Abstract
Least effort controller design procedures, for multivariable, machine tool models, are considered. The employment of these regulators for adaptive system analysis is proposed. An approximate relationship between the nonlinear, stochastic process system dynamics and the linear, mid-range model is employed. Model-reference, adaptive, multivariable control is advocated with the model-system error vector augmenting the actuator signals, during the system transient. The amplitude of the model-system uncertainty and the guarantee of closed-loop stability are established as mandatory performance requirements. To illustrate the theoretical procedures outlined, a nonlinear, distributed-lumped parameter model is employed, in a machine tool system application study. An adaptive model-reference control strategy is formulated using a simple, analytical representation for the system. The response of the adaptive system, following input and cutting load disturbances, is computed and the effectiveness of this form of controller is commented upon.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
