Zhao, YangDehghan, SinaAtes, AbdullahYuan, JieZhou, FengyuLi, YanChen, YangQuan2024-08-042024-08-0420182405-8963https://doi.org/10.1016/j.ifacol.2018.06.175https://hdl.handle.net/11616/983513rd IFAC Conference on Advances in Proportional-Integral-Derivative Control (PID) -- MAY 09-11, 2018 -- Ghent Univ, Ghent, BELGIUMThe design and application of learning feedforward controllers (LFFC) for the one staged refrigeration cycle model described in the PID2018 Benchmark Challenge is presented, and its effectiveness is evaluated. The control system consists of two components: 1) a preset PID component and 2) a learning feedforward component which is a function approximator that is adapted on the basis of the feedback signal. A B-spline network based LFFC and a low-pass filter based LFFC are designed to track the desired outlet temperature of evaporator secondary flux and the superheating degree of refrigerant at evaporator outlet. Encouraging simulation results are included. Qualitative and quantitative comparison results evaluations show that, with little effort, a high-performance control system can be obtained with this approach. Our initial simple attempt of low-pass filter based LFFC and B-spline network based LFFC give J=0.4902 and J=0.6536 relative to the decentralized PID controller, respectively. Besides, the initial attempt of a combination controller of our optimized PI controller and low-pass filter LFFC gives J=0.6947 relative to the multi-variable PID controller. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.eninfo:eu-repo/semantics/openAccessLearning feedforward controlvapour-compression refrigeration systemconditional integrationPID 2018 Benchmark ChallengePID2018 Benchmark Challenge: learning feedforward controlConference Object51466366810.1016/j.ifacol.2018.06.1752-s2.0-85048794308N/AWOS:000435709300114N/A