., iterative feedback tuning (IFT) and simultaneous perturbation stochastic approximation (SPSA), to servo system control. The representative case of controlled processes modeled by second-order systems with an integral component is discussed. New IFT and SPSA algorithms are suggested to tune the parameters of the state feedback controllers with an integrator in the linear-quadratic-Gaussian (LQG) problem formulation. An implementation case study concerning the LQG-based design of an angular position controller for a direct current servo system laboratory equipment is included to highlight the pros and cons of IFT and SPSA from an application's point of view. The comparison of IFT and SPSA algorithms is focused on an insight into their implementation.