Paper
15 March 2006 H-infinity controller design for structural damping
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Abstract
This paper describes a multivariable controller design procedure that uses mixed-sensitivity H-infinity control theory. The design procedure is based on the assumption that structural noise can be modeled as entering a state-space system through a random input matrix. The design process starts with a full-order flexible state-space model that undergoes a frequency-weighted balanced truncation to obtain a reduced-order model with excellent low frequency matching. Weighting functions are then created to specify the desired frequency range for disturbance rejection and controller bandwidth. A structural noise input matrix is also designed to identify system modes where maximal damping is desired. An augmented plant is then assembled using the reduced-order model, weighting functions and structural noise input matrix to create a mixed-sensitivity configuration. A state-space controller is then realized using an H-infinity design algorithm. A two-input, three-output, doubly cantilevered beam system provides a design example. A 174th-order, discrete-time, state-space model of the cantilevered beam system was used to generate a reduced 40th- order model. A 55th-order Hinfinity controller was then designed with a controller bandwidth of approximately 300 Hz. This non-square modern controller uses feedback signals from two piezoelectric sensors, each collocated with one of two piezoelectric actuators, and one highly non-collocated accelerometer. The two piezoelectric actuators provide the control actuation. Frequency analysis and time-domain simulations are utilized to demonstrate the damping performance.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Darren W. Rowen and Mark A. Hopkins "H-infinity controller design for structural damping", Proc. SPIE 6169, Smart Structures and Materials 2006: Damping and Isolation, 616904 (15 March 2006); https://doi.org/10.1117/12.658327
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KEYWORDS
Systems modeling

Data modeling

Actuators

Device simulation

System identification

Matrices

Process modeling

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