This book is a companion text to Active Control of Sound by P.A. Nelson and S.J. Elliott, also published by Academic Press. It summarizes the principles underlying active vibration control and its practical applications by combining material from vibrations, mechanics, signal processing, acoustics, and control theory. The emphasis of the book is on the active control of waves in structures, the active isolation of vibrations, the use of distributed strain actuators and sensors, and the active control of structurally radiated sound. The feedforward control of deterministic disturbances, the active control of structural waves and the active isolation of vibrations are covered in detail, as well as the more conventional work on modal feedback. The principles of the transducers used as actuateors and sensors for such control strategies are also given an in-depth description. The reader will find particularly interesting the two chapters on the active control of sound radiation from structures: active structural acoustic control. The reason for controlling high frequency vibration is often to prevent sound radiation, and the principles and practical application of such techniques are presented here for both plates and cylinders. The volume is written in textbook style and is aimed at students, practicing engineers, and researchers.

Active control of vibration, 1st edition

In this paper we review essential aspects in- volved in the design of an active vibration control system. We present a generic procedure to the design process and give selective examples from the literature on relevant ma- terial. Together with examples of their applications, various topics are briefly introduced, such as structure modeling, model reduction, feedback control, feedforward control, con- trollability and observability, spillover, eigenstructure assign- ment (pole placement), coordinate coupling control, robust control, optimal control, state observers (estimators), intelli- gent structure and controller, adaptive control, active con- trol effects on the system, time delay, actuator-structure interaction, and optimal placement of actuators.

Active Structural Vibration Control: A Review

Precise positioning of piezo-actuated stages using hysteresis-observer based control

Fuzzy logic in control system: fuzzy logic controller controller part i

This paper considers the optimal placement of collocated piezoelectric actuator–sensor pairs on a thin plate using a model-based linear quadratic regulator (LQR) controller. LQR performance is taken as objective for finding the optimal location of sensor–actuator pairs. The problem is formulated using the finite element method (FEM) as multi-input–multi-output (MIMO) model control. The discrete optimal sensor and actuator location problem is formulated in the framework of a zero–one optimization problem. A genetic algorithm (GA) is used to solve the zero–one optimization problem. Different classical control strategies like direct proportional feedback, constant-gain negative velocity feedback and the LQR optimal control scheme are applied to study the control effectiveness.

https://iopscience.iop.org/article/10.1088/0964-1726/16/6/073/pdf

The optimal location of piezoelectric actuators and sensors for vibration control of plates

This paper presents the numerical modeling of a plate structure containing bonded piezoelectric material. Hamilton's principle is employed to derive the finite element equations using the mechanical energy of the structure and the electrical energy of the piezoelectric material. Then, a numerical model is developed based on Kirchhoff's plate theory. A computational program is implemented for analyzing the static and dynamic behavior of composite plates with piezoelectric layers symmetrically bonded to the top and bottom surfaces. A set of numerical simulations is performed and the results are compared with those from analytical formulation available in the literature and with software ANSYS® .

/pdf/finite-element-modeling-of-a-plate-with-localized-57oe5u0489.pdf

Finite element modeling of a plate with localized piezoelectric sensors and actuators

A self-organizing fuzzy logic controller for the active control of flexible structures using piezoelectric actuators

In this paper, a digital regulator is designed and experimentally implemented for a flexible beam type structure containing piezoelectric sensors and actuators by using optimal control design techniques. The controller consists of a linear quadratic regulator with a state estimator, namely a Kalman observer. The structure is a cantilever beam containing a set of sensor/actuator PVDF/PZT ceramic piezoelectric patches bonded to the beam surface at the optimal location obtained for the first three vibration modes. The equations of motion of the beam are developed by using the assumed modes technique for flexible structures in infinite-dimensional models. This paper uses a method of minimizing the effect of the removed higher order modes on the low frequency dynamics of the truncated model by adding a zero frequency term to the low order model of the system. A measure of the controllability and observability of the system based on the modal cost function for flexible structures containing piezoelectric elements (intelligent structures) is used. The observability and controllability measures are determined especially to guide the placement of sensors and actuators, respectively. The experimental and numerical transfer functions are adjusted by using an optimization procedure. Experimental results illustrate the optimal control design of a cantilever beam structure.

/pdf/experiments-on-optimal-vibration-control-of-a-flexible-beam-skq28g9ht7.pdf

Experiments on Optimal Vibration Control of a Flexible Beam Containing Piezoelectric Sensors and Actuators

This paper describes the use of artificial neural networks for the control of vibrations of a mechanical system using its experimental direct inverse model. The neural controller is trained to model the experimental inverse model of the plant using the backpropagation algorithm with simulated annealing. The inverse model of the plant is obtained by the training mechanism that uses experimental input and output data. After the training, the neural network is used as a forward controller. The efficiency and the robustness of the controller are shown through experimental tests. The neural control algorithm is implemented in a computer and the performance of controller is evaluated under a set of experimental tests made to the active control of vibrations of a mechanical system of one degree of freedom actuated by magnetic actuators.

A neural network-based direct inverse control for active control of vibrations of mechanical systems

This paper presents a design of adaptive fuzzy controllers applied to the control of vibrations in flexible structures containing distributed piezoelectric actuator patches. The adaptive fuzzy controller is constructed from a set of fuzzy IF-THEN rules whose parameters are adjusted on-line according to some adaptation law. The adaptive law is derived based on the Lyapunov's stability theory. This control methodology is experimentally verified in a steel cantilever test beam and a set of experimental tests are made in the system to verify the efficiency of the adaptive fuzzy controller proposed.

/pdf/on-line-control-of-a-flexible-beam-using-adaptive-fuzzy-4pe43sg7ea.pdf

J.F. Ribeiro

Papers

Finite element modeling of a plate with localized piezoelectric sensors and actuators

A self-organizing fuzzy logic controller for the active control of flexible structures using piezoelectric actuators

Experiments on Optimal Vibration Control of a Flexible Beam Containing Piezoelectric Sensors and Actuators

A neural network-based direct inverse control for active control of vibrations of mechanical systems

On-line control of a flexible beam using adaptive fuzzy controller and piezoelectric actuators