A fuzzy neural network based control system for active damping of slewing structures with piezoceramic actuators

Issam Zeinoun, Farshad Khorrami

Research output: Contribution to journalConference articlepeer-review


This paper presents a control scheme based on fuzzy logic and neural network algorithms and its application to vibration damping of slewing flexible structures with piezoceramic sensors and actuators. In particular, the algorithms are implemented on a flexible-link manipulator. Here, a fuzzy based adaptive controller is considered due to its simplicity and the fact that it does not require expressing the controller in terms of the system parameters, as is necessary in the case of self-tuning regulators. This controller is based on a functional fuzzy model where the consequents are crisp functions of the system states and/or inputs; these functions represent controllers designed for different operating regimes. The premise is constituted by the fuzzy subsets corresponding to the process parameters estimated in real time. The neural network is utilized for two different purposes: 1) derivation of a fuzzy model of the system (fuzzy system identification), 2) derivation of the rule base for the fuzzy logic controller through training. The effectiveness of this new scheme is verified on a clamped-free beam and a flexible-link manipulator instrumented with piezoceramic sensors and actuators. It will be shown that robust performance may be achieved in face of large parameter variations.

Original languageEnglish (US)
Pages (from-to)684-695
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - May 6 1994
Event1994 North American Conference on Smart Structures and Materials: Smart Structures and Intelligent Systems - Orlando, United States
Duration: Feb 13 1994Feb 18 1994

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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