LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Control of autoresonance in mechanical and physical models

Photo by clemono from unsplash

Autoresonant energy transfer has been considered as one of the most effective methods of excitation and control of high-energy oscillations for a broad range of physical and engineering systems. Nonlinear… Click to show full abstract

Autoresonant energy transfer has been considered as one of the most effective methods of excitation and control of high-energy oscillations for a broad range of physical and engineering systems. Nonlinear time-invariant feedback control provides effective self-tuning and self-adaptation mechanisms targeted at preserving resonance oscillations under variations of the system parameters but its implementation may become extremely complicated. A large class of systems can avoid nonlinear feedback, still producing the required state due to time-variant feed-forward frequency control. This type of control in oscillator arrays employs an intrinsic property of a nonlinear oscillator to vary both its amplitude and the frequency when the driving frequency changes. This paper presents a survey of recently published and new results studying possibilities and limitations of time-variant frequency control in nonlinear oscillator arrays. This article is part of the themed issue ‘Horizons of cybernetical physics’.

Keywords: physical models; control autoresonance; frequency; control; autoresonance mechanical; mechanical physical

Journal Title: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Year Published: 2017

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.