Title: Nonlinear full-order observer-based controller design for active magnetic levitation via LQR-feedback linearisation
Authors: Abdollha M. Benomair; M. Osman Tokhi
Addresses: Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK ' Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK
Abstract: Magnetic levitation (Maglev) systems are highly beneficial in industrial applications owing to their reduced power consumption, increased power efficiency and reduced cost of maintenance. Common applications include Maglev power generation (e.g., wind turbine), Maglev trains and medical devices (e.g., magnetically suspended artificial heart pump). This paper presents the exact input-state feedback linearisation of a nonlinear Maglev system using estimated states. The observed states from a nonlinear dynamic full-order observer are used as inputs to the controller where the control law does not need to be expressed in terms of all measured variables. Then, a linear quadratic regulator is used as an optimal controller for the linearised model to guarantee the stability of the observer-based control scheme and, finally, a tracking controller for magnetic levitation is derived.
Keywords: magnetic levitation systems; MLS; Maglev; linear quadratic regulator; LQR; exact state input linearisation; nonlinear observers; full-order observers; controller design; feedback linearisation; optimal control; tracking control.
International Journal of Modelling, Identification and Control, 2016 Vol.26 No.1, pp.59 - 67
Available online: 14 Jul 2016 *Full-text access for editors Access for subscribers Purchase this article Comment on this article