  This paper presents a multi-variable Model Predictive Control (MPC) based
controller for the one-staged refrigeration cycle model described in the
PID2018 Benchmark Challenge. This model represents a two-input, two-output
system with strong nonlinearities and high coupling between its variables. A
general purpose optimal control problem (OCP) solver Matlab toolbox called
RIOTS is used as the OCP solver for the proposed MPC scheme which allows for
straightforward implementation of the method and for solving a wide range of
constrained linear and nonlinear optimal control problems. A conditional
integral (CI) compensator is embedded in the controller to compensate for the
small steady state errors. This method shows significant improvements in
performance compared to both discrete decentralized control (C1) and
multi-variable PID controller (C2) originally given in PID2018 Benchmark
Challenge as a baseline. Our solution is introduced in detail in this paper and
our final results using the overall relative index, $J$, are 0.2 over C1 and
0.3 over C2, respectively. In other words, we achieved 80% improvement over C1
and 70% improvement over C2. We expect to achieve further improvements when
some optimized searching efforts are used for MPC and CI parameter tuning.
