Batch process is a typical multi-phase process. Due to the interaction between the phases of the
batch process, high precision control in a single phase cannot guarantee high precision control of the whole batch
process. In order to solve this problem, the guaranteed cost iterative learning control (ILC) of multi-phase batch
processes is studied in this paper. Firstly, through introducing the output error, the state error and the extended
information, the multi-phase batch process is transformed into an equivalent 2D switched system which has
different dimensions. In addition, under the measurable condition, the guaranteed cost iterative learning control
law with extended information is designed. The proposed control law ensures not only the stability of the system
but also the optimal control performance. Next, in order to study the stability of the system and the minimum
running time under the condition of stable running, the multi-Lyapunov function method is used. By means of
the average dwell time method, the sufficient conditions ensuring system to be exponentially stable are given in
the form of linear matrix inequality (LMI). Finally, the injection molding process is taken as an example to make
simulation, which shows the feasibility and effectiveness of the proposed method.
WANG Limin (王立敏), WANG Runze (王润泽), XIONG Yuting (熊玉婷), WANG Haosen (王浩森), ZHU Lin (朱琳), ZHANG Ke (张可), GAO Furong (高福荣)
. Guaranteed Cost Iterative Learning Control for Multi-Phase Batch Processes[J]. Journal of Shanghai Jiaotong University(Science), 2018
, 23(6)
: 811
-819
.
DOI: 10.1007/s12204-018-2002-1
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