Noise and vibration are often limiting factors in performance of many industrial systems. The conventional method of treatment is to redesign the system or to use passive damping. The former could be a costly exercise, while the latter, although effective at higher frequencies may be of little use at lower frequencies. Active noise and vibration control (ANVC) systems have emerged as viable technologies to fill this low-frequency gap.

This special section is aimed at sketching a broad perspective of the field by presenting a number of papers related to emerging technologies for ANVC systems. Following is an overview of the papers that are included in this special section.

The paper by Fang et al. is concerned with modeling, identification and control of interactions between the acoustic field and structure in a three-dimensional enclosure. One of the panels of the enclosure is vibrated, hence generating acoustic noise inside the enclosure. A reduced order model of the structure is then used to design a controller for broadband reduction of acoustic noise throughout the enclosure. The paper reports experimental implementation of a controller on a laboratory setup designed for this specific purpose.

Kermani, Moallem and Patel propose a methodology for optimal placement of a piezoelectric actuator on a flexible beam, with a view to vibration suppression in the structure. Their method is based on the SVD of the controllability Grammian of the system. They demonstrate that various parameters of the piezoelectric actuator, and the beam can be optimized by maximizing the singular value of a specific vibrating mode of the structure. They obtain optimal parameters for a flexible link with a piezoelectric transducer as a secondary actuator, and demonstrate that significant vibration attenuation can be achieved without spill over into out-of-bandwidth modes.

The paper by Fraanje et al. suggests a method for H2 optimal control design by estimating the controller directly from measured signals. This is done using subspace system identification and the internal model control approach. The authors illustrate their robust control design method on a vibrating plate with several sensors and actuators, hence a MIMO plant. They demonstrate that the robust controller stabilizes the system when an additional mass is added to the plate.

Bohn and co-authors investigate active vibration control of engine-induced vibration in automotive vehicles. They assume that the disturbance is entered the system at the input of the plant, and use a state observer to estimate the states of the disturbance model. They allow the disturbance to be of harmonic nature with time-varying fundamental frequency. The resulting observer is time-varying to effectively model the disturbance. They also report experimental results obtained from an active vibration control system in a car.

The paper by Dadfarnia and his co-authors proposes an observer-based regulator for a Cartesian robotic arm. The system is modeled as a cantilever beam with a translation base support. An electrodynamic shaker is used to control motion of the base, and a piezoelectric actuator, bonded to the surface of the beam is used to suppress residual vibration of the arm. The authors develop a model of the system using the assumed modes technique, design a reduced-order observer to estimate velocity related variables and design and implement a controller for the system. Furthermore, they report the experimental results, which closely match the simulations.

The paper by Snyder et al. is on sensing acoustical power radiated from vibrating structures. The sensor is made up of an array of microphones arranged in a hemisphere away from the structure. The total pressure is written as a quadratic function of the measured acoustical pressure at several locations in the hemisphere. This expression involves transfer functions between multipoles on the structure and microphones in the hemisphere. The strength of this paper is in using a minimum of structural information and promoting the idea of acoustic-centric approach. Active noise control is its intended application. The utility of the sensing method is experimentally demonstrated by implementing an adaptive feedforward control scheme to reduce the radiated noise. Experimental results demonstrate that accurate power sensing results can be obtained with a very small number of multipoles.

Finally, the paper by Su deals with the problem of vibration-induced phase noise in quartz crystal oscillators. Active vibration control method is generally used to reduce the vibration-induced electrical noise in quartz crystal oscillators. One such method is polarization effect tuning, an active vibration control method that applies an electrical signal to electrodes of the crystal resonator to form a vibration cancellation signal, which is intended to reduce the noise at the electrical end to render the mechanical vibration virtually invisible. The author proposes an improvement to the polarization-effect tuning technique by incorporating a compensator into the tuning path in a way that the frequency response of the vibration cancellation signal matches the frequency response of the vibration-induced phase noise, hence reducing the noise level significantly.