A comparison of software-based approaches to identifying FOPDT and SOPDT model parameters from process step response data

摘要: System identification is the experimental approach to deriving process models, which can take many forms depending upon their intended use. In work described in this paper, ultimate aim use them design of controllers for regulating engineering processes. Modelling always involves approximations since all real systems are some extent non-linear, time-varying, and distributed. Thus, it highly improbable that any set models will contain ‘true’ system structure. A more realistic therefore identify a model provides an acceptable approximation, context application used. controller design, first step often determine using frequency response data. This paper compares different modern software approaches exploit data, where either first- or second-order-plus-dead-time (FOPDT SOPDT) transfer function. They include integral equation method, algorithm available MATLAB Optimization Toolbox, recently developed in-house uses particle swarm optimisation (PSO) approach.