Paper
24 July 1998 Robust intelligent control of structures using piezoceramic materials
Peter Mayhan, Gregory N. Washington
Author Affiliations +
Abstract
The use of smart materials (piezoceramic elements) in structure vibration damping has risen in popularity. The ability to use these materials as both sensors, capturing a voltage upon straining of the material, and actuators, acquiring a displacement due to an electric voltage, has increased. The work presented in this paper develops the use of robust intelligent control as applied to smart materials. A steel cantilever beam was constructed as the experimental (physical) plant. Piezoceramic material, lead zirconate titanate, was surface mounted as both sensors and actuators. The controller was formed using algorithms produced from adaptive fuzzy controls. Fuzzy model reference learning control (FMRLC) is a learning system with the capability to improve its performance over a period of time when various plant uncertainties are introduced. The expected goal of this paper is to dampen the fundamental vibration mode of the beam utilizing the intelligent control algorithm developed. Other controllers, such as positive position feedback (PPF) and direct fuzzy (DF), were developed and compared to the adaptive fuzzy controller. The robustness of the system was also examined when the cantilever beam system properties changed. Extra masses were added to account for the variations of the system parameters. The FMRLC controller showed a dramatic improvement over the PPF and DF. It is the adaptive nature of the FMRLC that makes the system robust to parameter changes.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter Mayhan and Gregory N. Washington "Robust intelligent control of structures using piezoceramic materials", Proc. SPIE 3323, Smart Structures and Materials 1998: Mathematics and Control in Smart Structures, (24 July 1998); https://doi.org/10.1117/12.316314
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Cited by 2 scholarly publications.
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KEYWORDS
Fuzzy logic

Actuators

Systems modeling

Sensors

Control systems

Process control

Algorithm development

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