  The 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.
