A state space modeling and control method for multivariable smart structural systems

• Published in: Smart materials and structures Vol. 5; no. 4; pp. 386 - 399
• Main Authors: Butler, Robert, Rao, Vittal
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.08.1996; Institute of Physics
• Subjects: Exact sciences and technology; Fundamental areas of phenomenology (including applications); Physics; Solid mechanics; Structural and continuum mechanics; Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...); Vibrations and mechanical waves; Multivariable control; Active system; Vinylidene fluoride polymer; Piezoelectricity; Vibration control; State space; Numerical method; System identification; Algorithm; Monitoring control system; Intelligent system
• DOI: 10.1088/0964-1726/5/4/002
• ISSN: 0964-1726

A system identification technique for the derivation of minimal, continuous time state variable models for multivariable smart structural systems is presented. The structural identification technique is based on the measurement of eigenvalues and eigenvectors of the structure. Two sensors are required for each mode included in the structural system model. Unlike computational system identification techniques, the relatively large number of sensors simplifies the identification process making it ideal for systems with several inputs and outputs. Additionally, the identification technique allows the implementation of MIMO full state feedback controllers with simple analog hardware. The eigenvectors of distributed parameter structural systems are examined. It is shown that direct measurements of the eigenvalues and eigenvectors are possible for the lightly damped structural systems considered in this paper. The identification procedure utilizes n measurement variables of the structural system with n/2 modes to produce a nth order model. This allows for the measurements to be defined as the model states. It is shown that an array consisting of n/2 sensors on the structure and some simple analog hardware suffice for the identification. For symmetrical systems, it is shown that the number of sensors required for the model identification is reduced further. (Author)