Advances and Trends in Mathematical Modelling, Control and Identification of Vibrating Systems

Edited by
May 2022
132 pages
  • ISBN978-3-0365-3949-2 (Hardback)
  • ISBN978-3-0365-3950-8 (PDF)

This book is a reprint of the Special Issue Advances and Trends in Mathematical Modelling, Control and Identification of Vibrating Systems that was published in

Computer Science & Mathematics
Physical Sciences
Public Health & Healthcare

This book introduces novel results on mathematical modelling, parameter identification, and automatic control for a wide range of applications of mechanical, electric, and mechatronic systems, where undesirable oscillations or vibrations are manifested. The six chapters of the book written by experts from international scientific community cover a wide range of interesting research topics related to: algebraic identification of rotordynamic parameters in rotor-bearing system using finite element models; model predictive control for active automotive suspension systems by means of hydraulic actuators; model-free data-driven-based control for a Voltage Source Converter-based Static Synchronous Compensator to improve the dynamic power grid performance under transient scenarios; an exact elasto-dynamics theory for bending vibrations for a class of flexible structures; motion profile tracking control and vibrating disturbance suppression for quadrotor aerial vehicles using artificial neural networks and particle swarm optimization; and multiple adaptive controllers based on B-Spline artificial neural networks for regulation and attenuation of low frequency oscillations for large-scale power systems. The book is addressed for both academic and industrial researchers and practitioners, as well as for postgraduate and undergraduate engineering students and other experts in a wide variety of disciplines seeking to know more about the advances and trends in mathematical modelling, control and identification of engineering systems in which undesirable oscillations or vibrations could be presented during their operation.

  • Hardback
© 2022 by the authors; CC BY-NC-ND license
B-spline neural networks; adaptive power system control; coordinated multiple controllers; StatCom; exact plate theory; thick plate; bending vibration; partial differential operator theory; gauge condition; data-driven control; reactive power compensation; STATCOM; voltage control; voltage source converter; quadrotor UAV; artificial neural networks; robust control; Taylor series; B-splines; particle swarm optimization; active suspension; model predictive control; linear parameter varying; ellipsoidal set; attraction sets; quadratic stability; algebraic identification; rotor-bearing system; finite element model; rotordynamic coefficients