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Utilizing higher-order neural networks in U-model based controllers for stable nonlinear plants

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  • Control Applications
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Abstract

The use of intelligent control schemes in nonlinear model based control (NMBC) has gained widespread popularity. Neural networks, in particular, have been used extensively to model the dynamics of nonlinear plants. However, in most cases, these models do not lend themselves to easy maneuvering for controller design. Therefore, a common need is being felt to develop intelligent control strategies that lead to computationally simple control laws. To address this issue, we recently proposed a U-model based controller utilizing nonlinear adaptive filters. The present work extends that concept further to include higher-order neural networks (HONN) for better approximation. The main feature of the proposed structure is its ability to capture higher-order nonlinear properties of the input pattern space while allowing the synthesis of a simple control law. The effectiveness of the proposed scheme is demonstrated through application to various nonlinear models and a comparison with the Backstepping controller is presented.

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Authors and Affiliations

  1. ECE, SQU, Muscat, Oman

    Muhammed Shafiq

  2. Dept. of Electrical Engineering, Karlstad University, SE-651 88, Karlstad, Sweden

    Naveed R. Butt

Authors
  1. Muhammed Shafiq
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  2. Naveed R. Butt
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Corresponding author

Correspondence to Muhammed Shafiq.

Additional information

Recommended by Editor Hyun Seok Yang. We acknowledge support of Sulatan Qaboos University, Muscat, Oman for this research work.

Muhammad Shafiq received his BE degree in Electronic Engineering from NED University, Karachi, Pakistan in 1989. He completed his PhD studies in information and computer engineering at Chiba University, Chiba, Japan in 1997. He worked as technical manager at Thalus, Sauadai Arabai. He served King Fahd University of Petroleum and Minerals as faculty member. He worked as a professor under higher education commission at GIKI and IIUI, Pakistan. Presently, he is working as faculty member in ECE, SQU, Oman.He worked with Pakistan Engineering Council as a member of accreditation teams formed for accreditating several electrical, electronic and mechatronics engineering programs in Pakistan. He was member of national curriculum development committee for communication systems under HEC, Pakistan. He has supervised serveral MS and PhD thesis. He is among the authors of more than eight journal and conference papers. His research interests include applied nonlinear control, adaptive control, and soft computing techniques applied to control systems.

Naveed R. Butt received his B.S. degree in Lasers and Optoelectronics from the GIK Institute, Pakistan, in 2002. He received his Master’s degree in Systems Engineering (Automation and Control) in 2006 from KFUPM, Saudi Arabia. He is currently working towards a Ph.D. degree with Lund University, Sweden. He was previously a Research Assistant with KFUPM in 2004. His research interests include: statistical signal processing, system identification, and intelligent systems.

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Shafiq, M., Butt, N.R. Utilizing higher-order neural networks in U-model based controllers for stable nonlinear plants. Int. J. Control Autom. Syst. 9, 489–496 (2011). https://doi.org/10.1007/s12555-011-0308-y

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  • DOI: https://doi.org/10.1007/s12555-011-0308-y

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