J.W. Li, X.B. Chen, and W.J. Zhang (Canada)
Modelling, dynamics, axiomatic design, and control NOMENCLATURE ADT axiomatic design theory DPi the ith design parameter Di(t) the ith discrepancy E(t) error of model prediction FRi the ith functional requirement Gi(s) the ith transfer function K steady-state gain of step response (µm/v) L time delay coefficient (s) os% percent overshoot of step response Pi the ith peak tp peak time (s) tpa average peak time (s) ipt peak time of the ith peak (s) ts settling time of step resp
This paper presents a novel approach to modeling dynamic systems with the purpose of control. The philosophy behind this approach is based on our observation that there is a complete analogy between system design and system modeling; in particular, functional requirements (in design) correspond to dynamics (in modeling) of the system to be modeled and design parameters (in design) correspond to models (in modeling). With this analogy, we assume that a model can be decomposed into a set of basic models. We then apply the axiomatic design theory (ADT) developed by N.P. Suh in late 1980s, in particular Independence Axiom of ADT, to determine these basic models. Experiments were conducted and are presented in this paper. The experimental results show the effectiveness of the proposed approach to modeling complex dynamic systems for the purpose of control.
Important Links:
Go Back
