location: Current position: Prof. Tao Liu >> Scientific Research >> Paper Publications

Robust PID based indirect-type iterative learning control for batch processes with time-varying uncertainties

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Indexed by:期刊论文

Date of Publication:2014-12-01

Journal:JOURNAL OF PROCESS CONTROL

Included Journals:SCIE、EI

Volume:24

Issue:12,SI

Page Number:95-106

ISSN No.:0959-1524

Key Words:Batch process; Iterative learning control (ILC); Proportional-integral-derivative (PID) controller; Time-varying uncertainty; Robust H infinity control objective

Abstract:Based on the proportional-integral-derivative (PID) control structure widely used in engineering applications, a robust indirect-type iterative learning control (ILC) method is proposed for industrial batch processes subject to time-varying uncertainties. An important merit is that the proposed ILC design is independent of the PID tuning that aims primarily to hold robust stability of the closed-loop system, owing to the fact that the ILC updating law is implemented through adjusting the setpoint of the closed-loop PID control structure plus a feedforward control to the plant input from batch to batch. According to the robust H infinity control objective, a robust discrete-time PID tuning algorithm is given in terms of the plant state-space model description to accommodate for time-varying process uncertainties. For the batchwise direction, a robust ILC updating law is developed based on the two-dimensional (2D) control system theory. Only measured output errors of current and previous cycles are used to implement the proposed ILC scheme for the convenience of practical application. An illustrative example from the literature is adopted to demonstrate the effectiveness and merits of the proposed ILC method. (C) 2014 Elsevier Ltd. All rights reserved.

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