Robust parameter design (or, briefly, parameter design) has been widely used as a cost effective tool to reduce process variability by appropriate selection of control factors to make the process insensitive to noise. However, when there are strong noise factors in the process, use of parameter design alone may not be effective and an on-line control strategy can be used to compensate for the e...

This dissertation considers the application of recent robust control techniques to parameter-dependent mechanical systems. Particular emphasis is placed on the study of exible dynamic systems that possess lightly-damped, parameter-dependent, resonances at frequencies that are within the bandwidth of the controller. A detailed examination of an example system, highlighting the complexities assoc...

This paper focuses on several aspects to be considered when designing generic control strategies for Evolutionary Algorithms. We propose a method to encapsulate multiple parameters, reducing control to only one variable. This method allows to define generic control strategies regardless of the algorithm’s operators and of the problem to be solved. Three implementation-independent strategies are...

Find a state or output feedbac:k wlth flxed gains such that nlce stabllity (deflned by a regloo in tbe elgenvalue plane) ls robust wlth respect to !arge plant parameter varladoos, semor failures, and quantlzatJon effects in tbe controller. Keep tbe requlred magnltude of control Inputs smail in thls deslgn. A tool for tacldJ.ng suc:h problems by des1gB in tbe controller parameter space % ls intr...

The paper introduces novel techniques for achieving global convergence results and improving transient performance in stochastic adaptive control. For example, there is introduced switching between a least squares and an extended least squares parameter estimation algorithm according to an ill-conditioning measure, and there is appropriate selection of external persistently exciting signals, th...