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EN
Predictive Functional Control (PFC), belonging to the family of predictive control techniques, has been demonstrated as a powerful algorithm for controlling process plants. The input/output PFC formulation has been a particularly attractive paradigm for industrial processes, with a combination of simplicity and effectiveness. Though its use of a lag plus delay ARX/ARMAX model is justified in many applications, there exists a range of process types which may present difficulties, leading to chattering and/or instability. In this paper, instability of first order PFC is addressed, and solutions to handle higher order and difficult systems are proposed. The input/output PFC formulation is extended to cover the cases of internal models with zero and/or higher order pole dynamics in an ARX/ARMAX form, via a parallel and cascaded model decomposition. Finally, a generic form of PFC, based on elementary outputs, is proposed to handle a wider range of higher order oscillatory and non-minimum phase systems. The range of solutions presented are supported by appropriate examples.
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Content available remote Analytical Design of Stable Continuous-Time Generalised Predictive Control
EN
With a recently renewed interest in the continuous-time approach to control system design the continuous-time generalised predictive control (CGPC) is also worth considering. The main objective of this presentation is the development of an analytical perspective that results in explicit design procedures for stable control of both minimum-phase and non-minimum-phase SISO systems. The basic project idea is founded on a set of closed-loop prototype characteristics with definite time-domain specifications.
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