De-Centralized and Centralized Control for Realistic EMS Maglev Systems

A comparative study of de-centralized and centralized controllers when used with real EMS Maglev Systems is introduced. This comparison is divided into two parts. Part I is concerned with numerical simulation and experimental testing on a two ton six-magnet EMS Maglev vehicle. Levitation and lateral control with these controllers individually and when including flux feedback control in combination with these controllers to enhance stability are introduced. The centralized controller is better than the de-centralized one when the system is exposed to a lateral disturbing force such as wind gusts. The flux feedback control when combined with de-centralized or centralized controllers does improve the stability and is more resistant and robust with respect to the air gap variations. Part II is concerned with the study of Maglev vehicle-girder dynamic interaction system and the comparison between these two controllers on this typical system based on performance and ride quality achieved. Numerical simulations of the ODU EMS Maglev vehicle interacting with girder are conducted with these two different controllers. The de-centralized and centralized control for EMS Maglev systems that interact with a flexible girder provides similar ride quality

New design paradigms for MIMO control system synthesis

Abstract: "This report examines the use of Gain Plots (GPs), a new graphical representation and perspective on the Evans root locus, for analysis and design of multivariable feedback control systems. The development is based on the adjustment of a scalar, forward loop, proportional control gain cascaded with a square multi-input, multi-output (MIMO) plant employed in an output feedback configuration. By tracking the closed-loop eigenvalues as an explicit function of gain, it is possible to visualize the MIMO root loci in a set of plots, the GPs, depicting the polar coordinates of each eigenvalue in the complex plane. The GPs consist of two graphs: (i) magnitude of system eigenvalues vs. gain, and (ii) argument (angle) of system eigenvalues vs. gain.The concept of GPs is developed in detail in a companion report focusing on single-input, single-output systems (Kurfess and Nagurka, 1991a). By identifying closed-loop eigenvalue trajectories, the GPs impart significant insight for determining the values of scalar gain that render a MIMO closed-loop system either stable or unstable. Furthermore, by exposing the correspondence of gain values to specific eigenvalueangles and magnitudes, the GPs are useful for evaluating the migration of closed- loop eigenvalues toward finite and infinite transmission zeros. The GPs reveal MIMO eigenvalue information unambiguously in a new and precise manner, that is not available in a standard MIMO root locus plot.Thus, GPs significantly enhance the control engineer's multivariable systems toolbox.