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Quantitative-fuzzy Controller Design for Multivariable Systems with Uncertainty

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  • Control Theory and Applications
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Abstract

This work serves as a pioneer contribution in terms of application of Quantitative Feedback Theory (QFT) methodology and fuzzy logic method to design a controller for MIMO systems. Due to the presence of uncertainty in multivariable dynamic systems, the application of robust control methods for achieving high accuracy in tracking is inevitable. On the other hand, application of QFT to MIMO uncertain systems still remains to be one of the most difficult control problems for engineers. In this paper, authors attempt to simplify the MIMO control problem by proposing a new algorithm which joins QFT and fuzzy techniques. In order to illustrate the utility of the proposed algorithm, its application on a two degree of freedom link robot manipulator is depicted. Initially, a QFT controller is designed for each link to overcome the track and disturbance rejection problems. Then, a bi-level tuned PD-fuzzy controller is employed as one strategy for curbing probable errors in the previous controller. The controller design was carried in the following stages; first, a linear PD controller independently applied to each actuator. Then, fuzzy rules were developed to design a fuzzy PD controller. Fuzzy controller normalizing parameters were regulated according to maximum PD control errors. In the second stage, named nonlinear tuning, other parameters of the fuzzy controller were tuned using genetic algorithms. Finally, nonlinear simulations of arbitrary path tracking shows that the proposed controller has a consistent tracking ability, and also it can clearly be seen that the mentioned approach is precise and very simple in comparison to other MIMO control techniques.

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Authors and Affiliations

  1. Department of Mechanical Engineering, University of Torbat-Heydarieh, Torbat Heydarieh, Khorasan Razavi, Iran

    Mohammad Reza Gharib

  2. Department of Mechanical Engineering, Lamar University, Beaumont, TX, USA

    Armin Daneshvar

Authors
  1. Mohammad Reza Gharib
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  2. Armin Daneshvar
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Corresponding author

Correspondence to Mohammad Reza Gharib.

Additional information

Recommended by Associate Editor Yangmin Li under the direction of Editor Euntai Kim.

Mohammad Reza Gharib received the Ph.D degree in Mechanical Engineering from Ferdowsi University of Mashhad. His research interests include robust control, robotics, and Modeling. Professor Gharib joined the faculty of the Department of Mechanical and Industrial Engineering at University of Torbat Heydarieh in 2014 as a chair of department.

Armin Daneshvar received his master’s degree in Mechanical Engineering from Lamar University, Beaumont, TX, USA, in 2019. His interests include dynamics, robust control, robotics, computational mechanics.

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Gharib, M.R., Daneshvar, A. Quantitative-fuzzy Controller Design for Multivariable Systems with Uncertainty. Int. J. Control Autom. Syst. 17, 1515–1523 (2019). https://doi.org/10.1007/s12555-018-0567-y

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  • DOI: https://doi.org/10.1007/s12555-018-0567-y

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