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Structured Robust Control for a Pmdc Motor Speed Controller Using Swarm Optimization and Mixed Sensitivity Approach

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Intelligent Automation and Computer Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 52))

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Abstract

This paper proposes a new technique for designing a robust DC motor speed controller based on the concepts of fixed-structure robust controller and a mixed sensitivity method. Performance is specified by selecting the closed-loop objective weight, and uncertainties caused by the parameter changes of motor resistance, motor inductance and load are used to formulate the multiplicative uncertainty weight. Particle Swarm Optimization (PSO) is adopted to solve the optimization problem and find the optimal structured controller. The proposed technique can solve the problem of complicated and high order controller of conventional full order H controller and also retains the robust performance of conventional H optimal control. The performance and robustness of the proposed speed controller are investigated in a Permanent Magnet DC (PMDC) motor in comparison with the controllers designed by conventional H optimal control and conventional ISE method. Results of simulations demonstrate the advantages of the proposed controller in terms of simple structure and robustness against plant perturbations and disturbances. Experiments are performed to verify the effectiveness of the proposed technique.

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Acknowledgements

This research work was funded by King Mongkut’s Institute of Technology Ladkrabang Research fund. This work was also supported by DSTAR, KMITL and NECTEC, NSTDA.

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Correspondence to Somyot Kaitwanidvilai .

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© 2009 Springer Science+Business Media B.V.

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Kaitwanidvilai, S., Ngamroo, I. (2009). Structured Robust Control for a Pmdc Motor Speed Controller Using Swarm Optimization and Mixed Sensitivity Approach. In: Huang, X., Ao, SI., Castillo, O. (eds) Intelligent Automation and Computer Engineering. Lecture Notes in Electrical Engineering, vol 52. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3517-2_34

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  • DOI: https://doi.org/10.1007/978-90-481-3517-2_34

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  • Publisher Name: Springer, Dordrecht

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